diff --git a/.devops/nix/package.nix b/.devops/nix/package.nix
index 1c9633cdf..e8d5b0bd9 100644
--- a/.devops/nix/package.nix
+++ b/.devops/nix/package.nix
@@ -214,7 +214,6 @@ effectiveStdenv.mkDerivation (
         (cmakeBool "LLAMA_CUDA" useCuda)
         (cmakeBool "LLAMA_HIPBLAS" useRocm)
         (cmakeBool "LLAMA_METAL" useMetalKit)
-        (cmakeBool "LLAMA_MPI" useMpi)
         (cmakeBool "LLAMA_VULKAN" useVulkan)
         (cmakeBool "LLAMA_STATIC" enableStatic)
       ]
diff --git a/.github/labeler.yml b/.github/labeler.yml
new file mode 100644
index 000000000..a67f78044
--- /dev/null
+++ b/.github/labeler.yml
@@ -0,0 +1,78 @@
+# https://github.com/actions/labeler
+
+SYCL:
+    - changed-files:
+        - any-glob-to-any-file:
+            - ggml-sycl.h
+            - ggml-sycl.cpp
+            - README-sycl.md
+Nvidia GPU:
+    - changed-files:
+        - any-glob-to-any-file:
+            - ggml-cuda/**
+Vulkan:
+    - changed-files:
+        - any-glob-to-any-file:
+            - ggml_vk_generate_shaders.py
+            - ggml-vulkan*
+documentation:
+    - changed-files:
+        - any-glob-to-any-file:
+            - docs/**
+            - media/**
+testing:
+    - changed-files:
+        - any-glob-to-any-file:
+            - tests/**
+build:
+    - changed-files:
+        - any-glob-to-any-file:
+            - cmake/**
+            - CMakeLists.txt
+            - CMakePresets.json
+            - codecov.yml
+examples:
+    - changed-files:
+        - any-glob-to-any-file: examples/**
+devops:
+    - changed-files:
+        - any-glob-to-any-file:
+            - .devops/**
+            - .github/**
+            - ci/**
+python:
+    - changed-files:
+        - any-glob-to-any-file:
+            - "**/*.py"
+            - requirements/**
+            - gguf-py/**
+            - .flake8
+script:
+    - changed-files:
+        - any-glob-to-any-file:
+            - scripts/**
+android:
+    - changed-files:
+        - any-glob-to-any-file:
+            - examples/llama.android/**
+server:
+    - changed-files:
+        - any-glob-to-any-file:
+            - examples/server/**
+ggml:
+    - changed-files:
+        - any-glob-to-any-file:
+            - ggml.c
+            - ggml.h
+            - ggml-*.c
+            - ggml-*.h
+            - ggml-cuda/**
+nix:
+    - changed-files:
+        - any-glob-to-any-file:
+            - "**/*.nix"
+            - .github/workflows/nix-*.yml
+            - .devops/nix/nixpkgs-instances.nix
+embedding:
+    - changed-files:
+        - any-glob-to-any-file: examples/embedding/
diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 0109cc004..7b616281b 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -271,49 +271,15 @@ jobs:
           path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-x64.zip
           name: llama-bin-ubuntu-x64.zip
 
-#  ubuntu-latest-cmake-sanitizer:
-#    runs-on: ubuntu-latest
-#
-#    continue-on-error: true
-#
-#    strategy:
-#      matrix:
-#        sanitizer: [ADDRESS, THREAD, UNDEFINED]
-#        build_type: [Debug, Release]
-#
-#    steps:
-#      - name: Clone
-#        id: checkout
-#        uses: actions/checkout@v4
-#
-#      - name: Dependencies
-#        id: depends
-#        run: |
-#          sudo apt-get update
-#          sudo apt-get install build-essential
-#
-#      - name: Build
-#        id: cmake_build
-#        run: |
-#          mkdir build
-#          cd build
-#          cmake .. -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON -DCMAKE_BUILD_TYPE=${{ matrix.build_type }}
-#          cmake --build . --config ${{ matrix.build_type }} -j $(nproc)
-#
-#      - name: Test
-#        id: cmake_test
-#        run: |
-#          cd build
-#          ctest -L main --verbose --timeout 900
-
-  ubuntu-latest-cmake-mpi:
+  ubuntu-latest-cmake-sanitizer:
     runs-on: ubuntu-latest
 
     continue-on-error: true
 
     strategy:
       matrix:
-        mpi_library: [mpich, libopenmpi-dev]
+        sanitizer: [ADDRESS, THREAD, UNDEFINED]
+        build_type: [Debug, Release]
 
     steps:
       - name: Clone
@@ -324,21 +290,21 @@ jobs:
         id: depends
         run: |
           sudo apt-get update
-          sudo apt-get install build-essential ${{ matrix.mpi_library }}
+          sudo apt-get install build-essential
 
       - name: Build
         id: cmake_build
         run: |
           mkdir build
           cd build
-          cmake -DLLAMA_MPI=ON ..
-          cmake --build . --config Release -j $(nproc)
+          cmake .. -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON -DCMAKE_BUILD_TYPE=${{ matrix.build_type }}
+          cmake --build . --config ${{ matrix.build_type }} -j $(nproc)
 
       - name: Test
         id: cmake_test
         run: |
           cd build
-          ctest -L main --verbose
+          ctest -L main --verbose --timeout 900
 
   ubuntu-latest-cmake-rpc:
     runs-on: ubuntu-latest
diff --git a/.github/workflows/labeler.yml b/.github/workflows/labeler.yml
new file mode 100644
index 000000000..368dbdbe5
--- /dev/null
+++ b/.github/workflows/labeler.yml
@@ -0,0 +1,17 @@
+name: "Pull Request Labeler"
+on:
+- pull_request_target
+
+jobs:
+  labeler:
+    permissions:
+      contents: read
+      pull-requests: write
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+      with:
+        repository: "ggerganov/llama.cpp"
+    - uses: actions/labeler@v5
+      with:
+        configuration-path: '.github/labeler.yml'
diff --git a/.github/workflows/server.yml b/.github/workflows/server.yml
index afac89c5b..0789efd18 100644
--- a/.github/workflows/server.yml
+++ b/.github/workflows/server.yml
@@ -32,10 +32,8 @@ jobs:
 
     strategy:
       matrix:
-        # TODO: temporary disabled due to linux kernel issues
-        #sanitizer: [ADDRESS, THREAD, UNDEFINED]
-        sanitizer: [UNDEFINED]
-        build_type: [Debug]
+        sanitizer: [ADDRESS, THREAD, UNDEFINED]
+        build_type: [RelWithDebInfo]
         include:
           - build_type: Release
             sanitizer: ""
@@ -102,10 +100,8 @@ jobs:
               -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
           cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target server
 
-
       - name: Tests
         id: server_integration_tests
-        if: ${{ !matrix.disabled_on_pr || !github.event.pull_request }}
         run: |
           cd examples/server/tests
           PORT=8888 ./tests.sh
diff --git a/.github/workflows/zig-build.yml b/.github/workflows/zig-build.yml
deleted file mode 100644
index 747c35cc0..000000000
--- a/.github/workflows/zig-build.yml
+++ /dev/null
@@ -1,29 +0,0 @@
-name: Zig CI
-
-on:
-  pull_request:
-  push:
-    branches:
-      - master
-
-concurrency:
-  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
-  cancel-in-progress: true
-
-jobs:
-  build:
-    strategy:
-      fail-fast: false
-      matrix:
-        runs-on: [ubuntu-latest, macos-latest, windows-latest]
-    runs-on: ${{ matrix.runs-on }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-          fetch-depth: 0
-      - uses: goto-bus-stop/setup-zig@v2
-        with:
-          version: 0.11.0
-      - name: Build Summary
-        run: zig build --summary all -freference-trace
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 990e34b86..ef02ff669 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -1,4 +1,4 @@
-cmake_minimum_required(VERSION 3.14)  # for add_link_options and implicit target directories.
+cmake_minimum_required(VERSION 3.14) # for add_link_options and implicit target directories.
 project("llama.cpp" C CXX)
 include(CheckIncludeFileCXX)
 
@@ -77,6 +77,7 @@ option(LLAMA_AVX2                            "llama: enable AVX2"
 option(LLAMA_AVX512                          "llama: enable AVX512"                             OFF)
 option(LLAMA_AVX512_VBMI                     "llama: enable AVX512-VBMI"                        OFF)
 option(LLAMA_AVX512_VNNI                     "llama: enable AVX512-VNNI"                        OFF)
+option(LLAMA_AVX512_BF16                     "llama: enable AVX512-BF16"                        OFF)
 option(LLAMA_FMA                             "llama: enable FMA"                                ${INS_ENB})
 # in MSVC F16C is implied with AVX2/AVX512
 if (NOT MSVC)
@@ -122,9 +123,7 @@ set(LLAMA_METAL_MACOSX_VERSION_MIN "" CACHE STRING
                                              "llama: metal minimum macOS version")
 set(LLAMA_METAL_STD "" CACHE STRING          "llama: metal standard version (-std flag)")
 option(LLAMA_KOMPUTE                         "llama: use Kompute"                               OFF)
-option(LLAMA_MPI                             "llama: use MPI"                                   OFF)
 option(LLAMA_RPC                             "llama: use RPC"                                   OFF)
-option(LLAMA_QKK_64                          "llama: use super-block size of 64 for k-quants"   OFF)
 option(LLAMA_SYCL                            "llama: use SYCL"                                  OFF)
 option(LLAMA_SYCL_F16                        "llama: use 16 bit floats for sycl calculations"   OFF)
 set(LLAMA_SYCL_TARGET   "INTEL" CACHE STRING "llama: sycl target device")
@@ -134,6 +133,8 @@ set(LLAMA_SCHED_MAX_COPIES  "4" CACHE STRING "llama: max input copies for pipeli
 option(LLAMA_BUILD_TESTS                     "llama: build tests"    ${LLAMA_STANDALONE})
 option(LLAMA_BUILD_EXAMPLES                  "llama: build examples" ${LLAMA_STANDALONE})
 option(LLAMA_BUILD_SERVER                    "llama: build server example"                      ON)
+option(LLAMA_LASX                            "llama: enable lasx"                               ON)
+option(LLAMA_LSX                             "llama: enable lsx"                                ON)
 
 # add perf arguments
 option(LLAMA_PERF                            "llama: enable perf"                               OFF)
@@ -382,10 +383,6 @@ if (LLAMA_LLAMAFILE)
     set(GGML_SOURCES_LLAMAFILE sgemm.cpp)
 endif()
 
-if (LLAMA_QKK_64)
-    add_compile_definitions(GGML_QKK_64)
-endif()
-
 if (LLAMA_CUBLAS)
     message(WARNING "LLAMA_CUBLAS is deprecated and will be removed in the future.\nUse LLAMA_CUDA instead")
     set(LLAMA_CUDA ON)
@@ -466,35 +463,6 @@ if (LLAMA_CUDA)
     endif()
 endif()
 
-if (LLAMA_MPI)
-    cmake_minimum_required(VERSION 3.10)
-    find_package(MPI)
-    if (MPI_C_FOUND)
-        message(STATUS "MPI found")
-
-        set(GGML_HEADERS_MPI ggml-mpi.h)
-        set(GGML_SOURCES_MPI ggml-mpi.c)
-
-        add_compile_definitions(GGML_USE_MPI)
-        add_compile_definitions(${MPI_C_COMPILE_DEFINITIONS})
-
-        if (NOT MSVC)
-            add_compile_options(-Wno-cast-qual)
-        endif()
-
-        set(LLAMA_EXTRA_LIBS     ${LLAMA_EXTRA_LIBS}     ${MPI_C_LIBRARIES})
-        set(LLAMA_EXTRA_INCLUDES ${LLAMA_EXTRA_INCLUDES} ${MPI_C_INCLUDE_DIRS})
-
-        # Even if you're only using the C header, C++ programs may bring in MPI
-        # C++ functions, so more linkage is needed
-        if (MPI_CXX_FOUND)
-            set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS}     ${MPI_CXX_LIBRARIES})
-        endif()
-    else()
-        message(WARNING "MPI not found")
-    endif()
-endif()
-
 if (LLAMA_RPC)
     add_compile_definitions(GGML_USE_RPC)
 
@@ -532,6 +500,12 @@ if (LLAMA_VULKAN)
 
         add_compile_definitions(GGML_USE_VULKAN)
 
+        # Workaround to the "can't dereference invalidated vector iterator" bug in clang-cl debug build
+        # Posssibly relevant: https://stackoverflow.com/questions/74748276/visual-studio-no-displays-the-correct-length-of-stdvector
+        if (MSVC AND CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
+            add_compile_definitions(_ITERATOR_DEBUG_LEVEL=0)
+        endif()
+
         if (LLAMA_VULKAN_CHECK_RESULTS)
             add_compile_definitions(GGML_VULKAN_CHECK_RESULTS)
         endif()
@@ -581,7 +555,7 @@ if (LLAMA_HIPBLAS)
     else()
         # Forward AMDGPU_TARGETS to CMAKE_HIP_ARCHITECTURES.
         if(AMDGPU_TARGETS AND NOT CMAKE_HIP_ARCHITECTURES)
-            set(CMAKE_HIP_ARCHITECTURES ${AMDGPU_ARGETS})
+            set(CMAKE_HIP_ARCHITECTURES ${AMDGPU_TARGETS})
         endif()
         cmake_minimum_required(VERSION 3.21)
         enable_language(HIP)
@@ -1090,6 +1064,10 @@ elseif (CMAKE_OSX_ARCHITECTURES STREQUAL "x86_64" OR CMAKE_GENERATOR_PLATFORM_LW
                 add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VNNI__>)
                 add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VNNI__>)
             endif()
+            if (LLAMA_AVX512_BF16)
+                add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512BF16__>)
+                add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512BF16__>)
+            endif()
         elseif (LLAMA_AVX2)
             list(APPEND ARCH_FLAGS /arch:AVX2)
         elseif (LLAMA_AVX)
@@ -1121,6 +1099,9 @@ elseif (CMAKE_OSX_ARCHITECTURES STREQUAL "x86_64" OR CMAKE_GENERATOR_PLATFORM_LW
         if (LLAMA_AVX512_VNNI)
             list(APPEND ARCH_FLAGS -mavx512vnni)
         endif()
+        if (LLAMA_AVX512_BF16)
+            list(APPEND ARCH_FLAGS -mavx512bf16)
+        endif()
     endif()
 elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64")
     message(STATUS "PowerPC detected")
@@ -1130,6 +1111,17 @@ elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64")
         list(APPEND ARCH_FLAGS -mcpu=native -mtune=native)
         #TODO: Add  targets for Power8/Power9 (Altivec/VSX) and Power10(MMA) and query for big endian systems (ppc64/le/be)
     endif()
+elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "loongarch64")
+    message(STATUS "loongarch64 detected")
+
+    list(APPEND ARCH_FLAGS -march=loongarch64)
+    if (LLAMA_LASX)
+        list(APPEND ARCH_FLAGS -mlasx)
+    endif()
+    if (LLAMA_LSX)
+        list(APPEND ARCH_FLAGS -mlsx)
+    endif()
+
 else()
     message(STATUS "Unknown architecture")
 endif()
@@ -1218,7 +1210,6 @@ add_library(ggml OBJECT
             ${GGML_SOURCES_CUDA}      ${GGML_HEADERS_CUDA}
             ${GGML_SOURCES_OPENCL}    ${GGML_HEADERS_OPENCL}
             ${GGML_SOURCES_METAL}     ${GGML_HEADERS_METAL}
-            ${GGML_SOURCES_MPI}       ${GGML_HEADERS_MPI}
             ${GGML_SOURCES_RPC}       ${GGML_HEADERS_RPC}
             ${GGML_SOURCES_EXTRA}     ${GGML_HEADERS_EXTRA}
             ${GGML_SOURCES_SYCL}      ${GGML_HEADERS_SYCL}
@@ -1306,7 +1297,7 @@ install(FILES ${CMAKE_CURRENT_BINARY_DIR}/LlamaConfig.cmake
 
 set(GGML_PUBLIC_HEADERS "ggml.h" "ggml-alloc.h" "ggml-backend.h"
         "${GGML_HEADERS_CUDA}"  "${GGML_HEADERS_OPENCL}"
-        "${GGML_HEADERS_METAL}" "${GGML_HEADERS_MPI}" "${GGML_HEADERS_EXTRA}")
+        "${GGML_HEADERS_METAL}" "${GGML_HEADERS_EXTRA}")
 
 set_target_properties(ggml PROPERTIES PUBLIC_HEADER "${GGML_PUBLIC_HEADERS}")
 install(TARGETS ggml PUBLIC_HEADER)
diff --git a/Makefile b/Makefile
index 22d521856..fe63cbd60 100644
--- a/Makefile
+++ b/Makefile
@@ -379,15 +379,16 @@ ifneq ($(filter ppc64le%,$(UNAME_M)),)
 	CUDA_POWER_ARCH = 1
 endif
 
+ifneq ($(filter loongarch64%,$(UNAME_M)),)
+	MK_CFLAGS   += -mlasx
+	MK_CXXFLAGS += -mlasx
+endif
+
 else
 	MK_CFLAGS   += -march=rv64gcv -mabi=lp64d
 	MK_CXXFLAGS += -march=rv64gcv -mabi=lp64d
 endif
 
-ifdef LLAMA_QKK_64
-	MK_CPPFLAGS += -DGGML_QKK_64
-endif
-
 ifndef LLAMA_NO_ACCELERATE
 	# Mac OS - include Accelerate framework.
 	# `-framework Accelerate` works both with Apple Silicon and Mac Intel
@@ -399,13 +400,6 @@ ifndef LLAMA_NO_ACCELERATE
 	endif
 endif # LLAMA_NO_ACCELERATE
 
-ifdef LLAMA_MPI
-	MK_CPPFLAGS += -DGGML_USE_MPI
-	MK_CFLAGS   += -Wno-cast-qual
-	MK_CXXFLAGS += -Wno-cast-qual
-	OBJS        += ggml-mpi.o
-endif # LLAMA_MPI
-
 ifdef LLAMA_OPENBLAS
 	MK_CPPFLAGS += -DGGML_USE_OPENBLAS $(shell pkg-config --cflags-only-I openblas)
 	MK_CFLAGS   += $(shell pkg-config --cflags-only-other openblas)
@@ -629,11 +623,6 @@ ggml-metal-embed.o: ggml-metal.metal ggml-common.h
 endif
 endif # LLAMA_METAL
 
-ifdef LLAMA_MPI
-ggml-mpi.o: ggml-mpi.c ggml-mpi.h
-	$(CC) $(CFLAGS) -c $< -o $@
-endif # LLAMA_MPI
-
 ifndef LLAMA_NO_LLAMAFILE
 sgemm.o: sgemm.cpp sgemm.h ggml.h
 	$(CXX) $(CXXFLAGS) -c $< -o $@
diff --git a/README.md b/README.md
index 7dd6fc0eb..2ee267fdf 100644
--- a/README.md
+++ b/README.md
@@ -107,7 +107,6 @@ Typically finetunes of the base models below are supported as well.
 - [X] [Aquila 1 & 2](https://huggingface.co/models?search=BAAI/Aquila)
 - [X] [Starcoder models](https://github.com/ggerganov/llama.cpp/pull/3187)
 - [X] [Refact](https://huggingface.co/smallcloudai/Refact-1_6B-fim)
-- [X] [Persimmon 8B](https://github.com/ggerganov/llama.cpp/pull/3410)
 - [X] [MPT](https://github.com/ggerganov/llama.cpp/pull/3417)
 - [X] [Bloom](https://github.com/ggerganov/llama.cpp/pull/3553)
 - [x] [Yi models](https://huggingface.co/models?search=01-ai/Yi)
@@ -128,6 +127,7 @@ Typically finetunes of the base models below are supported as well.
 - [x] [SEA-LION](https://huggingface.co/models?search=sea-lion)
 - [x] [GritLM-7B](https://huggingface.co/GritLM/GritLM-7B) + [GritLM-8x7B](https://huggingface.co/GritLM/GritLM-8x7B)
 - [x] [OLMo](https://allenai.org/olmo)
+- [x] [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) + [Pythia](https://github.com/EleutherAI/pythia)
 
 (instructions for supporting more models: [HOWTO-add-model.md](./docs/HOWTO-add-model.md))
 
@@ -141,6 +141,7 @@ Typically finetunes of the base models below are supported as well.
 - [x] [Yi-VL](https://huggingface.co/models?search=Yi-VL)
 - [x] [Mini CPM](https://huggingface.co/models?search=MiniCPM)
 - [x] [Moondream](https://huggingface.co/vikhyatk/moondream2)
+- [x] [Bunny](https://github.com/BAAI-DCAI/Bunny)
 
 **HTTP server**
 
@@ -301,7 +302,7 @@ cd llama.cpp
 
 ### Build
 
-In order to build llama.cpp you have three different options.
+In order to build llama.cpp you have four different options.
 
 - Using `make`:
   - On Linux or MacOS:
@@ -382,45 +383,6 @@ To disable the Metal build at compile time use the `LLAMA_NO_METAL=1` flag or th
 When built with Metal support, you can explicitly disable GPU inference with the `--n-gpu-layers|-ngl 0` command-line
 argument.
 
-### MPI Build
-
-MPI lets you distribute the computation over a cluster of machines. Because of the serial nature of LLM prediction, this won't yield any end-to-end speed-ups, but it will let you run larger models than would otherwise fit into RAM on a single machine.
-
-First you will need MPI libraries installed on your system. The two most popular (only?) options are [MPICH](https://www.mpich.org) and [OpenMPI](https://www.open-mpi.org). Either can be installed with a package manager (`apt`, Homebrew, MacPorts, etc).
-
-Next you will need to build the project with `LLAMA_MPI` set to true on all machines; if you're building with `make`, you will also need to specify an MPI-capable compiler (when building with CMake, this is configured automatically):
-
-- Using `make`:
-
-  ```bash
-  make CC=mpicc CXX=mpicxx LLAMA_MPI=1
-  ```
-
-- Using `CMake`:
-
-  ```bash
-  cmake -S . -B build -DLLAMA_MPI=ON
-  ```
-
-Once the programs are built, download/convert the weights on all of the machines in your cluster. The paths to the weights and programs should be identical on all machines.
-
-Next, ensure password-less SSH access to each machine from the primary host, and create a `hostfile` with a list of the hostnames and their relative "weights" (slots). If you want to use localhost for computation, use its local subnet IP address rather than the loopback address or "localhost".
-
-Here is an example hostfile:
-
-```
-192.168.0.1:2
-malvolio.local:1
-```
-
-The above will distribute the computation across 2 processes on the first host and 1 process on the second host. Each process will use roughly an equal amount of RAM. Try to keep these numbers small, as inter-process (intra-host) communication is expensive.
-
-Finally, you're ready to run a computation using `mpirun`:
-
-```bash
-mpirun -hostfile hostfile -n 3 ./main -m ./models/7B/ggml-model-q4_0.gguf -n 128
-```
-
 ### BLAS Build
 
 Building the program with BLAS support may lead to some performance improvements in prompt processing using batch sizes higher than 32 (the default is 512). Support with CPU-only BLAS implementations doesn't affect the normal generation performance. We may see generation performance improvements with GPU-involved BLAS implementations, e.g. cuBLAS, hipBLAS and CLBlast. There are currently several different BLAS implementations available for build and use:
diff --git a/build.zig b/build.zig
deleted file mode 100644
index 96783574f..000000000
--- a/build.zig
+++ /dev/null
@@ -1,172 +0,0 @@
-// Compatible with Zig Version 0.11.0
-const std = @import("std");
-const ArrayList = std.ArrayList;
-const Compile = std.Build.Step.Compile;
-const ConfigHeader = std.Build.Step.ConfigHeader;
-const Mode = std.builtin.Mode;
-const CrossTarget = std.zig.CrossTarget;
-
-const Maker = struct {
-    builder: *std.build.Builder,
-    target: CrossTarget,
-    optimize: Mode,
-    enable_lto: bool,
-
-    include_dirs: ArrayList([]const u8),
-    cflags: ArrayList([]const u8),
-    cxxflags: ArrayList([]const u8),
-    objs: ArrayList(*Compile),
-
-    fn addInclude(m: *Maker, dir: []const u8) !void {
-        try m.include_dirs.append(dir);
-    }
-    fn addProjectInclude(m: *Maker, path: []const []const u8) !void {
-        try m.addInclude(try m.builder.build_root.join(m.builder.allocator, path));
-    }
-    fn addCFlag(m: *Maker, flag: []const u8) !void {
-        try m.cflags.append(flag);
-    }
-    fn addCxxFlag(m: *Maker, flag: []const u8) !void {
-        try m.cxxflags.append(flag);
-    }
-    fn addFlag(m: *Maker, flag: []const u8) !void {
-        try m.addCFlag(flag);
-        try m.addCxxFlag(flag);
-    }
-
-    fn init(builder: *std.build.Builder) !Maker {
-        const target = builder.standardTargetOptions(.{});
-        const zig_version = @import("builtin").zig_version_string;
-        const commit_hash = try std.ChildProcess.exec(
-            .{ .allocator = builder.allocator, .argv = &.{ "git", "rev-parse", "HEAD" } },
-        );
-        try std.fs.cwd().writeFile("common/build-info.cpp", builder.fmt(
-            \\int LLAMA_BUILD_NUMBER = {};
-            \\char const *LLAMA_COMMIT = "{s}";
-            \\char const *LLAMA_COMPILER = "Zig {s}";
-            \\char const *LLAMA_BUILD_TARGET = "{s}";
-            \\
-        , .{ 0, commit_hash.stdout[0 .. commit_hash.stdout.len - 1], zig_version, try target.allocDescription(builder.allocator) }));
-        var m = Maker{
-            .builder = builder,
-            .target = target,
-            .optimize = builder.standardOptimizeOption(.{}),
-            .enable_lto = false,
-            .include_dirs = ArrayList([]const u8).init(builder.allocator),
-            .cflags = ArrayList([]const u8).init(builder.allocator),
-            .cxxflags = ArrayList([]const u8).init(builder.allocator),
-            .objs = ArrayList(*Compile).init(builder.allocator),
-        };
-
-        try m.addCFlag("-std=c11");
-        try m.addCxxFlag("-std=c++11");
-        try m.addProjectInclude(&.{});
-        try m.addProjectInclude(&.{"common"});
-        return m;
-    }
-
-    fn obj(m: *const Maker, name: []const u8, src: []const u8) *Compile {
-        const o = m.builder.addObject(.{ .name = name, .target = m.target, .optimize = m.optimize });
-        if (o.target.getAbi() != .msvc)
-            o.defineCMacro("_GNU_SOURCE", null);
-
-        if (std.mem.endsWith(u8, src, ".c")) {
-            o.addCSourceFiles(&.{src}, m.cflags.items);
-            o.linkLibC();
-        } else {
-            o.addCSourceFiles(&.{src}, m.cxxflags.items);
-            if (o.target.getAbi() == .msvc) {
-                o.linkLibC(); // need winsdk + crt
-            } else {
-                // linkLibCpp already add (libc++ + libunwind + libc)
-                o.linkLibCpp();
-            }
-        }
-        for (m.include_dirs.items) |i| o.addIncludePath(.{ .path = i });
-        o.want_lto = m.enable_lto;
-        return o;
-    }
-
-    fn exe(m: *const Maker, name: []const u8, src: []const u8, deps: []const *Compile) *Compile {
-        const e = m.builder.addExecutable(.{ .name = name, .target = m.target, .optimize = m.optimize });
-        e.addCSourceFiles(&.{src}, m.cxxflags.items);
-        for (deps) |d| e.addObject(d);
-        for (m.objs.items) |o| e.addObject(o);
-        for (m.include_dirs.items) |i| e.addIncludePath(.{ .path = i });
-
-        // https://github.com/ziglang/zig/issues/15448
-        if (e.target.getAbi() == .msvc) {
-            e.linkLibC(); // need winsdk + crt
-        } else {
-            // linkLibCpp already add (libc++ + libunwind + libc)
-            e.linkLibCpp();
-        }
-        m.builder.installArtifact(e);
-        e.want_lto = m.enable_lto;
-        return e;
-    }
-};
-
-pub fn build(b: *std.build.Builder) !void {
-    var make = try Maker.init(b);
-    make.enable_lto = b.option(bool, "lto", "Enable LTO optimization, (default: false)") orelse false;
-
-    const ggml = make.obj("ggml", "ggml.c");
-    const sgemm = make.obj("sgemm", "sgemm.cpp");
-    const ggml_alloc = make.obj("ggml-alloc", "ggml-alloc.c");
-    const ggml_backend = make.obj("ggml-backend", "ggml-backend.c");
-    const ggml_quants = make.obj("ggml-quants", "ggml-quants.c");
-    const unicode = make.obj("unicode", "unicode.cpp");
-    const unicode_data = make.obj("unicode-data", "unicode-data.cpp");
-    const llama = make.obj("llama", "llama.cpp");
-    const buildinfo = make.obj("common", "common/build-info.cpp");
-    const common = make.obj("common", "common/common.cpp");
-    const console = make.obj("console", "common/console.cpp");
-    const sampling = make.obj("sampling", "common/sampling.cpp");
-    const grammar_parser = make.obj("grammar-parser", "common/grammar-parser.cpp");
-    const json_schema_to_grammar = make.obj("json-schema-to-grammar", "common/json-schema-to-grammar.cpp");
-    const train = make.obj("train", "common/train.cpp");
-    const clip = make.obj("clip", "examples/llava/clip.cpp");
-    const llava = make.obj("llava", "examples/llava/llava.cpp");
-
-    _ = make.exe("main", "examples/main/main.cpp", &.{ ggml, sgemm, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, json_schema_to_grammar, buildinfo, sampling, console, grammar_parser });
-    _ = make.exe("quantize", "examples/quantize/quantize.cpp", &.{ ggml, sgemm, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, json_schema_to_grammar, buildinfo });
-    _ = make.exe("perplexity", "examples/perplexity/perplexity.cpp", &.{ ggml, sgemm, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, json_schema_to_grammar, buildinfo });
-    _ = make.exe("embedding", "examples/embedding/embedding.cpp", &.{ ggml, sgemm, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, json_schema_to_grammar, buildinfo });
-    _ = make.exe("finetune", "examples/finetune/finetune.cpp", &.{ ggml, sgemm, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, json_schema_to_grammar, buildinfo, train });
-    _ = make.exe("train-text-from-scratch", "examples/train-text-from-scratch/train-text-from-scratch.cpp", &.{ ggml, sgemm, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, json_schema_to_grammar, buildinfo, train });
-
-    const server = make.exe("server", "examples/server/server.cpp", &.{ ggml, sgemm, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, json_schema_to_grammar, buildinfo, sampling, grammar_parser, clip, llava });
-    if (server.target.isWindows()) {
-        server.linkSystemLibrary("ws2_32");
-    }
-
-    const server_assets = [_][]const u8{ "index.html", "index.js", "completion.js", "json-schema-to-grammar.mjs" };
-    for (server_assets) |asset| {
-        const input_path = b.fmt("examples/server/public/{s}", .{asset});
-        const output_path = b.fmt("examples/server/{s}.hpp", .{asset});
-
-        // Portable equivalent of `b.addSystemCommand(&.{ "xxd", "-n", asset, "-i", input_path, output_path }) })`:
-
-        const input = try std.fs.cwd().readFileAlloc(b.allocator, input_path, std.math.maxInt(usize));
-        defer b.allocator.free(input);
-
-        var buf = std.ArrayList(u8).init(b.allocator);
-        defer buf.deinit();
-
-        for (input) |byte| {
-            try std.fmt.format(buf.writer(), "0x{X:0>2}, ", .{byte});
-        }
-
-        var name = try std.mem.replaceOwned(u8, b.allocator, asset, "-", "_");
-        defer b.allocator.free(name);
-        std.mem.replaceScalar(u8, name, '.', '_');
-
-        try std.fs.cwd().writeFile(output_path, b.fmt(
-            "unsigned char {s}[] = {{{s}}};\nunsigned int {s}_len = {d};\n",
-            .{ name, buf.items, name, input.len },
-        ));
-
-        std.debug.print("Dumped hex of \"{s}\" ({s}) to {s}\n", .{ input_path, name, output_path });
-    }
-}
diff --git a/ci/run.sh b/ci/run.sh
index d5972480b..940299025 100755
--- a/ci/run.sh
+++ b/ci/run.sh
@@ -202,12 +202,15 @@ function gg_sum_test_scripts_release {
 }
 
 function gg_get_model {
-    local gguf_3b="$MNT/models/open-llama/3B-v2/ggml-model-f16.gguf"
-    local gguf_7b="$MNT/models/open-llama/7B-v2/ggml-model-f16.gguf"
-    if [[ -s $gguf_3b ]]; then
-        echo -n "$gguf_3b"
-    elif [[ -s $gguf_7b ]]; then
-        echo -n "$gguf_7b"
+    local gguf_0="$MNT/models/pythia/1.4B/ggml-model-f16.gguf"
+    local gguf_1="$MNT/models/pythia/2.8B/ggml-model-f16.gguf"
+    local gguf_2="$MNT/models/open-llama/7B-v2/ggml-model-f16.gguf"
+    if [[ -s $gguf_0 ]]; then
+        echo -n "$gguf_0"
+    elif [[ -s $gguf_1 ]]; then
+        echo -n "$gguf_1"
+    elif [[ -s $gguf_2 ]]; then
+        echo -n "$gguf_2"
     else
         echo >&2 "No model found. Can't run gg_run_ctest_with_model."
         exit 1
@@ -256,139 +259,6 @@ function gg_sum_ctest_with_model_release {
     gg_printf '```\n'
 }
 
-# open_llama_3b_v2
-
-function gg_run_open_llama_3b_v2 {
-    cd ${SRC}
-
-    gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/config.json
-    gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/resolve/main/tokenizer.model
-    gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/tokenizer_config.json
-    gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/special_tokens_map.json
-    gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/resolve/main/pytorch_model.bin
-    gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/generation_config.json
-
-    gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
-    unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
-    head -n 60 models-mnt/wikitext/wikitext-2-raw/wiki.test.raw > models-mnt/wikitext/wikitext-2-raw/wiki.test-60.raw
-
-    path_models="../models-mnt/open-llama/3B-v2"
-    path_wiki="../models-mnt/wikitext/wikitext-2-raw"
-
-    rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
-
-    set -e
-
-    (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_QKK_64=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
-    (time make -j                                                             ) 2>&1 | tee -a $OUT/${ci}-make.log
-
-    python3 ../convert.py ${path_models}
-
-    model_f16="${path_models}/ggml-model-f16.gguf"
-    model_q8_0="${path_models}/ggml-model-q8_0.gguf"
-    model_q4_0="${path_models}/ggml-model-q4_0.gguf"
-    model_q4_1="${path_models}/ggml-model-q4_1.gguf"
-    model_q5_0="${path_models}/ggml-model-q5_0.gguf"
-    model_q5_1="${path_models}/ggml-model-q5_1.gguf"
-    model_q2_k="${path_models}/ggml-model-q2_k.gguf"
-    model_q3_k="${path_models}/ggml-model-q3_k.gguf"
-    model_q4_k="${path_models}/ggml-model-q4_k.gguf"
-    model_q5_k="${path_models}/ggml-model-q5_k.gguf"
-    model_q6_k="${path_models}/ggml-model-q6_k.gguf"
-
-    wiki_test_60="${path_wiki}/wiki.test-60.raw"
-
-    ./bin/quantize ${model_f16} ${model_q8_0} q8_0
-    ./bin/quantize ${model_f16} ${model_q4_0} q4_0
-    ./bin/quantize ${model_f16} ${model_q4_1} q4_1
-    ./bin/quantize ${model_f16} ${model_q5_0} q5_0
-    ./bin/quantize ${model_f16} ${model_q5_1} q5_1
-    ./bin/quantize ${model_f16} ${model_q2_k} q2_k
-    ./bin/quantize ${model_f16} ${model_q3_k} q3_k
-    ./bin/quantize ${model_f16} ${model_q4_k} q4_k
-    ./bin/quantize ${model_f16} ${model_q5_k} q5_k
-    ./bin/quantize ${model_f16} ${model_q6_k} q6_k
-
-    (time ./bin/main --model ${model_f16}  -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
-    (time ./bin/main --model ${model_q8_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
-    (time ./bin/main --model ${model_q4_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
-    (time ./bin/main --model ${model_q4_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
-    (time ./bin/main --model ${model_q5_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
-    (time ./bin/main --model ${model_q5_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
-    (time ./bin/main --model ${model_q2_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
-    (time ./bin/main --model ${model_q3_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
-    (time ./bin/main --model ${model_q4_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
-    (time ./bin/main --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
-    (time ./bin/main --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
-
-    (time ./bin/perplexity --model ${model_f16}  -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
-    (time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
-    (time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
-    (time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
-    (time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
-    (time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
-    (time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
-    (time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
-    (time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
-    (time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
-    (time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
-
-    (time ./bin/imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
-
-    (time ./bin/save-load-state     --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
-    (time ./bin/save-load-state -fa --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
-
-    function check_ppl {
-        qnt="$1"
-        ppl=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
-
-        if [ $(echo "$ppl > 20.0" | bc) -eq 1 ]; then
-            printf '  - %s @ %s (FAIL: ppl > 20.0)\n' "$qnt" "$ppl"
-            return 20
-        fi
-
-        printf '  - %s @ %s OK\n' "$qnt" "$ppl"
-        return 0
-    }
-
-    check_ppl "f16"  "$(cat $OUT/${ci}-tg-f16.log  | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-    check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
-
-    cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
-
-    set +e
-}
-
-function gg_sum_open_llama_3b_v2 {
-    gg_printf '### %s\n\n' "${ci}"
-
-    gg_printf 'OpenLLaMA 3B-v2:\n'
-    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
-    gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
-    gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
-    gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
-    gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
-    gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
-    gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
-    gg_printf '- q5_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_0.log)"
-    gg_printf '- q5_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_1.log)"
-    gg_printf '- q2_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q2_k.log)"
-    gg_printf '- q3_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q3_k.log)"
-    gg_printf '- q4_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_k.log)"
-    gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
-    gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
-    gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
-}
-
 # open_llama_7b_v2
 # requires: GG_BUILD_CUDA
 
@@ -417,7 +287,7 @@ function gg_run_open_llama_7b_v2 {
     (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                                           ) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    python3 ../convert.py ${path_models}
+    python3 ../convert.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
 
     model_f16="${path_models}/ggml-model-f16.gguf"
     model_q8_0="${path_models}/ggml-model-q8_0.gguf"
@@ -526,6 +396,272 @@ function gg_sum_open_llama_7b_v2 {
     gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
 }
 
+# pythia_1.4b
+
+function gg_run_pythia_1_4b {
+    cd ${SRC}
+
+    gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/config.json
+    gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/tokenizer.json
+    gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/tokenizer_config.json
+    gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/special_tokens_map.json
+    gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/resolve/main/pytorch_model.bin
+
+    gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
+    unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
+    head -n 60 models-mnt/wikitext/wikitext-2-raw/wiki.test.raw > models-mnt/wikitext/wikitext-2-raw/wiki.test-60.raw
+
+    path_models="../models-mnt/pythia/1.4B"
+    path_wiki="../models-mnt/wikitext/wikitext-2-raw"
+
+    rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
+
+    set -e
+
+    (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
+    (time make -j                                            ) 2>&1 | tee -a $OUT/${ci}-make.log
+
+    python3 ../convert-hf-to-gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
+
+    model_f16="${path_models}/ggml-model-f16.gguf"
+    model_q8_0="${path_models}/ggml-model-q8_0.gguf"
+    model_q4_0="${path_models}/ggml-model-q4_0.gguf"
+    model_q4_1="${path_models}/ggml-model-q4_1.gguf"
+    model_q5_0="${path_models}/ggml-model-q5_0.gguf"
+    model_q5_1="${path_models}/ggml-model-q5_1.gguf"
+    model_q2_k="${path_models}/ggml-model-q2_k.gguf"
+    model_q3_k="${path_models}/ggml-model-q3_k.gguf"
+    model_q4_k="${path_models}/ggml-model-q4_k.gguf"
+    model_q5_k="${path_models}/ggml-model-q5_k.gguf"
+    model_q6_k="${path_models}/ggml-model-q6_k.gguf"
+
+    wiki_test_60="${path_wiki}/wiki.test-60.raw"
+
+    ./bin/quantize ${model_f16} ${model_q8_0} q8_0
+    ./bin/quantize ${model_f16} ${model_q4_0} q4_0
+    ./bin/quantize ${model_f16} ${model_q4_1} q4_1
+    ./bin/quantize ${model_f16} ${model_q5_0} q5_0
+    ./bin/quantize ${model_f16} ${model_q5_1} q5_1
+    ./bin/quantize ${model_f16} ${model_q2_k} q2_k
+    ./bin/quantize ${model_f16} ${model_q3_k} q3_k
+    ./bin/quantize ${model_f16} ${model_q4_k} q4_k
+    ./bin/quantize ${model_f16} ${model_q5_k} q5_k
+    ./bin/quantize ${model_f16} ${model_q6_k} q6_k
+
+    (time ./bin/main --model ${model_f16}  -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
+    (time ./bin/main --model ${model_q8_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
+    (time ./bin/main --model ${model_q4_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
+    (time ./bin/main --model ${model_q4_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
+    (time ./bin/main --model ${model_q5_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
+    (time ./bin/main --model ${model_q5_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
+    (time ./bin/main --model ${model_q2_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
+    (time ./bin/main --model ${model_q3_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
+    (time ./bin/main --model ${model_q4_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
+    (time ./bin/main --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
+    (time ./bin/main --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
+
+    (time ./bin/perplexity --model ${model_f16}  -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
+    (time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
+    (time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
+    (time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
+    (time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
+    (time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
+    (time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
+    (time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
+    (time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
+    (time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
+    (time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
+
+    (time ./bin/imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
+
+    (time ./bin/save-load-state     --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/save-load-state -fa --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+
+    function check_ppl {
+        qnt="$1"
+        ppl=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
+
+        if [ $(echo "$ppl > 20.0" | bc) -eq 1 ]; then
+            printf '  - %s @ %s (FAIL: ppl > 20.0)\n' "$qnt" "$ppl"
+            return 20
+        fi
+
+        printf '  - %s @ %s OK\n' "$qnt" "$ppl"
+        return 0
+    }
+
+    check_ppl "f16"  "$(cat $OUT/${ci}-tg-f16.log  | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+   #check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log # note: ppl > 20.0 for this quant and model
+    check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+
+    cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
+
+    set +e
+}
+
+function gg_sum_pythia_1_4b {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Pythia 1.4B:\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
+    gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
+    gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
+    gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
+    gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
+    gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
+    gg_printf '- q5_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_0.log)"
+    gg_printf '- q5_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_1.log)"
+    gg_printf '- q2_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q2_k.log)"
+    gg_printf '- q3_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q3_k.log)"
+    gg_printf '- q4_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_k.log)"
+    gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
+    gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
+    gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
+}
+
+# pythia_2_8b
+# requires: GG_BUILD_CUDA
+
+function gg_run_pythia_2_8b {
+    cd ${SRC}
+
+    gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/config.json
+    gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/tokenizer.json
+    gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/tokenizer_config.json
+    gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/special_tokens_map.json
+    gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/resolve/main/pytorch_model.bin
+
+    gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
+    unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
+
+    path_models="../models-mnt/pythia/2.8B"
+    path_wiki="../models-mnt/wikitext/wikitext-2-raw"
+
+    rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
+
+    set -e
+
+    (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
+    (time make -j                                                           ) 2>&1 | tee -a $OUT/${ci}-make.log
+
+    python3 ../convert-hf-to-gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
+
+    model_f16="${path_models}/ggml-model-f16.gguf"
+    model_q8_0="${path_models}/ggml-model-q8_0.gguf"
+    model_q4_0="${path_models}/ggml-model-q4_0.gguf"
+    model_q4_1="${path_models}/ggml-model-q4_1.gguf"
+    model_q5_0="${path_models}/ggml-model-q5_0.gguf"
+    model_q5_1="${path_models}/ggml-model-q5_1.gguf"
+    model_q2_k="${path_models}/ggml-model-q2_k.gguf"
+    model_q3_k="${path_models}/ggml-model-q3_k.gguf"
+    model_q4_k="${path_models}/ggml-model-q4_k.gguf"
+    model_q5_k="${path_models}/ggml-model-q5_k.gguf"
+    model_q6_k="${path_models}/ggml-model-q6_k.gguf"
+
+    wiki_test="${path_wiki}/wiki.test.raw"
+
+    ./bin/quantize ${model_f16} ${model_q8_0} q8_0
+    ./bin/quantize ${model_f16} ${model_q4_0} q4_0
+    ./bin/quantize ${model_f16} ${model_q4_1} q4_1
+    ./bin/quantize ${model_f16} ${model_q5_0} q5_0
+    ./bin/quantize ${model_f16} ${model_q5_1} q5_1
+    ./bin/quantize ${model_f16} ${model_q2_k} q2_k
+    ./bin/quantize ${model_f16} ${model_q3_k} q3_k
+    ./bin/quantize ${model_f16} ${model_q4_k} q4_k
+    ./bin/quantize ${model_f16} ${model_q5_k} q5_k
+    ./bin/quantize ${model_f16} ${model_q6_k} q6_k
+
+    (time ./bin/main --model ${model_f16}  -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
+    (time ./bin/main --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
+    (time ./bin/main --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
+    (time ./bin/main --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
+    (time ./bin/main --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
+    (time ./bin/main --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
+    (time ./bin/main --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
+    (time ./bin/main --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
+    (time ./bin/main --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
+    (time ./bin/main --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
+    (time ./bin/main --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
+
+    (time ./bin/perplexity --model ${model_f16}  -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
+    (time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
+    (time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
+    (time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
+    (time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
+    (time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
+    (time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
+    (time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
+    (time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
+    (time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
+    (time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
+
+    (time ./bin/imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
+
+    (time ./bin/save-load-state     -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/save-load-state -fa -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/save-load-state     -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+    (time ./bin/save-load-state -fa -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
+
+    function check_ppl {
+        qnt="$1"
+        ppl=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
+
+        if [ $(echo "$ppl > 20.0" | bc) -eq 1 ]; then
+            printf '  - %s @ %s (FAIL: ppl > 20.0)\n' "$qnt" "$ppl"
+            return 20
+        fi
+
+        printf '  - %s @ %s OK\n' "$qnt" "$ppl"
+        return 0
+    }
+
+    check_ppl "f16"  "$(cat $OUT/${ci}-tg-f16.log  | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+   #check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log # note: ppl > 20.0 for this quant and model
+    check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+
+    cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
+
+    set +e
+}
+
+function gg_sum_pythia_2_8b {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Pythia 2.8B:\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
+    gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
+    gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
+    gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
+    gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
+    gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
+    gg_printf '- q5_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_0.log)"
+    gg_printf '- q5_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_1.log)"
+    gg_printf '- q2_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q2_k.log)"
+    gg_printf '- q3_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q3_k.log)"
+    gg_printf '- q4_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_k.log)"
+    gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
+    gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
+    gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
+}
+
 # bge-small
 
 function gg_run_embd_bge_small {
@@ -552,7 +688,7 @@ function gg_run_embd_bge_small {
     (time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time make -j                                            ) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    python3 ../convert-hf-to-gguf.py ${path_models}
+    python3 ../convert-hf-to-gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
 
     model_f16="${path_models}/ggml-model-f16.gguf"
     model_q8_0="${path_models}/ggml-model-q8_0.gguf"
@@ -606,9 +742,10 @@ if [ -z ${GG_BUILD_LOW_PERF} ]; then
 
     if [ -z ${GG_BUILD_VRAM_GB} ] || [ ${GG_BUILD_VRAM_GB} -ge 8 ]; then
         if [ -z ${GG_BUILD_CUDA} ]; then
-            test $ret -eq 0 && gg_run open_llama_3b_v2
+            test $ret -eq 0 && gg_run pythia_1_4b
         else
-            test $ret -eq 0 && gg_run open_llama_7b_v2
+            test $ret -eq 0 && gg_run pythia_2_8b
+            #test $ret -eq 0 && gg_run open_llama_7b_v2
         fi
         test $ret -eq 0 && gg_run ctest_with_model_debug
         test $ret -eq 0 && gg_run ctest_with_model_release
diff --git a/common/common.cpp b/common/common.cpp
index e624fc7f3..7500e08ff 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -73,7 +73,11 @@
 
 using json = nlohmann::ordered_json;
 
-int32_t get_num_physical_cores() {
+//
+// CPU utils
+//
+
+int32_t cpu_get_num_physical_cores() {
 #ifdef __linux__
     // enumerate the set of thread siblings, num entries is num cores
     std::unordered_set<std::string> siblings;
@@ -142,9 +146,9 @@ static bool is_running_on_efficiency_core(void) {
     return core_type == intel_atom;
 }
 
-static int count_math_cpus(int cpu_count) {
+static int cpu_count_math_cpus(int n_cpu) {
     int result = 0;
-    for (int cpu = 0; cpu < cpu_count; ++cpu) {
+    for (int cpu = 0; cpu < n_cpu; ++cpu) {
         if (pin_cpu(cpu)) {
             return -1;
         }
@@ -162,16 +166,16 @@ static int count_math_cpus(int cpu_count) {
 /**
  * Returns number of CPUs on system that are useful for math.
  */
-int get_math_cpu_count() {
+int32_t cpu_get_num_math() {
 #if defined(__x86_64__) && defined(__linux__) && !defined(__ANDROID__)
-    int cpu_count = sysconf(_SC_NPROCESSORS_ONLN);
-    if (cpu_count < 1) {
-        return get_num_physical_cores();
+    int n_cpu = sysconf(_SC_NPROCESSORS_ONLN);
+    if (n_cpu < 1) {
+        return cpu_get_num_physical_cores();
     }
     if (is_hybrid_cpu()) {
         cpu_set_t affinity;
         if (!pthread_getaffinity_np(pthread_self(), sizeof(affinity), &affinity)) {
-            int result = count_math_cpus(cpu_count);
+            int result = cpu_count_math_cpus(n_cpu);
             pthread_setaffinity_np(pthread_self(), sizeof(affinity), &affinity);
             if (result > 0) {
                 return result;
@@ -179,108 +183,103 @@ int get_math_cpu_count() {
         }
     }
 #endif
-    return get_num_physical_cores();
+    return cpu_get_num_physical_cores();
 }
 
-void process_escapes(std::string & input) {
-    std::size_t input_len = input.length();
-    std::size_t output_idx = 0;
+//
+// CLI argument parsing
+//
 
-    for (std::size_t input_idx = 0; input_idx < input_len; ++input_idx) {
-        if (input[input_idx] == '\\' && input_idx + 1 < input_len) {
-            switch (input[++input_idx]) {
-                case 'n':  input[output_idx++] = '\n'; break;
-                case 'r':  input[output_idx++] = '\r'; break;
-                case 't':  input[output_idx++] = '\t'; break;
-                case '\'': input[output_idx++] = '\''; break;
-                case '\"': input[output_idx++] = '\"'; break;
-                case '\\': input[output_idx++] = '\\'; break;
-                case 'x':
-                    // Handle \x12, etc
-                    if (input_idx + 2 < input_len) {
-                        const char x[3] = { input[input_idx + 1], input[input_idx + 2], 0 };
-                        char *err_p = nullptr;
-                        const long val = std::strtol(x, &err_p, 16);
-                        if (err_p == x + 2) {
-                            input_idx += 2;
-                            input[output_idx++] = char(val);
-                            break;
-                        }
-                    }
-                    // fall through
-                default:   input[output_idx++] = '\\';
-                           input[output_idx++] = input[input_idx]; break;
+void gpt_params_handle_model_default(gpt_params & params) {
+    if (!params.hf_repo.empty()) {
+        // short-hand to avoid specifying --hf-file -> default it to --model
+        if (params.hf_file.empty()) {
+            if (params.model.empty()) {
+                throw std::invalid_argument("error: --hf-repo requires either --hf-file or --model\n");
             }
-        } else {
-            input[output_idx++] = input[input_idx];
+            params.hf_file = params.model;
+        } else if (params.model.empty()) {
+            std::string cache_directory = fs_get_cache_directory();
+            const bool success = fs_create_directory_with_parents(cache_directory);
+            if (!success) {
+                throw std::runtime_error("failed to create cache directory: " + cache_directory);
+            }
+            params.model = cache_directory + string_split(params.hf_file, '/').back();
+        }
+    } else if (!params.model_url.empty()) {
+        if (params.model.empty()) {
+            auto f = string_split(params.model_url, '#').front();
+            f = string_split(f, '?').front();
+            f = string_split(f, '/').back();
+            params.model =  "models/" + f;
+        }
+    } else if (params.model.empty()) {
+        params.model = DEFAULT_MODEL_PATH;
+    }
+}
+
+bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
+    bool invalid_param = false;
+    std::string arg;
+    const std::string arg_prefix = "--";
+    llama_sampling_params & sparams = params.sparams;
+
+    for (int i = 1; i < argc; i++) {
+        arg = argv[i];
+        if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) {
+            std::replace(arg.begin(), arg.end(), '_', '-');
+        }
+        if (!gpt_params_find_arg(argc, argv, arg, params, i, invalid_param)) {
+            throw std::invalid_argument("error: unknown argument: " + arg);
+        }
+        if (invalid_param) {
+            throw std::invalid_argument("error: invalid parameter for argument: " + arg);
         }
     }
 
-    input.resize(output_idx);
+    if (params.prompt_cache_all &&
+            (params.interactive || params.interactive_first ||
+             params.instruct)) {
+
+        throw std::invalid_argument("error: --prompt-cache-all not supported in interactive mode yet\n");
+    }
+
+    gpt_params_handle_model_default(params);
+
+    if (params.escape) {
+        string_process_escapes(params.prompt);
+        string_process_escapes(params.input_prefix);
+        string_process_escapes(params.input_suffix);
+        string_process_escapes(sparams.cfg_negative_prompt);
+        for (auto & antiprompt : params.antiprompt) {
+            string_process_escapes(antiprompt);
+        }
+    }
+
+    if (!params.kv_overrides.empty()) {
+        params.kv_overrides.emplace_back();
+        params.kv_overrides.back().key[0] = 0;
+    }
+
+    return true;
 }
 
 bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
     bool result = true;
     try {
         if (!gpt_params_parse_ex(argc, argv, params)) {
-            gpt_print_usage(argc, argv, gpt_params());
+            gpt_params_print_usage(argc, argv, gpt_params());
             exit(0);
         }
     }
     catch (const std::invalid_argument & ex) {
         fprintf(stderr, "%s\n", ex.what());
-        gpt_print_usage(argc, argv, gpt_params());
+        gpt_params_print_usage(argc, argv, gpt_params());
         exit(1);
     }
     return result;
 }
 
-bool parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides) {
-    const char * sep = strchr(data, '=');
-    if (sep == nullptr || sep - data >= 128) {
-        fprintf(stderr, "%s: malformed KV override '%s'\n", __func__, data);
-        return false;
-    }
-    llama_model_kv_override kvo;
-    std::strncpy(kvo.key, data, sep - data);
-    kvo.key[sep - data] = 0;
-    sep++;
-    if (strncmp(sep, "int:", 4) == 0) {
-        sep += 4;
-        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT;
-        kvo.val_i64 = std::atol(sep);
-    } else if (strncmp(sep, "float:", 6) == 0) {
-        sep += 6;
-        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT;
-        kvo.val_f64 = std::atof(sep);
-    } else if (strncmp(sep, "bool:", 5) == 0) {
-        sep += 5;
-        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL;
-        if (std::strcmp(sep, "true") == 0) {
-            kvo.val_bool = true;
-        } else if (std::strcmp(sep, "false") == 0) {
-            kvo.val_bool = false;
-        } else {
-            fprintf(stderr, "%s: invalid boolean value for KV override '%s'\n", __func__, data);
-            return false;
-        }
-    } else if (strncmp(sep, "str:", 4) == 0) {
-        sep += 4;
-        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_STR;
-        if (strlen(sep) > 127) {
-            fprintf(stderr, "%s: malformed KV override '%s', value cannot exceed 127 chars\n", __func__, data);
-            return false;
-        }
-        strncpy(kvo.val_str, sep, 127);
-        kvo.val_str[127] = '\0';
-    } else {
-        fprintf(stderr, "%s: invalid type for KV override '%s'\n", __func__, data);
-        return false;
-    }
-    overrides.emplace_back(std::move(kvo));
-    return true;
-}
-
 bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_params & params, int & i, bool & invalid_param) {
     llama_sampling_params & sparams = params.sparams;
 
@@ -546,7 +545,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
             return true;
         }
         const auto sampler_names = string_split(argv[i], ';');
-        sparams.samplers_sequence = sampler_types_from_names(sampler_names, true);
+        sparams.samplers_sequence = llama_sampling_types_from_names(sampler_names, true);
         return true;
     }
     if (arg == "--sampling-seq") {
@@ -554,7 +553,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
             invalid_param = true;
             return true;
         }
-        sparams.samplers_sequence = sampler_types_from_chars(argv[i]);
+        sparams.samplers_sequence = llama_sampling_types_from_chars(argv[i]);
         return true;
     }
     if (arg == "--top-p") {
@@ -1240,7 +1239,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
         return true;
     }
     if (arg == "-h" || arg == "--help") {
-        gpt_print_usage(argc, argv, gpt_params());
+        gpt_params_print_usage(argc, argv, gpt_params());
         exit(0);
     }
     if (arg == "--version") {
@@ -1311,7 +1310,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
             invalid_param = true;
             return true;
         }
-        if (!parse_kv_override(argv[i], params.kv_overrides)) {
+        if (!string_parse_kv_override(argv[i], params.kv_overrides)) {
             fprintf(stderr, "error: Invalid type for KV override: %s\n", argv[i]);
             invalid_param = true;
             return true;
@@ -1345,83 +1344,14 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
     return false;
 }
 
-void gpt_params_handle_model_default(gpt_params & params) {
-    if (!params.hf_repo.empty()) {
-        // short-hand to avoid specifying --hf-file -> default it to --model
-        if (params.hf_file.empty()) {
-            if (params.model.empty()) {
-                throw std::invalid_argument("error: --hf-repo requires either --hf-file or --model\n");
-            }
-            params.hf_file = params.model;
-        } else if (params.model.empty()) {
-            params.model = "models/" + string_split(params.hf_file, '/').back();
-        }
-    } else if (!params.model_url.empty()) {
-        if (params.model.empty()) {
-            auto f = string_split(params.model_url, '#').front();
-            f = string_split(f, '?').front();
-            f = string_split(f, '/').back();
-            params.model =  "models/" + f;
-        }
-    } else if (params.model.empty()) {
-        params.model = DEFAULT_MODEL_PATH;
-    }
-}
-
-bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
-    bool invalid_param = false;
-    std::string arg;
-    const std::string arg_prefix = "--";
-    llama_sampling_params & sparams = params.sparams;
-
-    for (int i = 1; i < argc; i++) {
-        arg = argv[i];
-        if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) {
-            std::replace(arg.begin(), arg.end(), '_', '-');
-        }
-        if (!gpt_params_find_arg(argc, argv, arg, params, i, invalid_param)) {
-            throw std::invalid_argument("error: unknown argument: " + arg);
-        }
-        if (invalid_param) {
-            throw std::invalid_argument("error: invalid parameter for argument: " + arg);
-        }
-    }
-
-    if (params.prompt_cache_all &&
-            (params.interactive || params.interactive_first ||
-             params.instruct)) {
-
-        throw std::invalid_argument("error: --prompt-cache-all not supported in interactive mode yet\n");
-    }
-
-    gpt_params_handle_model_default(params);
-
-    if (params.escape) {
-        process_escapes(params.prompt);
-        process_escapes(params.input_prefix);
-        process_escapes(params.input_suffix);
-        process_escapes(sparams.cfg_negative_prompt);
-        for (auto & antiprompt : params.antiprompt) {
-            process_escapes(antiprompt);
-        }
-    }
-
-    if (!params.kv_overrides.empty()) {
-        params.kv_overrides.emplace_back();
-        params.kv_overrides.back().key[0] = 0;
-    }
-
-    return true;
-}
-
-void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
+void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
     const llama_sampling_params & sparams = params.sparams;
 
     std::string sampler_type_chars;
     std::string sampler_type_names;
     for (const auto sampler_type : sparams.samplers_sequence) {
         sampler_type_chars += static_cast<char>(sampler_type);
-        sampler_type_names += sampler_type_to_name_string(sampler_type) + ";";
+        sampler_type_names += llama_sampling_type_to_str(sampler_type) + ";";
     }
     sampler_type_names.pop_back();
 
@@ -1618,7 +1548,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
 #endif // LOG_DISABLE_LOGS
 }
 
-std::string get_system_info(const gpt_params & params) {
+std::string gpt_params_get_system_info(const gpt_params & params) {
     std::ostringstream os;
 
     os << "system_info: n_threads = " << params.n_threads;
@@ -1630,7 +1560,52 @@ std::string get_system_info(const gpt_params & params) {
     return os.str();
 }
 
-std::string gpt_random_prompt(std::mt19937 & rng) {
+//
+// String utils
+//
+
+std::vector<std::string> string_split(std::string input, char separator) {
+    std::vector<std::string> parts;
+    size_t separator_pos = input.find(separator);
+    while (separator_pos != std::string::npos) {
+        std::string part = input.substr(0, separator_pos);
+        parts.emplace_back(part);
+        input = input.substr(separator_pos + 1);
+        separator_pos = input.find(separator);
+    }
+    parts.emplace_back(input);
+    return parts;
+}
+
+std::string string_strip(const std::string & str) {
+    size_t start = 0;
+    size_t end = str.size();
+    while (start < end && std::isspace(str[start])) {
+        start++;
+    }
+    while (end > start && std::isspace(str[end - 1])) {
+        end--;
+    }
+    return str.substr(start, end - start);
+}
+
+std::string string_get_sortable_timestamp() {
+    using clock = std::chrono::system_clock;
+
+    const clock::time_point current_time = clock::now();
+    const time_t as_time_t = clock::to_time_t(current_time);
+    char timestamp_no_ns[100];
+    std::strftime(timestamp_no_ns, 100, "%Y_%m_%d-%H_%M_%S", std::localtime(&as_time_t));
+
+    const int64_t ns = std::chrono::duration_cast<std::chrono::nanoseconds>(
+        current_time.time_since_epoch() % 1000000000).count();
+    char timestamp_ns[11];
+    snprintf(timestamp_ns, 11, "%09" PRId64, ns);
+
+    return std::string(timestamp_no_ns) + "." + std::string(timestamp_ns);
+}
+
+std::string string_random_prompt(std::mt19937 & rng) {
     const int r = rng() % 10;
     switch (r) {
         case 0: return "So";
@@ -1648,9 +1623,96 @@ std::string gpt_random_prompt(std::mt19937 & rng) {
     GGML_UNREACHABLE();
 }
 
+void string_process_escapes(std::string & input) {
+    std::size_t input_len = input.length();
+    std::size_t output_idx = 0;
+
+    for (std::size_t input_idx = 0; input_idx < input_len; ++input_idx) {
+        if (input[input_idx] == '\\' && input_idx + 1 < input_len) {
+            switch (input[++input_idx]) {
+                case 'n':  input[output_idx++] = '\n'; break;
+                case 'r':  input[output_idx++] = '\r'; break;
+                case 't':  input[output_idx++] = '\t'; break;
+                case '\'': input[output_idx++] = '\''; break;
+                case '\"': input[output_idx++] = '\"'; break;
+                case '\\': input[output_idx++] = '\\'; break;
+                case 'x':
+                    // Handle \x12, etc
+                    if (input_idx + 2 < input_len) {
+                        const char x[3] = { input[input_idx + 1], input[input_idx + 2], 0 };
+                        char *err_p = nullptr;
+                        const long val = std::strtol(x, &err_p, 16);
+                        if (err_p == x + 2) {
+                            input_idx += 2;
+                            input[output_idx++] = char(val);
+                            break;
+                        }
+                    }
+                    // fall through
+                default:   input[output_idx++] = '\\';
+                           input[output_idx++] = input[input_idx]; break;
+            }
+        } else {
+            input[output_idx++] = input[input_idx];
+        }
+    }
+
+    input.resize(output_idx);
+}
+
+bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides) {
+    const char * sep = strchr(data, '=');
+    if (sep == nullptr || sep - data >= 128) {
+        fprintf(stderr, "%s: malformed KV override '%s'\n", __func__, data);
+        return false;
+    }
+    llama_model_kv_override kvo;
+    std::strncpy(kvo.key, data, sep - data);
+    kvo.key[sep - data] = 0;
+    sep++;
+    if (strncmp(sep, "int:", 4) == 0) {
+        sep += 4;
+        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT;
+        kvo.val_i64 = std::atol(sep);
+    } else if (strncmp(sep, "float:", 6) == 0) {
+        sep += 6;
+        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT;
+        kvo.val_f64 = std::atof(sep);
+    } else if (strncmp(sep, "bool:", 5) == 0) {
+        sep += 5;
+        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL;
+        if (std::strcmp(sep, "true") == 0) {
+            kvo.val_bool = true;
+        } else if (std::strcmp(sep, "false") == 0) {
+            kvo.val_bool = false;
+        } else {
+            fprintf(stderr, "%s: invalid boolean value for KV override '%s'\n", __func__, data);
+            return false;
+        }
+    } else if (strncmp(sep, "str:", 4) == 0) {
+        sep += 4;
+        kvo.tag = LLAMA_KV_OVERRIDE_TYPE_STR;
+        if (strlen(sep) > 127) {
+            fprintf(stderr, "%s: malformed KV override '%s', value cannot exceed 127 chars\n", __func__, data);
+            return false;
+        }
+        strncpy(kvo.val_str, sep, 127);
+        kvo.val_str[127] = '\0';
+    } else {
+        fprintf(stderr, "%s: invalid type for KV override '%s'\n", __func__, data);
+        return false;
+    }
+    overrides.emplace_back(std::move(kvo));
+    return true;
+}
+
+//
+// Filesystem utils
+//
+
 // Validate if a filename is safe to use
 // To validate a full path, split the path by the OS-specific path separator, and validate each part with this function
-bool validate_file_name(const std::string & filename) {
+bool fs_validate_filename(const std::string & filename) {
     if (!filename.length()) {
         // Empty filename invalid
         return false;
@@ -1719,120 +1781,194 @@ bool validate_file_name(const std::string & filename) {
     return true;
 }
 
-//
-// String utils
-//
+// returns true if successful, false otherwise
+bool fs_create_directory_with_parents(const std::string & path) {
+#ifdef _WIN32
+    std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
+    std::wstring wpath = converter.from_bytes(path);
 
-std::vector<std::string> string_split(std::string input, char separator) {
-    std::vector<std::string> parts;
-    size_t separator_pos = input.find(separator);
-    while (separator_pos != std::string::npos) {
-        std::string part = input.substr(0, separator_pos);
-        parts.emplace_back(part);
-        input = input.substr(separator_pos + 1);
-        separator_pos = input.find(separator);
+    // if the path already exists, check whether it's a directory
+    const DWORD attributes = GetFileAttributesW(wpath.c_str());
+    if ((attributes != INVALID_FILE_ATTRIBUTES) && (attributes & FILE_ATTRIBUTE_DIRECTORY)) {
+        return true;
     }
-    parts.emplace_back(input);
-    return parts;
-}
 
-std::string string_strip(const std::string & str) {
-    size_t start = 0;
-    size_t end = str.size();
-    while (start < end && std::isspace(str[start])) {
-        start++;
-    }
-    while (end > start && std::isspace(str[end - 1])) {
-        end--;
-    }
-    return str.substr(start, end - start);
-}
+    size_t pos_slash = 0;
 
-std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) {
-    std::unordered_map<std::string, llama_sampler_type> sampler_canonical_name_map {
-        {"top_k",       llama_sampler_type::TOP_K},
-        {"top_p",       llama_sampler_type::TOP_P},
-        {"typical_p",   llama_sampler_type::TYPICAL_P},
-        {"min_p",       llama_sampler_type::MIN_P},
-        {"tfs_z",       llama_sampler_type::TFS_Z},
-        {"temperature", llama_sampler_type::TEMPERATURE}
-    };
+    // process path from front to back, procedurally creating directories
+    while ((pos_slash = path.find('\\', pos_slash)) != std::string::npos) {
+        const std::wstring subpath = wpath.substr(0, pos_slash);
+        const wchar_t * test = subpath.c_str();
 
-    // since samplers names are written multiple ways
-    // make it ready for both system names and input names
-    std::unordered_map<std::string, llama_sampler_type> sampler_alt_name_map {
-        {"top-k",       llama_sampler_type::TOP_K},
-        {"top-p",       llama_sampler_type::TOP_P},
-        {"nucleus",     llama_sampler_type::TOP_P},
-        {"typical-p",   llama_sampler_type::TYPICAL_P},
-        {"typical",     llama_sampler_type::TYPICAL_P},
-        {"min-p",       llama_sampler_type::MIN_P},
-        {"tfs-z",       llama_sampler_type::TFS_Z},
-        {"tfs",         llama_sampler_type::TFS_Z},
-        {"temp",        llama_sampler_type::TEMPERATURE}
-    };
+        const bool success = CreateDirectoryW(test, NULL);
+        if (!success) {
+            const DWORD error = GetLastError();
 
-    std::vector<llama_sampler_type> sampler_types;
-    sampler_types.reserve(names.size());
-    for (const auto & name : names)
-    {
-        auto sampler_item = sampler_canonical_name_map.find(name);
-        if (sampler_item != sampler_canonical_name_map.end())
-        {
-            sampler_types.push_back(sampler_item->second);
-        }
-        else
-        {
-            if (allow_alt_names)
-            {
-                sampler_item = sampler_alt_name_map.find(name);
-                if (sampler_item != sampler_alt_name_map.end())
-                {
-                    sampler_types.push_back(sampler_item->second);
+            // if the path already exists, ensure that it's a directory
+            if (error == ERROR_ALREADY_EXISTS) {
+                const DWORD attributes = GetFileAttributesW(subpath.c_str());
+                if (attributes == INVALID_FILE_ATTRIBUTES || !(attributes & FILE_ATTRIBUTE_DIRECTORY)) {
+                    return false;
                 }
+            } else {
+                return false;
             }
         }
+
+        pos_slash += 1;
     }
-    return sampler_types;
-}
 
-std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & names_string) {
-    std::unordered_map<char, llama_sampler_type> sampler_name_map {
-        {'k', llama_sampler_type::TOP_K},
-        {'p', llama_sampler_type::TOP_P},
-        {'y', llama_sampler_type::TYPICAL_P},
-        {'m', llama_sampler_type::MIN_P},
-        {'f', llama_sampler_type::TFS_Z},
-        {'t', llama_sampler_type::TEMPERATURE}
-    };
+    return true;
+#else
+    // if the path already exists, check whether it's a directory
+    struct stat info;
+    if (stat(path.c_str(), &info) == 0) {
+        return S_ISDIR(info.st_mode);
+    }
 
-    std::vector<llama_sampler_type> sampler_types;
-    sampler_types.reserve(names_string.size());
-    for (const auto & c : names_string) {
-        const auto sampler_item = sampler_name_map.find(c);
-        if (sampler_item != sampler_name_map.end()) {
-            sampler_types.push_back(sampler_item->second);
+    size_t pos_slash = 1; // skip leading slashes for directory creation
+
+    // process path from front to back, procedurally creating directories
+    while ((pos_slash = path.find('/', pos_slash)) != std::string::npos) {
+        const std::string subpath = path.substr(0, pos_slash);
+        struct stat info;
+
+        // if the path already exists, ensure that it's a directory
+        if (stat(subpath.c_str(), &info) == 0) {
+            if (!S_ISDIR(info.st_mode)) {
+                return false;
+            }
+        } else {
+            // create parent directories
+            const int ret = mkdir(subpath.c_str(), 0755);
+            if (ret != 0) {
+                return false;
+            }
         }
+
+        pos_slash += 1;
     }
-    return sampler_types;
+
+    return true;
+#endif // _WIN32
 }
 
-std::string sampler_type_to_name_string(llama_sampler_type sampler_type) {
-    switch (sampler_type) {
-        case llama_sampler_type::TOP_K:       return "top_k";
-        case llama_sampler_type::TFS_Z:       return "tfs_z";
-        case llama_sampler_type::TYPICAL_P:   return "typical_p";
-        case llama_sampler_type::TOP_P:       return "top_p";
-        case llama_sampler_type::MIN_P:       return "min_p";
-        case llama_sampler_type::TEMPERATURE: return "temperature";
-        default : return "";
+std::string fs_get_cache_directory() {
+    std::string cache_directory = "";
+    if (getenv("LLAMA_CACHE")) {
+        cache_directory = std::getenv("LLAMA_CACHE");
+        if (cache_directory.back() != DIRECTORY_SEPARATOR) {
+            cache_directory += DIRECTORY_SEPARATOR;
+        }
+    } else {
+#ifdef __linux__
+        if (std::getenv("XDG_CACHE_HOME")) {
+            cache_directory = std::getenv("XDG_CACHE_HOME");
+        } else {
+            cache_directory = std::getenv("HOME") + std::string("/.cache/");
+        }
+#elif defined(__APPLE__)
+        cache_directory = std::getenv("HOME") + std::string("/Library/Caches/");
+#elif defined(_WIN32)
+        cache_directory = std::getenv("APPDATA");
+#endif // __linux__
+        cache_directory += "llama.cpp";
+        cache_directory += DIRECTORY_SEPARATOR;
     }
+    return cache_directory;
 }
 
+
 //
 // Model utils
 //
 
+std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_params(gpt_params & params) {
+    auto mparams = llama_model_params_from_gpt_params(params);
+
+    llama_model * model = nullptr;
+
+    if (!params.hf_repo.empty() && !params.hf_file.empty()) {
+        model = llama_load_model_from_hf(params.hf_repo.c_str(), params.hf_file.c_str(), params.model.c_str(), mparams);
+    } else if (!params.model_url.empty()) {
+        model = llama_load_model_from_url(params.model_url.c_str(), params.model.c_str(), mparams);
+    } else {
+        model = llama_load_model_from_file(params.model.c_str(), mparams);
+    }
+
+    if (model == NULL) {
+        fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
+        return std::make_tuple(nullptr, nullptr);
+    }
+
+    auto cparams = llama_context_params_from_gpt_params(params);
+
+    llama_context * lctx = llama_new_context_with_model(model, cparams);
+    if (lctx == NULL) {
+        fprintf(stderr, "%s: error: failed to create context with model '%s'\n", __func__, params.model.c_str());
+        llama_free_model(model);
+        return std::make_tuple(nullptr, nullptr);
+    }
+
+    if (!params.control_vectors.empty()) {
+        if (params.control_vector_layer_start <= 0) params.control_vector_layer_start = 1;
+        if (params.control_vector_layer_end   <= 0) params.control_vector_layer_end   = llama_n_layer(model);
+
+        const auto cvec = llama_control_vector_load(params.control_vectors);
+        if (cvec.n_embd == -1) {
+            llama_free(lctx);
+            llama_free_model(model);
+            return std::make_tuple(nullptr, nullptr);
+        }
+
+        int err = llama_control_vector_apply(lctx,
+                                             cvec.data.data(),
+                                             cvec.data.size(),
+                                             cvec.n_embd,
+                                             params.control_vector_layer_start,
+                                             params.control_vector_layer_end);
+        if (err) {
+            llama_free(lctx);
+            llama_free_model(model);
+            return std::make_tuple(nullptr, nullptr);
+        }
+    }
+
+    for (unsigned int i = 0; i < params.lora_adapter.size(); ++i) {
+        const std::string & lora_adapter = std::get<0>(params.lora_adapter[i]);
+        float lora_scale = std::get<1>(params.lora_adapter[i]);
+        int err = llama_model_apply_lora_from_file(model,
+                                             lora_adapter.c_str(),
+                                             lora_scale,
+                                             ((i > 0) || params.lora_base.empty())
+                                                ? NULL
+                                                : params.lora_base.c_str(),
+                                             params.n_threads);
+        if (err != 0) {
+            fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
+            llama_free(lctx);
+            llama_free_model(model);
+            return std::make_tuple(nullptr, nullptr);
+        }
+    }
+
+    if (params.ignore_eos) {
+        params.sparams.logit_bias[llama_token_eos(model)] = -INFINITY;
+    }
+
+    if (params.warmup) {
+        LOG("warming up the model with an empty run\n");
+
+        std::vector<llama_token> tmp = { llama_token_bos(model), llama_token_eos(model), };
+        llama_decode(lctx, llama_batch_get_one(tmp.data(), std::min(tmp.size(), (size_t) params.n_batch), 0, 0));
+        llama_kv_cache_clear(lctx);
+        llama_synchronize(lctx);
+        llama_reset_timings(lctx);
+    }
+
+    return std::make_tuple(model, lctx);
+}
+
 struct llama_model_params llama_model_params_from_gpt_params(const gpt_params & params) {
     auto mparams = llama_model_default_params();
 
@@ -1918,27 +2054,6 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param
     return cparams;
 }
 
-void llama_batch_clear(struct llama_batch & batch) {
-    batch.n_tokens = 0;
-}
-
-void llama_batch_add(
-                 struct llama_batch & batch,
-                        llama_token   id,
-                          llama_pos   pos,
-    const std::vector<llama_seq_id> & seq_ids,
-                               bool   logits) {
-    batch.token   [batch.n_tokens] = id;
-    batch.pos     [batch.n_tokens] = pos;
-    batch.n_seq_id[batch.n_tokens] = seq_ids.size();
-    for (size_t i = 0; i < seq_ids.size(); ++i) {
-        batch.seq_id[batch.n_tokens][i] = seq_ids[i];
-    }
-    batch.logits  [batch.n_tokens] = logits;
-
-    batch.n_tokens++;
-}
-
 #ifdef LLAMA_USE_CURL
 
 static bool starts_with(const std::string & str, const std::string & prefix) {
@@ -2269,90 +2384,29 @@ struct llama_model * llama_load_model_from_hf(
 
 #endif // LLAMA_USE_CURL
 
-std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_params(gpt_params & params) {
-    auto mparams = llama_model_params_from_gpt_params(params);
+//
+// Batch utils
+//
 
-    llama_model * model = nullptr;
+void llama_batch_clear(struct llama_batch & batch) {
+    batch.n_tokens = 0;
+}
 
-    if (!params.hf_repo.empty() && !params.hf_file.empty()) {
-        model = llama_load_model_from_hf(params.hf_repo.c_str(), params.hf_file.c_str(), params.model.c_str(), mparams);
-    } else if (!params.model_url.empty()) {
-        model = llama_load_model_from_url(params.model_url.c_str(), params.model.c_str(), mparams);
-    } else {
-        model = llama_load_model_from_file(params.model.c_str(), mparams);
+void llama_batch_add(
+                 struct llama_batch & batch,
+                        llama_token   id,
+                          llama_pos   pos,
+    const std::vector<llama_seq_id> & seq_ids,
+                               bool   logits) {
+    batch.token   [batch.n_tokens] = id;
+    batch.pos     [batch.n_tokens] = pos;
+    batch.n_seq_id[batch.n_tokens] = seq_ids.size();
+    for (size_t i = 0; i < seq_ids.size(); ++i) {
+        batch.seq_id[batch.n_tokens][i] = seq_ids[i];
     }
+    batch.logits  [batch.n_tokens] = logits;
 
-    if (model == NULL) {
-        fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
-        return std::make_tuple(nullptr, nullptr);
-    }
-
-    auto cparams = llama_context_params_from_gpt_params(params);
-
-    llama_context * lctx = llama_new_context_with_model(model, cparams);
-    if (lctx == NULL) {
-        fprintf(stderr, "%s: error: failed to create context with model '%s'\n", __func__, params.model.c_str());
-        llama_free_model(model);
-        return std::make_tuple(nullptr, nullptr);
-    }
-
-    if (!params.control_vectors.empty()) {
-        if (params.control_vector_layer_start <= 0) params.control_vector_layer_start = 1;
-        if (params.control_vector_layer_end   <= 0) params.control_vector_layer_end   = llama_n_layer(model);
-
-        const auto cvec = llama_control_vector_load(params.control_vectors);
-        if (cvec.n_embd == -1) {
-            llama_free(lctx);
-            llama_free_model(model);
-            return std::make_tuple(nullptr, nullptr);
-        }
-
-        int err = llama_control_vector_apply(lctx,
-                                             cvec.data.data(),
-                                             cvec.data.size(),
-                                             cvec.n_embd,
-                                             params.control_vector_layer_start,
-                                             params.control_vector_layer_end);
-        if (err) {
-            llama_free(lctx);
-            llama_free_model(model);
-            return std::make_tuple(nullptr, nullptr);
-        }
-    }
-
-    for (unsigned int i = 0; i < params.lora_adapter.size(); ++i) {
-        const std::string & lora_adapter = std::get<0>(params.lora_adapter[i]);
-        float lora_scale = std::get<1>(params.lora_adapter[i]);
-        int err = llama_model_apply_lora_from_file(model,
-                                             lora_adapter.c_str(),
-                                             lora_scale,
-                                             ((i > 0) || params.lora_base.empty())
-                                                ? NULL
-                                                : params.lora_base.c_str(),
-                                             params.n_threads);
-        if (err != 0) {
-            fprintf(stderr, "%s: error: failed to apply lora adapter\n", __func__);
-            llama_free(lctx);
-            llama_free_model(model);
-            return std::make_tuple(nullptr, nullptr);
-        }
-    }
-
-    if (params.ignore_eos) {
-        params.sparams.logit_bias[llama_token_eos(model)] = -INFINITY;
-    }
-
-    if (params.warmup) {
-        LOG("warming up the model with an empty run\n");
-
-        std::vector<llama_token> tmp = { llama_token_bos(model), llama_token_eos(model), };
-        llama_decode(lctx, llama_batch_get_one(tmp.data(), std::min(tmp.size(), (size_t) params.n_batch), 0, 0));
-        llama_kv_cache_clear(lctx);
-        llama_synchronize(lctx);
-        llama_reset_timings(lctx);
-    }
-
-    return std::make_tuple(model, lctx);
+    batch.n_tokens++;
 }
 
 //
@@ -2440,321 +2494,11 @@ bool llama_should_add_bos_token(const llama_model * model) {
     return add_bos != -1 ? bool(add_bos) : (llama_vocab_type(model) == LLAMA_VOCAB_TYPE_SPM);
 }
 
-//
-// YAML utils
-//
-
-// returns true if successful, false otherwise
-bool create_directory_with_parents(const std::string & path) {
-#ifdef _WIN32
-    std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
-    std::wstring wpath = converter.from_bytes(path);
-
-    // if the path already exists, check whether it's a directory
-    const DWORD attributes = GetFileAttributesW(wpath.c_str());
-    if ((attributes != INVALID_FILE_ATTRIBUTES) && (attributes & FILE_ATTRIBUTE_DIRECTORY)) {
-        return true;
-    }
-
-    size_t pos_slash = 0;
-
-    // process path from front to back, procedurally creating directories
-    while ((pos_slash = path.find('\\', pos_slash)) != std::string::npos) {
-        const std::wstring subpath = wpath.substr(0, pos_slash);
-        const wchar_t * test = subpath.c_str();
-
-        const bool success = CreateDirectoryW(test, NULL);
-        if (!success) {
-            const DWORD error = GetLastError();
-
-            // if the path already exists, ensure that it's a directory
-            if (error == ERROR_ALREADY_EXISTS) {
-                const DWORD attributes = GetFileAttributesW(subpath.c_str());
-                if (attributes == INVALID_FILE_ATTRIBUTES || !(attributes & FILE_ATTRIBUTE_DIRECTORY)) {
-                    return false;
-                }
-            } else {
-                return false;
-            }
-        }
-
-        pos_slash += 1;
-    }
-
-    return true;
-#else
-    // if the path already exists, check whether it's a directory
-    struct stat info;
-    if (stat(path.c_str(), &info) == 0) {
-        return S_ISDIR(info.st_mode);
-    }
-
-    size_t pos_slash = 1; // skip leading slashes for directory creation
-
-    // process path from front to back, procedurally creating directories
-    while ((pos_slash = path.find('/', pos_slash)) != std::string::npos) {
-        const std::string subpath = path.substr(0, pos_slash);
-        struct stat info;
-
-        // if the path already exists, ensure that it's a directory
-        if (stat(subpath.c_str(), &info) == 0) {
-            if (!S_ISDIR(info.st_mode)) {
-                return false;
-            }
-        } else {
-            // create parent directories
-            const int ret = mkdir(subpath.c_str(), 0755);
-            if (ret != 0) {
-                return false;
-            }
-        }
-
-        pos_slash += 1;
-    }
-
-    return true;
-#endif // _WIN32
-}
-
-void dump_vector_float_yaml(FILE * stream, const char * prop_name, const std::vector<float> & data) {
-    if (data.empty()) {
-        fprintf(stream, "%s:\n", prop_name);
-        return;
-    }
-
-    fprintf(stream, "%s: [", prop_name);
-    for (size_t i = 0; i < data.size() - 1; ++i) {
-        fprintf(stream, "%e, ", data[i]);
-    }
-    fprintf(stream, "%e]\n", data.back());
-}
-
-void dump_vector_int_yaml(FILE * stream, const char * prop_name, const std::vector<int> & data) {
-    if (data.empty()) {
-        fprintf(stream, "%s:\n", prop_name);
-        return;
-    }
-
-    fprintf(stream, "%s: [", prop_name);
-    for (size_t i = 0; i < data.size() - 1; ++i) {
-        fprintf(stream, "%d, ", data[i]);
-    }
-    fprintf(stream, "%d]\n", data.back());
-}
-
-void dump_string_yaml_multiline(FILE * stream, const char * prop_name, const char * data) {
-    std::string data_str(data == NULL ? "" : data);
-
-    if (data_str.empty()) {
-        fprintf(stream, "%s:\n", prop_name);
-        return;
-    }
-
-    size_t pos_start = 0;
-    size_t pos_found = 0;
-
-    if (std::isspace(data_str[0]) || std::isspace(data_str.back())) {
-        data_str = std::regex_replace(data_str, std::regex("\n"), "\\n");
-        data_str = std::regex_replace(data_str, std::regex("\""), "\\\"");
-        data_str = std::regex_replace(data_str, std::regex(R"(\\[^n"])"), R"(\$&)");
-        data_str = "\"" + data_str + "\"";
-        fprintf(stream, "%s: %s\n", prop_name, data_str.c_str());
-        return;
-    }
-
-    if (data_str.find('\n') == std::string::npos) {
-        fprintf(stream, "%s: %s\n", prop_name, data_str.c_str());
-        return;
-    }
-
-    fprintf(stream, "%s: |\n", prop_name);
-    while ((pos_found = data_str.find('\n', pos_start)) != std::string::npos) {
-        fprintf(stream, "  %s\n", data_str.substr(pos_start, pos_found-pos_start).c_str());
-        pos_start = pos_found + 1;
-    }
-}
-
-std::string get_sortable_timestamp() {
-    using clock = std::chrono::system_clock;
-
-    const clock::time_point current_time = clock::now();
-    const time_t as_time_t = clock::to_time_t(current_time);
-    char timestamp_no_ns[100];
-    std::strftime(timestamp_no_ns, 100, "%Y_%m_%d-%H_%M_%S", std::localtime(&as_time_t));
-
-    const int64_t ns = std::chrono::duration_cast<std::chrono::nanoseconds>(
-        current_time.time_since_epoch() % 1000000000).count();
-    char timestamp_ns[11];
-    snprintf(timestamp_ns, 11, "%09" PRId64, ns);
-
-    return std::string(timestamp_no_ns) + "." + std::string(timestamp_ns);
-}
-
-void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const llama_context * lctx,
-                               const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc) {
-    const llama_sampling_params & sparams = params.sparams;
-
-    fprintf(stream, "build_commit: %s\n",        LLAMA_COMMIT);
-    fprintf(stream, "build_number: %d\n",        LLAMA_BUILD_NUMBER);
-    fprintf(stream, "cpu_has_arm_fma: %s\n",     ggml_cpu_has_arm_fma()     ? "true" : "false");
-    fprintf(stream, "cpu_has_avx: %s\n",         ggml_cpu_has_avx()         ? "true" : "false");
-    fprintf(stream, "cpu_has_avx_vnni: %s\n",    ggml_cpu_has_avx_vnni()    ? "true" : "false");
-    fprintf(stream, "cpu_has_avx2: %s\n",        ggml_cpu_has_avx2()        ? "true" : "false");
-    fprintf(stream, "cpu_has_avx512: %s\n",      ggml_cpu_has_avx512()      ? "true" : "false");
-    fprintf(stream, "cpu_has_avx512_vbmi: %s\n", ggml_cpu_has_avx512_vbmi() ? "true" : "false");
-    fprintf(stream, "cpu_has_avx512_vnni: %s\n", ggml_cpu_has_avx512_vnni() ? "true" : "false");
-    fprintf(stream, "cpu_has_cuda: %s\n",        ggml_cpu_has_cuda()        ? "true" : "false");
-    fprintf(stream, "cpu_has_vulkan: %s\n",      ggml_cpu_has_vulkan()      ? "true" : "false");
-    fprintf(stream, "cpu_has_clblast: %s\n",     ggml_cpu_has_clblast()     ? "true" : "false");
-    fprintf(stream, "cpu_has_kompute: %s\n",     ggml_cpu_has_kompute()     ? "true" : "false");
-    fprintf(stream, "cpu_has_fma: %s\n",         ggml_cpu_has_fma()         ? "true" : "false");
-    fprintf(stream, "cpu_has_gpublas: %s\n",     ggml_cpu_has_gpublas()     ? "true" : "false");
-    fprintf(stream, "cpu_has_neon: %s\n",        ggml_cpu_has_neon()        ? "true" : "false");
-    fprintf(stream, "cpu_has_f16c: %s\n",        ggml_cpu_has_f16c()        ? "true" : "false");
-    fprintf(stream, "cpu_has_fp16_va: %s\n",     ggml_cpu_has_fp16_va()     ? "true" : "false");
-    fprintf(stream, "cpu_has_wasm_simd: %s\n",   ggml_cpu_has_wasm_simd()   ? "true" : "false");
-    fprintf(stream, "cpu_has_blas: %s\n",        ggml_cpu_has_blas()        ? "true" : "false");
-    fprintf(stream, "cpu_has_sse3: %s\n",        ggml_cpu_has_sse3()        ? "true" : "false");
-    fprintf(stream, "cpu_has_vsx: %s\n",         ggml_cpu_has_vsx()         ? "true" : "false");
-    fprintf(stream, "cpu_has_matmul_int8: %s\n", ggml_cpu_has_matmul_int8() ? "true" : "false");
-
-#ifdef NDEBUG
-    fprintf(stream, "debug: false\n");
-#else
-    fprintf(stream, "debug: true\n");
-#endif // NDEBUG
-
-    fprintf(stream, "model_desc: %s\n", model_desc);
-    fprintf(stream, "n_vocab: %d  # output size of the final layer, 32001 for some models\n", llama_n_vocab(llama_get_model(lctx)));
-
-#ifdef __OPTIMIZE__
-    fprintf(stream, "optimize: true\n");
-#else
-    fprintf(stream, "optimize: false\n");
-#endif // __OPTIMIZE__
-
-    fprintf(stream, "time: %s\n", timestamp.c_str());
-
-    fprintf(stream, "\n");
-    fprintf(stream, "###############\n");
-    fprintf(stream, "# User Inputs #\n");
-    fprintf(stream, "###############\n");
-    fprintf(stream, "\n");
-
-    fprintf(stream, "alias: %s # default: unknown\n", params.model_alias.c_str());
-    fprintf(stream, "batch_size: %d # default: 512\n", params.n_batch);
-    dump_string_yaml_multiline(stream, "cfg_negative_prompt", sparams.cfg_negative_prompt.c_str());
-    fprintf(stream, "cfg_scale: %f # default: 1.0\n", sparams.cfg_scale);
-    fprintf(stream, "chunks: %d # default: -1 (unlimited)\n", params.n_chunks);
-    fprintf(stream, "color: %s # default: false\n", params.use_color ? "true" : "false");
-    fprintf(stream, "ctx_size: %d # default: 512\n", params.n_ctx);
-    fprintf(stream, "escape: %s # default: false\n", params.escape ? "true" : "false");
-    fprintf(stream, "file: # never logged, see prompt instead. Can still be specified for input.\n");
-    fprintf(stream, "frequency_penalty: %f # default: 0.0 \n", sparams.penalty_freq);
-    dump_string_yaml_multiline(stream, "grammar", sparams.grammar.c_str());
-    fprintf(stream, "grammar-file: # never logged, see grammar instead. Can still be specified for input.\n");
-    fprintf(stream, "hellaswag: %s # default: false\n", params.hellaswag ? "true" : "false");
-    fprintf(stream, "hellaswag_tasks: %zu # default: 400\n", params.hellaswag_tasks);
-
-    const auto logit_bias_eos = sparams.logit_bias.find(llama_token_eos(llama_get_model(lctx)));
-    const bool ignore_eos = logit_bias_eos != sparams.logit_bias.end() && logit_bias_eos->second == -INFINITY;
-    fprintf(stream, "ignore_eos: %s # default: false\n", ignore_eos ? "true" : "false");
-
-    dump_string_yaml_multiline(stream, "in_prefix", params.input_prefix.c_str());
-    fprintf(stream, "in_prefix_bos: %s # default: false\n", params.input_prefix_bos ? "true" : "false");
-    dump_string_yaml_multiline(stream, "in_suffix", params.input_prefix.c_str());
-    fprintf(stream, "instruct: %s # default: false\n", params.instruct ? "true" : "false");
-    fprintf(stream, "interactive: %s # default: false\n", params.interactive ? "true" : "false");
-    fprintf(stream, "interactive_specials: %s # default: false\n", params.interactive_specials ? "true" : "false");
-    fprintf(stream, "interactive_first: %s # default: false\n", params.interactive_first ? "true" : "false");
-    fprintf(stream, "keep: %d # default: 0\n", params.n_keep);
-    fprintf(stream, "logdir: %s # default: unset (no logging)\n", params.logdir.c_str());
-
-    fprintf(stream, "logit_bias:\n");
-    for (std::pair<llama_token, float> lb : sparams.logit_bias) {
-        if (ignore_eos && lb.first == logit_bias_eos->first) {
-            continue;
-        }
-        fprintf(stream, "  %d: %f", lb.first, lb.second);
-    }
-
-    fprintf(stream, "lora:\n");
-    for (std::tuple<std::string, float> la : params.lora_adapter) {
-        if (std::get<1>(la) != 1.0f) {
-            continue;
-        }
-        fprintf(stream, "  - %s\n", std::get<0>(la).c_str());
-    }
-    fprintf(stream, "lora_scaled:\n");
-    for (std::tuple<std::string, float> la : params.lora_adapter) {
-        if (std::get<1>(la) == 1.0f) {
-            continue;
-        }
-        fprintf(stream, "  - %s: %f\n", std::get<0>(la).c_str(), std::get<1>(la));
-    }
-    fprintf(stream, "lora_base: %s\n", params.lora_base.c_str());
-    fprintf(stream, "main_gpu: %d # default: 0\n", params.main_gpu);
-    fprintf(stream, "min_keep: %d # default: 0 (disabled)\n", sparams.min_keep);
-    fprintf(stream, "mirostat: %d # default: 0 (disabled)\n", sparams.mirostat);
-    fprintf(stream, "mirostat_ent: %f # default: 5.0\n", sparams.mirostat_tau);
-    fprintf(stream, "mirostat_lr: %f # default: 0.1\n", sparams.mirostat_eta);
-    fprintf(stream, "mlock: %s # default: false\n", params.use_mlock ? "true" : "false");
-    fprintf(stream, "model: %s # default: %s\n", params.model.c_str(), DEFAULT_MODEL_PATH);
-    fprintf(stream, "model_draft: %s # default:\n", params.model_draft.c_str());
-    fprintf(stream, "multiline_input: %s # default: false\n", params.multiline_input ? "true" : "false");
-    fprintf(stream, "n_gpu_layers: %d # default: -1\n", params.n_gpu_layers);
-    fprintf(stream, "n_predict: %d # default: -1 (unlimited)\n", params.n_predict);
-    fprintf(stream, "n_probs: %d # only used by server binary, default: 0\n", sparams.n_probs);
-    fprintf(stream, "no_mmap: %s # default: false\n", !params.use_mmap ? "true" : "false");
-    fprintf(stream, "penalize_nl: %s # default: false\n", sparams.penalize_nl ? "true" : "false");
-    fprintf(stream, "ppl_output_type: %d # default: 0\n", params.ppl_output_type);
-    fprintf(stream, "ppl_stride: %d # default: 0\n", params.ppl_stride);
-    fprintf(stream, "presence_penalty: %f # default: 0.0\n", sparams.penalty_present);
-    dump_string_yaml_multiline(stream, "prompt", params.prompt.c_str());
-    fprintf(stream, "prompt_cache: %s\n", params.path_prompt_cache.c_str());
-    fprintf(stream, "prompt_cache_all: %s # default: false\n", params.prompt_cache_all ? "true" : "false");
-    fprintf(stream, "prompt_cache_ro: %s # default: false\n", params.prompt_cache_ro ? "true" : "false");
-    dump_vector_int_yaml(stream, "prompt_tokens", prompt_tokens);
-    fprintf(stream, "random_prompt: %s # default: false\n", params.random_prompt ? "true" : "false");
-    fprintf(stream, "repeat_penalty: %f # default: 1.1\n", sparams.penalty_repeat);
-
-    fprintf(stream, "reverse_prompt:\n");
-    for (std::string ap : params.antiprompt) {
-        size_t pos = 0;
-        while ((pos = ap.find('\n', pos)) != std::string::npos) {
-            ap.replace(pos, 1, "\\n");
-            pos += 1;
-        }
-
-        fprintf(stream, "  - %s\n", ap.c_str());
-    }
-
-    fprintf(stream, "rope_freq_base: %f # default: 10000.0\n", params.rope_freq_base);
-    fprintf(stream, "rope_freq_scale: %f # default: 1.0\n", params.rope_freq_scale);
-    fprintf(stream, "seed: %u # default: -1 (random seed)\n", params.seed);
-    fprintf(stream, "simple_io: %s # default: false\n", params.simple_io ? "true" : "false");
-    fprintf(stream, "cont_batching: %s # default: false\n", params.cont_batching ? "true" : "false");
-    fprintf(stream, "flash_attn: %s # default: false\n", params.flash_attn ? "true" : "false");
-    fprintf(stream, "temp: %f # default: 0.8\n", sparams.temp);
-
-    const std::vector<float> tensor_split_vector(params.tensor_split, params.tensor_split + llama_max_devices());
-    dump_vector_float_yaml(stream, "tensor_split", tensor_split_vector);
-
-    fprintf(stream, "tfs: %f # default: 1.0\n", sparams.tfs_z);
-    fprintf(stream, "threads: %d # default: %u\n", params.n_threads, std::thread::hardware_concurrency());
-    fprintf(stream, "top_k: %d # default: 40\n", sparams.top_k);
-    fprintf(stream, "top_p: %f # default: 0.95\n", sparams.top_p);
-    fprintf(stream, "min_p: %f # default: 0.0\n", sparams.min_p);
-    fprintf(stream, "typical_p: %f # default: 1.0\n", sparams.typical_p);
-    fprintf(stream, "verbose_prompt: %s # default: false\n", params.verbose_prompt ? "true" : "false");
-    fprintf(stream, "display_prompt: %s # default: true\n", params.display_prompt ? "true" : "false");
-}
-
 //
 // KV cache utils
 //
 
-void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size) {
+void llama_kv_cache_dump_view(const llama_kv_cache_view & view, int row_size) {
     static const char slot_chars[] = ".123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+";
 
     printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d",
@@ -2777,7 +2521,7 @@ void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size) {
     printf("\n=== Done dumping\n");
 }
 
-void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size) {
+void llama_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_size) {
     static const char slot_chars[] = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz";
 
     printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d\n",
@@ -2825,6 +2569,10 @@ void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size) {
     printf("\n=== Done dumping\n");
 }
 
+//
+// Embedding utils
+//
+
 void llama_embd_normalize(const float * inp, float * out, int n) {
     double sum = 0.0;
     for (int i = 0; i < n; i++) {
@@ -3009,3 +2757,225 @@ llama_control_vector_data llama_control_vector_load(const std::vector<llama_cont
 
     return result;
 }
+
+//
+// YAML utils
+//
+
+void yaml_dump_vector_float(FILE * stream, const char * prop_name, const std::vector<float> & data) {
+    if (data.empty()) {
+        fprintf(stream, "%s:\n", prop_name);
+        return;
+    }
+
+    fprintf(stream, "%s: [", prop_name);
+    for (size_t i = 0; i < data.size() - 1; ++i) {
+        fprintf(stream, "%e, ", data[i]);
+    }
+    fprintf(stream, "%e]\n", data.back());
+}
+
+void yaml_dump_vector_int(FILE * stream, const char * prop_name, const std::vector<int> & data) {
+    if (data.empty()) {
+        fprintf(stream, "%s:\n", prop_name);
+        return;
+    }
+
+    fprintf(stream, "%s: [", prop_name);
+    for (size_t i = 0; i < data.size() - 1; ++i) {
+        fprintf(stream, "%d, ", data[i]);
+    }
+    fprintf(stream, "%d]\n", data.back());
+}
+
+void yaml_dump_string_multiline(FILE * stream, const char * prop_name, const char * data) {
+    std::string data_str(data == NULL ? "" : data);
+
+    if (data_str.empty()) {
+        fprintf(stream, "%s:\n", prop_name);
+        return;
+    }
+
+    size_t pos_start = 0;
+    size_t pos_found = 0;
+
+    if (std::isspace(data_str[0]) || std::isspace(data_str.back())) {
+        data_str = std::regex_replace(data_str, std::regex("\n"), "\\n");
+        data_str = std::regex_replace(data_str, std::regex("\""), "\\\"");
+        data_str = std::regex_replace(data_str, std::regex(R"(\\[^n"])"), R"(\$&)");
+        data_str = "\"" + data_str + "\"";
+        fprintf(stream, "%s: %s\n", prop_name, data_str.c_str());
+        return;
+    }
+
+    if (data_str.find('\n') == std::string::npos) {
+        fprintf(stream, "%s: %s\n", prop_name, data_str.c_str());
+        return;
+    }
+
+    fprintf(stream, "%s: |\n", prop_name);
+    while ((pos_found = data_str.find('\n', pos_start)) != std::string::npos) {
+        fprintf(stream, "  %s\n", data_str.substr(pos_start, pos_found-pos_start).c_str());
+        pos_start = pos_found + 1;
+    }
+}
+
+void yaml_dump_non_result_info(FILE * stream, const gpt_params & params, const llama_context * lctx,
+                               const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc) {
+    const llama_sampling_params & sparams = params.sparams;
+
+    fprintf(stream, "build_commit: %s\n",        LLAMA_COMMIT);
+    fprintf(stream, "build_number: %d\n",        LLAMA_BUILD_NUMBER);
+    fprintf(stream, "cpu_has_arm_fma: %s\n",     ggml_cpu_has_arm_fma()     ? "true" : "false");
+    fprintf(stream, "cpu_has_avx: %s\n",         ggml_cpu_has_avx()         ? "true" : "false");
+    fprintf(stream, "cpu_has_avx_vnni: %s\n",    ggml_cpu_has_avx_vnni()    ? "true" : "false");
+    fprintf(stream, "cpu_has_avx2: %s\n",        ggml_cpu_has_avx2()        ? "true" : "false");
+    fprintf(stream, "cpu_has_avx512: %s\n",      ggml_cpu_has_avx512()      ? "true" : "false");
+    fprintf(stream, "cpu_has_avx512_vbmi: %s\n", ggml_cpu_has_avx512_vbmi() ? "true" : "false");
+    fprintf(stream, "cpu_has_avx512_vnni: %s\n", ggml_cpu_has_avx512_vnni() ? "true" : "false");
+    fprintf(stream, "cpu_has_cuda: %s\n",        ggml_cpu_has_cuda()        ? "true" : "false");
+    fprintf(stream, "cpu_has_vulkan: %s\n",      ggml_cpu_has_vulkan()      ? "true" : "false");
+    fprintf(stream, "cpu_has_clblast: %s\n",     ggml_cpu_has_clblast()     ? "true" : "false");
+    fprintf(stream, "cpu_has_kompute: %s\n",     ggml_cpu_has_kompute()     ? "true" : "false");
+    fprintf(stream, "cpu_has_fma: %s\n",         ggml_cpu_has_fma()         ? "true" : "false");
+    fprintf(stream, "cpu_has_gpublas: %s\n",     ggml_cpu_has_gpublas()     ? "true" : "false");
+    fprintf(stream, "cpu_has_neon: %s\n",        ggml_cpu_has_neon()        ? "true" : "false");
+    fprintf(stream, "cpu_has_f16c: %s\n",        ggml_cpu_has_f16c()        ? "true" : "false");
+    fprintf(stream, "cpu_has_fp16_va: %s\n",     ggml_cpu_has_fp16_va()     ? "true" : "false");
+    fprintf(stream, "cpu_has_wasm_simd: %s\n",   ggml_cpu_has_wasm_simd()   ? "true" : "false");
+    fprintf(stream, "cpu_has_blas: %s\n",        ggml_cpu_has_blas()        ? "true" : "false");
+    fprintf(stream, "cpu_has_sse3: %s\n",        ggml_cpu_has_sse3()        ? "true" : "false");
+    fprintf(stream, "cpu_has_vsx: %s\n",         ggml_cpu_has_vsx()         ? "true" : "false");
+    fprintf(stream, "cpu_has_matmul_int8: %s\n", ggml_cpu_has_matmul_int8() ? "true" : "false");
+
+#ifdef NDEBUG
+    fprintf(stream, "debug: false\n");
+#else
+    fprintf(stream, "debug: true\n");
+#endif // NDEBUG
+
+    fprintf(stream, "model_desc: %s\n", model_desc);
+    fprintf(stream, "n_vocab: %d  # output size of the final layer, 32001 for some models\n", llama_n_vocab(llama_get_model(lctx)));
+
+#ifdef __OPTIMIZE__
+    fprintf(stream, "optimize: true\n");
+#else
+    fprintf(stream, "optimize: false\n");
+#endif // __OPTIMIZE__
+
+    fprintf(stream, "time: %s\n", timestamp.c_str());
+
+    fprintf(stream, "\n");
+    fprintf(stream, "###############\n");
+    fprintf(stream, "# User Inputs #\n");
+    fprintf(stream, "###############\n");
+    fprintf(stream, "\n");
+
+    fprintf(stream, "alias: %s # default: unknown\n", params.model_alias.c_str());
+    fprintf(stream, "batch_size: %d # default: 512\n", params.n_batch);
+    yaml_dump_string_multiline(stream, "cfg_negative_prompt", sparams.cfg_negative_prompt.c_str());
+    fprintf(stream, "cfg_scale: %f # default: 1.0\n", sparams.cfg_scale);
+    fprintf(stream, "chunks: %d # default: -1 (unlimited)\n", params.n_chunks);
+    fprintf(stream, "color: %s # default: false\n", params.use_color ? "true" : "false");
+    fprintf(stream, "ctx_size: %d # default: 512\n", params.n_ctx);
+    fprintf(stream, "escape: %s # default: false\n", params.escape ? "true" : "false");
+    fprintf(stream, "file: # never logged, see prompt instead. Can still be specified for input.\n");
+    fprintf(stream, "frequency_penalty: %f # default: 0.0 \n", sparams.penalty_freq);
+    yaml_dump_string_multiline(stream, "grammar", sparams.grammar.c_str());
+    fprintf(stream, "grammar-file: # never logged, see grammar instead. Can still be specified for input.\n");
+    fprintf(stream, "hellaswag: %s # default: false\n", params.hellaswag ? "true" : "false");
+    fprintf(stream, "hellaswag_tasks: %zu # default: 400\n", params.hellaswag_tasks);
+
+    const auto logit_bias_eos = sparams.logit_bias.find(llama_token_eos(llama_get_model(lctx)));
+    const bool ignore_eos = logit_bias_eos != sparams.logit_bias.end() && logit_bias_eos->second == -INFINITY;
+    fprintf(stream, "ignore_eos: %s # default: false\n", ignore_eos ? "true" : "false");
+
+    yaml_dump_string_multiline(stream, "in_prefix", params.input_prefix.c_str());
+    fprintf(stream, "in_prefix_bos: %s # default: false\n", params.input_prefix_bos ? "true" : "false");
+    yaml_dump_string_multiline(stream, "in_suffix", params.input_prefix.c_str());
+    fprintf(stream, "instruct: %s # default: false\n", params.instruct ? "true" : "false");
+    fprintf(stream, "interactive: %s # default: false\n", params.interactive ? "true" : "false");
+    fprintf(stream, "interactive_specials: %s # default: false\n", params.interactive_specials ? "true" : "false");
+    fprintf(stream, "interactive_first: %s # default: false\n", params.interactive_first ? "true" : "false");
+    fprintf(stream, "keep: %d # default: 0\n", params.n_keep);
+    fprintf(stream, "logdir: %s # default: unset (no logging)\n", params.logdir.c_str());
+
+    fprintf(stream, "logit_bias:\n");
+    for (std::pair<llama_token, float> lb : sparams.logit_bias) {
+        if (ignore_eos && lb.first == logit_bias_eos->first) {
+            continue;
+        }
+        fprintf(stream, "  %d: %f", lb.first, lb.second);
+    }
+
+    fprintf(stream, "lora:\n");
+    for (std::tuple<std::string, float> la : params.lora_adapter) {
+        if (std::get<1>(la) != 1.0f) {
+            continue;
+        }
+        fprintf(stream, "  - %s\n", std::get<0>(la).c_str());
+    }
+    fprintf(stream, "lora_scaled:\n");
+    for (std::tuple<std::string, float> la : params.lora_adapter) {
+        if (std::get<1>(la) == 1.0f) {
+            continue;
+        }
+        fprintf(stream, "  - %s: %f\n", std::get<0>(la).c_str(), std::get<1>(la));
+    }
+    fprintf(stream, "lora_base: %s\n", params.lora_base.c_str());
+    fprintf(stream, "main_gpu: %d # default: 0\n", params.main_gpu);
+    fprintf(stream, "min_keep: %d # default: 0 (disabled)\n", sparams.min_keep);
+    fprintf(stream, "mirostat: %d # default: 0 (disabled)\n", sparams.mirostat);
+    fprintf(stream, "mirostat_ent: %f # default: 5.0\n", sparams.mirostat_tau);
+    fprintf(stream, "mirostat_lr: %f # default: 0.1\n", sparams.mirostat_eta);
+    fprintf(stream, "mlock: %s # default: false\n", params.use_mlock ? "true" : "false");
+    fprintf(stream, "model: %s # default: %s\n", params.model.c_str(), DEFAULT_MODEL_PATH);
+    fprintf(stream, "model_draft: %s # default:\n", params.model_draft.c_str());
+    fprintf(stream, "multiline_input: %s # default: false\n", params.multiline_input ? "true" : "false");
+    fprintf(stream, "n_gpu_layers: %d # default: -1\n", params.n_gpu_layers);
+    fprintf(stream, "n_predict: %d # default: -1 (unlimited)\n", params.n_predict);
+    fprintf(stream, "n_probs: %d # only used by server binary, default: 0\n", sparams.n_probs);
+    fprintf(stream, "no_mmap: %s # default: false\n", !params.use_mmap ? "true" : "false");
+    fprintf(stream, "penalize_nl: %s # default: false\n", sparams.penalize_nl ? "true" : "false");
+    fprintf(stream, "ppl_output_type: %d # default: 0\n", params.ppl_output_type);
+    fprintf(stream, "ppl_stride: %d # default: 0\n", params.ppl_stride);
+    fprintf(stream, "presence_penalty: %f # default: 0.0\n", sparams.penalty_present);
+    yaml_dump_string_multiline(stream, "prompt", params.prompt.c_str());
+    fprintf(stream, "prompt_cache: %s\n", params.path_prompt_cache.c_str());
+    fprintf(stream, "prompt_cache_all: %s # default: false\n", params.prompt_cache_all ? "true" : "false");
+    fprintf(stream, "prompt_cache_ro: %s # default: false\n", params.prompt_cache_ro ? "true" : "false");
+    yaml_dump_vector_int(stream, "prompt_tokens", prompt_tokens);
+    fprintf(stream, "random_prompt: %s # default: false\n", params.random_prompt ? "true" : "false");
+    fprintf(stream, "repeat_penalty: %f # default: 1.1\n", sparams.penalty_repeat);
+
+    fprintf(stream, "reverse_prompt:\n");
+    for (std::string ap : params.antiprompt) {
+        size_t pos = 0;
+        while ((pos = ap.find('\n', pos)) != std::string::npos) {
+            ap.replace(pos, 1, "\\n");
+            pos += 1;
+        }
+
+        fprintf(stream, "  - %s\n", ap.c_str());
+    }
+
+    fprintf(stream, "rope_freq_base: %f # default: 10000.0\n", params.rope_freq_base);
+    fprintf(stream, "rope_freq_scale: %f # default: 1.0\n", params.rope_freq_scale);
+    fprintf(stream, "seed: %u # default: -1 (random seed)\n", params.seed);
+    fprintf(stream, "simple_io: %s # default: false\n", params.simple_io ? "true" : "false");
+    fprintf(stream, "cont_batching: %s # default: false\n", params.cont_batching ? "true" : "false");
+    fprintf(stream, "flash_attn: %s # default: false\n", params.flash_attn ? "true" : "false");
+    fprintf(stream, "temp: %f # default: 0.8\n", sparams.temp);
+
+    const std::vector<float> tensor_split_vector(params.tensor_split, params.tensor_split + llama_max_devices());
+    yaml_dump_vector_float(stream, "tensor_split", tensor_split_vector);
+
+    fprintf(stream, "tfs: %f # default: 1.0\n", sparams.tfs_z);
+    fprintf(stream, "threads: %d # default: %u\n", params.n_threads, std::thread::hardware_concurrency());
+    fprintf(stream, "top_k: %d # default: 40\n", sparams.top_k);
+    fprintf(stream, "top_p: %f # default: 0.95\n", sparams.top_p);
+    fprintf(stream, "min_p: %f # default: 0.0\n", sparams.min_p);
+    fprintf(stream, "typical_p: %f # default: 1.0\n", sparams.typical_p);
+    fprintf(stream, "verbose_prompt: %s # default: false\n", params.verbose_prompt ? "true" : "false");
+    fprintf(stream, "display_prompt: %s # default: true\n", params.display_prompt ? "true" : "false");
+}
diff --git a/common/common.h b/common/common.h
index 566490e2f..f68f3c297 100644
--- a/common/common.h
+++ b/common/common.h
@@ -27,7 +27,7 @@
 #define die_fmt(fmt, ...) do { fprintf(stderr, "error: " fmt "\n", __VA_ARGS__); exit(1); } while (0)
 
 #define print_build_info() do {                                                                     \
-    fprintf(stderr, "%s: build = %d (%s)\n", __func__, LLAMA_BUILD_NUMBER, LLAMA_COMMIT);           \
+    fprintf(stderr, "%s: build = %d (%s)\n",      __func__, LLAMA_BUILD_NUMBER, LLAMA_COMMIT);      \
     fprintf(stderr, "%s: built with %s for %s\n", __func__, LLAMA_COMPILER, LLAMA_BUILD_TARGET);    \
 } while(0)
 
@@ -35,14 +35,18 @@
 
 // build info
 extern int LLAMA_BUILD_NUMBER;
-extern char const *LLAMA_COMMIT;
-extern char const *LLAMA_COMPILER;
-extern char const *LLAMA_BUILD_TARGET;
+extern char const * LLAMA_COMMIT;
+extern char const * LLAMA_COMPILER;
+extern char const * LLAMA_BUILD_TARGET;
 
 struct llama_control_vector_load_info;
 
-int get_math_cpu_count();
-int32_t get_num_physical_cores();
+//
+// CPU utils
+//
+
+int32_t cpu_get_num_physical_cores();
+int32_t cpu_get_num_math();
 
 //
 // CLI argument parsing
@@ -51,7 +55,7 @@ int32_t get_num_physical_cores();
 struct gpt_params {
     uint32_t seed                 = LLAMA_DEFAULT_SEED; // RNG seed
 
-    int32_t n_threads             = get_math_cpu_count();
+    int32_t n_threads             = cpu_get_num_math();
     int32_t n_threads_draft       = -1;
     int32_t n_threads_batch       = -1;    // number of threads to use for batch processing (-1 = use n_threads)
     int32_t n_threads_batch_draft = -1;
@@ -179,33 +183,34 @@ struct gpt_params {
 
 void gpt_params_handle_model_default(gpt_params & params);
 
-bool parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides);
+bool gpt_params_parse_ex   (int argc, char ** argv, gpt_params & params);
+bool gpt_params_parse      (int argc, char ** argv, gpt_params & params);
+bool gpt_params_find_arg   (int argc, char ** argv, const std::string & arg, gpt_params & params, int & i, bool & invalid_param);
+void gpt_params_print_usage(int argc, char ** argv, const gpt_params & params);
 
-bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params);
-
-bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
-
-void gpt_print_usage(int argc, char ** argv, const gpt_params & params);
-
-bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_params & params, int & i, bool & invalid_param);
-
-std::string get_system_info(const gpt_params & params);
-
-std::string gpt_random_prompt(std::mt19937 & rng);
-
-void process_escapes(std::string& input);
-
-bool validate_file_name(const std::string & filename);
+std::string gpt_params_get_system_info(const gpt_params & params);
 
 //
 // String utils
 //
 
-std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
-std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & names_string);
 std::vector<std::string> string_split(std::string input, char separator);
+
 std::string string_strip(const std::string & str);
-std::string sampler_type_to_name_string(llama_sampler_type sampler_type);
+std::string string_get_sortable_timestamp();
+std::string string_random_prompt(std::mt19937 & rng);
+
+bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides);
+void string_process_escapes(std::string & input);
+
+//
+// Filesystem utils
+//
+
+bool fs_validate_filename(const std::string & filename);
+bool fs_create_directory_with_parents(const std::string & path);
+
+std::string fs_get_cache_directory();
 
 //
 // Model utils
@@ -276,29 +281,15 @@ std::string llama_detokenize_bpe(
 // defaults to true when model type is SPM, otherwise false.
 bool llama_should_add_bos_token(const llama_model * model);
 
-//
-// YAML utils
-//
-
-bool create_directory_with_parents(const std::string & path);
-void dump_vector_float_yaml(FILE * stream, const char * prop_name, const std::vector<float> & data);
-void dump_vector_int_yaml(FILE * stream, const char * prop_name, const std::vector<int> & data);
-void dump_string_yaml_multiline(FILE * stream, const char * prop_name, const char * data);
-std::string get_sortable_timestamp();
-
-void dump_non_result_info_yaml(
-    FILE * stream, const gpt_params & params, const llama_context * lctx,
-    const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc);
-
 //
 // KV cache utils
 //
 
 // Dump the KV cache view with the number of sequences per cell.
-void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size = 80);
+void llama_kv_cache_dump_view(const llama_kv_cache_view & view, int row_size = 80);
 
 // Dump the KV cache view showing individual sequences in each cell (long output).
-void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
+void llama_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
 
 //
 // Embedding utils
@@ -332,6 +323,20 @@ llama_control_vector_data llama_control_vector_load(const std::vector<llama_cont
 //
 // Split utils
 //
+
 static const char * const LLM_KV_SPLIT_NO            = "split.no";
 static const char * const LLM_KV_SPLIT_COUNT         = "split.count";
 static const char * const LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count";
+
+//
+// YAML utils
+//
+
+void yaml_dump_vector_float    (FILE * stream, const char * prop_name, const std::vector<float> & data);
+void yaml_dump_vector_int      (FILE * stream, const char * prop_name, const std::vector<int> & data);
+void yaml_dump_string_multiline(FILE * stream, const char * prop_name, const char * data);
+
+void yaml_dump_non_result_info(
+    FILE * stream, const gpt_params & params, const llama_context * lctx,
+    const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc);
+
diff --git a/common/sampling.cpp b/common/sampling.cpp
index f0f1b92d3..f1f803516 100644
--- a/common/sampling.cpp
+++ b/common/sampling.cpp
@@ -125,7 +125,7 @@ std::string llama_sampling_order_print(const llama_sampling_params & params) {
     std::string result = "CFG -> Penalties ";
     if (params.mirostat == 0) {
         for (auto sampler_type : params.samplers_sequence) {
-            const auto sampler_type_name = sampler_type_to_name_string(sampler_type);
+            const auto sampler_type_name = llama_sampling_type_to_str(sampler_type);
             if (!sampler_type_name.empty()) {
                 result += "-> " + sampler_type_name + " ";
             }
@@ -137,6 +137,87 @@ std::string llama_sampling_order_print(const llama_sampling_params & params) {
     return result;
 }
 
+std::string llama_sampling_type_to_str(llama_sampler_type sampler_type) {
+    switch (sampler_type) {
+        case llama_sampler_type::TOP_K:       return "top_k";
+        case llama_sampler_type::TFS_Z:       return "tfs_z";
+        case llama_sampler_type::TYPICAL_P:   return "typical_p";
+        case llama_sampler_type::TOP_P:       return "top_p";
+        case llama_sampler_type::MIN_P:       return "min_p";
+        case llama_sampler_type::TEMPERATURE: return "temperature";
+        default : return "";
+    }
+}
+
+std::vector<llama_sampler_type> llama_sampling_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) {
+    std::unordered_map<std::string, llama_sampler_type> sampler_canonical_name_map {
+        {"top_k",       llama_sampler_type::TOP_K},
+        {"top_p",       llama_sampler_type::TOP_P},
+        {"typical_p",   llama_sampler_type::TYPICAL_P},
+        {"min_p",       llama_sampler_type::MIN_P},
+        {"tfs_z",       llama_sampler_type::TFS_Z},
+        {"temperature", llama_sampler_type::TEMPERATURE}
+    };
+
+    // since samplers names are written multiple ways
+    // make it ready for both system names and input names
+    std::unordered_map<std::string, llama_sampler_type> sampler_alt_name_map {
+        {"top-k",       llama_sampler_type::TOP_K},
+        {"top-p",       llama_sampler_type::TOP_P},
+        {"nucleus",     llama_sampler_type::TOP_P},
+        {"typical-p",   llama_sampler_type::TYPICAL_P},
+        {"typical",     llama_sampler_type::TYPICAL_P},
+        {"min-p",       llama_sampler_type::MIN_P},
+        {"tfs-z",       llama_sampler_type::TFS_Z},
+        {"tfs",         llama_sampler_type::TFS_Z},
+        {"temp",        llama_sampler_type::TEMPERATURE}
+    };
+
+    std::vector<llama_sampler_type> sampler_types;
+    sampler_types.reserve(names.size());
+    for (const auto & name : names)
+    {
+        auto sampler_item = sampler_canonical_name_map.find(name);
+        if (sampler_item != sampler_canonical_name_map.end())
+        {
+            sampler_types.push_back(sampler_item->second);
+        }
+        else
+        {
+            if (allow_alt_names)
+            {
+                sampler_item = sampler_alt_name_map.find(name);
+                if (sampler_item != sampler_alt_name_map.end())
+                {
+                    sampler_types.push_back(sampler_item->second);
+                }
+            }
+        }
+    }
+    return sampler_types;
+}
+
+std::vector<llama_sampler_type> llama_sampling_types_from_chars(const std::string & names_string) {
+    std::unordered_map<char, llama_sampler_type> sampler_name_map {
+        {'k', llama_sampler_type::TOP_K},
+        {'p', llama_sampler_type::TOP_P},
+        {'y', llama_sampler_type::TYPICAL_P},
+        {'m', llama_sampler_type::MIN_P},
+        {'f', llama_sampler_type::TFS_Z},
+        {'t', llama_sampler_type::TEMPERATURE}
+    };
+
+    std::vector<llama_sampler_type> sampler_types;
+    sampler_types.reserve(names_string.size());
+    for (const auto & c : names_string) {
+        const auto sampler_item = sampler_name_map.find(c);
+        if (sampler_item != sampler_name_map.end()) {
+            sampler_types.push_back(sampler_item->second);
+        }
+    }
+    return sampler_types;
+}
+
 // no reasons to expose this function in header
 static void sampler_queue(
                    struct llama_context * ctx_main,
@@ -179,7 +260,7 @@ static llama_token llama_sampling_sample_impl(
                   struct llama_context * ctx_main,
                   struct llama_context * ctx_cfg,
                   const int idx,
-                  bool is_resampling) {  // Add a parameter to indicate if we are resampling
+                  bool is_resampling) {
     const llama_sampling_params & params = ctx_sampling->params;
 
     const float   temp            = params.temp;
@@ -188,8 +269,8 @@ static llama_token llama_sampling_sample_impl(
     const float   mirostat_eta    = params.mirostat_eta;
 
     std::vector<float> original_logits;
-    auto cur_p = llama_sampling_prepare(ctx_sampling, ctx_main, ctx_cfg, idx, !is_resampling, &original_logits);
-    if (!is_resampling) {
+    auto cur_p = llama_sampling_prepare(ctx_sampling, ctx_main, ctx_cfg, idx, /* apply_grammar= */ is_resampling, &original_logits);
+    if (ctx_sampling->grammar != NULL && !is_resampling) {
         GGML_ASSERT(!original_logits.empty());
     }
     llama_token id = 0;
@@ -252,7 +333,7 @@ static llama_token llama_sampling_sample_impl(
             // Restore logits from the copy
             std::copy(original_logits.begin(), original_logits.end(), logits);
 
-            return llama_sampling_sample_impl(ctx_sampling, ctx_main, ctx_cfg, idx, true);  // Pass true for is_resampling
+            return llama_sampling_sample_impl(ctx_sampling, ctx_main, ctx_cfg, idx, /* is_resampling= */ true);
         }
     }
 
@@ -285,7 +366,8 @@ static llama_token_data_array llama_sampling_prepare_impl(
     // Get a pointer to the logits
     float * logits = llama_get_logits_ith(ctx_main, idx);
 
-    if (apply_grammar && original_logits != NULL) {
+    if (ctx_sampling->grammar != NULL && !apply_grammar) {
+        GGML_ASSERT(original_logits != NULL);
         // Only make a copy of the original logits if we are not applying grammar checks, not sure if I actually have to do this.
         *original_logits = {logits, logits + llama_n_vocab(llama_get_model(ctx_main))};
     }
@@ -342,7 +424,7 @@ llama_token llama_sampling_sample(
                   struct llama_context * ctx_cfg,
                   const int idx) {
     // Call the implementation function with is_resampling set to false by default
-    return llama_sampling_sample_impl(ctx_sampling, ctx_main, ctx_cfg, idx, false);
+    return llama_sampling_sample_impl(ctx_sampling, ctx_main, ctx_cfg, idx, /* is_resampling= */ false);
 }
 
 llama_token_data_array llama_sampling_prepare(
diff --git a/common/sampling.h b/common/sampling.h
index 655732ad1..eeaa53b8b 100644
--- a/common/sampling.h
+++ b/common/sampling.h
@@ -116,6 +116,11 @@ std::string llama_sampling_print(const llama_sampling_params & params);
 // Print sampling order into a string
 std::string llama_sampling_order_print(const llama_sampling_params & params);
 
+std::string llama_sampling_type_to_str(llama_sampler_type sampler_type);
+
+std::vector<llama_sampler_type> llama_sampling_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
+std::vector<llama_sampler_type> llama_sampling_types_from_chars(const std::string & names_string);
+
 // this is a common sampling function used across the examples for convenience
 // it can serve as a starting point for implementing your own sampling function
 // Note: When using multiple sequences, it is the caller's responsibility to call
diff --git a/common/train.cpp b/common/train.cpp
index 0dbfd24df..2d41a1d29 100644
--- a/common/train.cpp
+++ b/common/train.cpp
@@ -1380,7 +1380,7 @@ bool consume_common_train_arg(
 
 void finish_processing_train_args(struct train_params_common * params) {
     if (params->escape) {
-        process_escapes(params->sample_start);
+        string_process_escapes(params->sample_start);
     }
 }
 
diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py
index 27983fadf..1923b88ba 100755
--- a/convert-hf-to-gguf-update.py
+++ b/convert-hf-to-gguf-update.py
@@ -72,6 +72,7 @@ models = [
     {"name": "mpt",            "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/mosaicml/mpt-7b", },
     {"name": "starcoder",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/bigcode/starcoder2-3b", },
     {"name": "gpt-2",          "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/openai-community/gpt2", },
+    {"name": "stablelm2",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b", },
     {"name": "refact",         "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/smallcloudai/Refact-1_6-base", },
     {"name": "command-r",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/CohereForAI/c4ai-command-r-v01", },
     {"name": "qwen2",          "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen1.5-7B", },
diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index b9f893cac..880f874b0 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -14,6 +14,7 @@ from pathlib import Path
 from hashlib import sha256
 from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterable, Iterator, Sequence, TypeVar, cast
 
+import math
 import numpy as np
 import torch
 
@@ -446,6 +447,9 @@ class Model:
         if chkhsh == "3ce83efda5659b07b1ad37ca97ca5797ea4285d9b9ab0dc679e4a720c9da7454":
             # ref: https://huggingface.co/openai-community/gpt2
             res = "gpt-2"
+        if chkhsh == "32d85c31273f8019248f2559fed492d929ea28b17e51d81d3bb36fff23ca72b3":
+            # ref: https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b
+            res = "stablelm2"
         if chkhsh == "6221ad2852e85ce96f791f476e0b390cf9b474c9e3d1362f53a24a06dc8220ff":
             # ref: https://huggingface.co/smallcloudai/Refact-1_6-base
             res = "refact"
@@ -573,6 +577,10 @@ class Model:
 
         vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size())
 
+        tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
+        scores: list[float] = [-10000.0] * vocab_size
+        toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size
+
         for token_id in range(tokenizer.vocab_size()):
             piece = tokenizer.IdToPiece(token_id)
             text = piece.encode("utf-8")
@@ -588,21 +596,23 @@ class Model:
             elif tokenizer.IsByte(token_id):
                 toktype = SentencePieceTokenTypes.BYTE
 
-            tokens.append(text)
-            scores.append(score)
-            toktypes.append(toktype)
+            tokens[token_id] = text
+            scores[token_id] = score
+            toktypes[token_id] = toktype
 
         added_tokens_file = self.dir_model / 'added_tokens.json'
         if added_tokens_file.is_file():
             with open(added_tokens_file, "r", encoding="utf-8") as f:
                 added_tokens_json = json.load(f)
-
                 for key in added_tokens_json:
-                    key = key.encode("utf-8")
-                    if key not in tokens:
-                        tokens.append(key)
-                        scores.append(-1000.0)
-                        toktypes.append(SentencePieceTokenTypes.USER_DEFINED)
+                    token_id = added_tokens_json[key]
+                    if (token_id >= vocab_size):
+                        logger.warning(f'ignore token {token_id}: id is out of range, max={vocab_size - 1}')
+                        continue
+
+                    tokens[token_id] = key.encode("utf-8")
+                    scores[token_id] = -1000.0
+                    toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
 
         if vocab_size > len(tokens):
             pad_count = vocab_size - len(tokens)
@@ -612,8 +622,6 @@ class Model:
                 scores.append(-1000.0)
                 toktypes.append(SentencePieceTokenTypes.UNUSED)
 
-        assert len(tokens) == vocab_size
-
         self.gguf_writer.add_tokenizer_model("llama")
         self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
@@ -665,6 +673,44 @@ class GPTNeoXModel(Model):
         self.gguf_writer.add_parallel_residual(self.hparams.get("use_parallel_residual", True))
         self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_eps"])
 
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        del bid  # unused
+
+        n_head = self.hparams.get("n_head", self.hparams.get("num_attention_heads"))
+        n_embed = self.hparams.get("hidden_size", self.hparams.get("n_embed"))
+
+        tensors: list[tuple[str, Tensor]] = []
+
+        if re.match(r"gpt_neox\.layers\.\d+\.attention\.query_key_value\.weight", name):
+            # Map bloom-style qkv_linear to gpt-style qkv_linear
+            # bloom: https://github.com/huggingface/transformers/blob/main/src/transformers/models/bloom/modeling_bloom.py#L238-L252  # noqa
+            # gpt-2: https://github.com/huggingface/transformers/blob/main/src/transformers/models/gpt2/modeling_gpt2.py#L312  # noqa
+            qkv_weights = data_torch.reshape((n_head, 3, n_embed // n_head, n_embed))
+            data_torch = torch.cat(
+                (
+                    qkv_weights[:, 0, :, :].reshape((-1, n_embed)),
+                    qkv_weights[:, 1, :, :].reshape((-1, n_embed)),
+                    qkv_weights[:, 2, :, :].reshape((-1, n_embed)),
+                ),
+                dim=0,
+            )
+            logger.info("re-format attention.linear_qkv.weight")
+        elif re.match(r"gpt_neox\.layers\.\d+\.attention\.query_key_value\.bias", name):
+            qkv_bias = data_torch.reshape((n_head, 3, n_embed // n_head))
+            data_torch = torch.cat(
+                (
+                    qkv_bias[:, 0, :].reshape((n_embed,)),
+                    qkv_bias[:, 1, :].reshape((n_embed,)),
+                    qkv_bias[:, 2, :].reshape((n_embed,)),
+                ),
+                dim=0,
+            )
+            logger.info("re-format attention.linear_qkv.bias")
+
+        tensors.append((self.map_tensor_name(name), data_torch))
+
+        return tensors
+
 
 @Model.register("BloomForCausalLM")
 class BloomModel(Model):
@@ -1141,45 +1187,6 @@ class RefactModel(Model):
         return tensors
 
 
-@Model.register("PersimmonForCausalLM")
-class PersimmonModel(Model):
-    model_arch = gguf.MODEL_ARCH.PERSIMMON
-
-    def set_gguf_parameters(self):
-        block_count = self.hparams.get("num_layers", self.hparams.get("num_hidden_layers"))
-        head_count = self.hparams["num_attention_heads"]
-        head_count_kv = head_count
-        hidden_size = self.hparams["hidden_size"]
-
-        self.gguf_writer.add_name('persimmon-8b-chat')
-        self.gguf_writer.add_context_length(self.hparams["max_position_embeddings"])
-        self.gguf_writer.add_embedding_length(hidden_size)
-        self.gguf_writer.add_block_count(block_count)
-        self.gguf_writer.add_feed_forward_length(self.hparams["intermediate_size"])
-
-        # NOTE: not sure about this change - why does the model not have a rope dimension count when it is smaller
-        #       than the head size?
-        #       ref: https://github.com/ggerganov/llama.cpp/pull/4889
-        # self.gguf_writer.add_rope_dimension_count(hidden_size // head_count)
-        self.gguf_writer.add_rope_dimension_count(hidden_size // head_count // 2)
-
-        self.gguf_writer.add_head_count(head_count)
-        self.gguf_writer.add_head_count_kv(head_count_kv)
-        self.gguf_writer.add_rope_freq_base(self.hparams["rope_theta"])
-        self.gguf_writer.add_layer_norm_eps(self.hparams["layer_norm_eps"])
-
-    def set_vocab(self):
-        self._set_vocab_sentencepiece()
-        # self.gguf_writer.add_bos_token_id(71013)
-        # self.gguf_writer.add_eos_token_id(71013)
-
-    def extra_f32_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool:
-        del name, new_name, bid, n_dims  # unused
-
-        # TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?)
-        return True
-
-
 @Model.register("StableLmForCausalLM", "StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM")
 class StableLMModel(Model):
     model_arch = gguf.MODEL_ARCH.STABLELM
@@ -1772,6 +1779,38 @@ class Phi3MiniModel(Model):
                     scores[token_id] = -1000.0
                     toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
 
+        tokenizer_config_file = self.dir_model / 'tokenizer_config.json'
+        if tokenizer_config_file.is_file():
+            with open(tokenizer_config_file, "r", encoding="utf-8") as f:
+                tokenizer_config_json = json.load(f)
+                added_tokens_decoder = tokenizer_config_json.get("added_tokens_decoder", {})
+                for token_id, foken_data in added_tokens_decoder.items():
+                    token_id = int(token_id)
+                    token = foken_data["content"].encode("utf-8")
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                        assert tokens[token_id] == token
+                    tokens[token_id] = token
+                    scores[token_id] = -1000.0
+                    toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
+                    if foken_data.get("special"):
+                        toktypes[token_id] = SentencePieceTokenTypes.CONTROL
+
+        tokenizer_file = self.dir_model / 'tokenizer.json'
+        if tokenizer_file.is_file():
+            with open(tokenizer_file, "r", encoding="utf-8") as f:
+                tokenizer_json = json.load(f)
+                added_tokens = tokenizer_json.get("added_tokens", [])
+                for foken_data in added_tokens:
+                    token_id = int(foken_data["id"])
+                    token = foken_data["content"].encode("utf-8")
+                    if toktypes[token_id] != SentencePieceTokenTypes.UNKNOWN:
+                        assert tokens[token_id] == token
+                    tokens[token_id] = token
+                    scores[token_id] = -1000.0
+                    toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
+                    if foken_data.get("special"):
+                        toktypes[token_id] = SentencePieceTokenTypes.CONTROL
+
         self.gguf_writer.add_tokenizer_model("llama")
         self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
@@ -1784,23 +1823,59 @@ class Phi3MiniModel(Model):
     def set_gguf_parameters(self):
         block_count = self.find_hparam(["num_hidden_layers", "n_layer"])
 
-        rot_pct = 1.0
         n_embd = self.find_hparam(["hidden_size", "n_embd"])
         n_head = self.find_hparam(["num_attention_heads", "n_head"])
+        n_head_kv = self.find_hparam(["num_key_value_heads", "n_head_kv"])
         rms_eps = self.find_hparam(["rms_norm_eps"])
+        max_pos_embds = self.find_hparam(["n_positions", "max_position_embeddings"])
+        orig_max_pos_embds = self.find_hparam(["original_max_position_embeddings"])
+        rope_dims = n_embd // n_head
 
         self.gguf_writer.add_name("Phi3")
-        self.gguf_writer.add_context_length(self.find_hparam(["n_positions", "max_position_embeddings"]))
-
+        self.gguf_writer.add_context_length(max_pos_embds)
+        self.gguf_writer.add_rope_scaling_orig_ctx_len(orig_max_pos_embds)
         self.gguf_writer.add_embedding_length(n_embd)
-        self.gguf_writer.add_feed_forward_length(8192)
+        self.gguf_writer.add_feed_forward_length(self.find_hparam(["intermediate_size"]))
         self.gguf_writer.add_block_count(block_count)
         self.gguf_writer.add_head_count(n_head)
-        self.gguf_writer.add_head_count_kv(n_head)
+        self.gguf_writer.add_head_count_kv(n_head_kv)
         self.gguf_writer.add_layer_norm_rms_eps(rms_eps)
-        self.gguf_writer.add_rope_dimension_count(int(rot_pct * n_embd) // n_head)
+        self.gguf_writer.add_rope_dimension_count(rope_dims)
+        self.gguf_writer.add_rope_freq_base(self.find_hparam(["rope_theta"]))
         self.gguf_writer.add_file_type(self.ftype)
 
+        # write rope scaling for long context (128k) model
+        rope_scaling = self.find_hparam(['rope_scaling'], True)
+        if (rope_scaling is None):
+            return
+
+        scale = max_pos_embds / orig_max_pos_embds
+
+        rope_scaling_type = rope_scaling.get('type', '').lower()
+        if len(rope_scaling_type) == 0:
+            raise KeyError('Missing the required key rope_scaling.type')
+
+        if rope_scaling_type == 'su':
+            attn_factor = math.sqrt(1 + math.log(scale) / math.log(orig_max_pos_embds)) if scale > 1.0 else 1.0
+        elif rope_scaling_type == 'yarn':
+            attn_factor = 0.1 * math.log(scale) + 1.0 if scale > 1.0 else 1.0
+        else:
+            raise NotImplementedError(f'The rope scaling type {rope_scaling_type} is not supported yet')
+
+        self.gguf_writer.add_rope_scaling_attn_factors(attn_factor)
+
+        long_factors = rope_scaling.get('long_factor', None)
+        short_factors = rope_scaling.get('short_factor', None)
+
+        if long_factors is None or short_factors is None:
+            raise KeyError('Missing the required key rope_scaling.long_factor or rope_scaling_short_factor')
+
+        if len(long_factors) != len(short_factors) or len(long_factors) != rope_dims / 2:
+            raise ValueError(f'The length of rope long and short factors must be {rope_dims / 2}')
+
+        self.gguf_writer.add_tensor(gguf.TENSOR_NAMES[gguf.MODEL_TENSOR.ROPE_FACTORS_LONG]  + ".weight", np.array(long_factors, dtype=np.float32))
+        self.gguf_writer.add_tensor(gguf.TENSOR_NAMES[gguf.MODEL_TENSOR.ROPE_FACTORS_SHORT] + ".weight", np.array(short_factors, dtype=np.float32))
+
 
 @Model.register("PlamoForCausalLM")
 class PlamoModel(Model):
@@ -2391,6 +2466,157 @@ class JinaBertV2Model(BertModel):
         self.gguf_writer.add_add_eos_token(True)
 
 
+@Model.register("ArcticForCausalLM")
+class ArcticModel(Model):
+    model_arch = gguf.MODEL_ARCH.ARCTIC
+
+    def set_vocab(self):
+        # The reason for using a custom implementation here is that the
+        # snowflake-arctic-instruct model redefined tokens 31998 and 31999 from
+        # tokenizer.model and used them as BOS and EOS instead of adding new tokens.
+        from sentencepiece import SentencePieceProcessor
+
+        tokenizer_path = self.dir_model / 'tokenizer.model'
+
+        if not tokenizer_path.is_file():
+            logger.error(f'Error: Missing {tokenizer_path}')
+            sys.exit(1)
+
+        # Read the whole vocabulary from the tokenizer.model file
+        tokenizer = SentencePieceProcessor()
+        tokenizer.LoadFromFile(str(tokenizer_path))
+
+        vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size())
+
+        tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
+        scores: list[float] = [-10000.0] * vocab_size
+        toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size
+
+        for token_id in range(tokenizer.vocab_size()):
+
+            piece = tokenizer.IdToPiece(token_id)
+            text = piece.encode("utf-8")
+            score = tokenizer.GetScore(token_id)
+
+            toktype = SentencePieceTokenTypes.NORMAL
+            if tokenizer.IsUnknown(token_id):
+                toktype = SentencePieceTokenTypes.UNKNOWN
+            elif tokenizer.IsControl(token_id):
+                toktype = SentencePieceTokenTypes.CONTROL
+            elif tokenizer.IsUnused(token_id):
+                toktype = SentencePieceTokenTypes.UNUSED
+            elif tokenizer.IsByte(token_id):
+                toktype = SentencePieceTokenTypes.BYTE
+
+            tokens[token_id] = text
+            scores[token_id] = score
+            toktypes[token_id] = toktype
+
+        # Use the added_tokens_decoder field from tokeniser_config.json as the source
+        # of information about added/redefined tokens and modify them accordingly.
+        tokenizer_config_file = self.dir_model / 'tokenizer_config.json'
+        if tokenizer_config_file.is_file():
+            with open(tokenizer_config_file, "r", encoding="utf-8") as f:
+                tokenizer_config_json = json.load(f)
+
+                if "added_tokens_decoder" in tokenizer_config_json:
+                    added_tokens_decoder = tokenizer_config_json["added_tokens_decoder"]
+                    for token_id, token_json in added_tokens_decoder.items():
+                        token_id = int(token_id)
+                        if (token_id >= vocab_size):
+                            logger.debug(f'ignore token {token_id}: id is out of range, max={vocab_size - 1}')
+                            continue
+
+                        token_content = token_json["content"]
+                        token_type = SentencePieceTokenTypes.USER_DEFINED
+                        token_score = -10000.0
+
+                        # Map unk_token to UNKNOWN, other special tokens to CONTROL
+                        # Set the score to 0.0 as in the original tokenizer.model
+                        if ("special" in token_json) and token_json["special"]:
+                            if token_content == tokenizer_config_json["unk_token"]:
+                                token_type = SentencePieceTokenTypes.UNKNOWN
+                            else:
+                                token_type = SentencePieceTokenTypes.CONTROL
+                            token_score = 0.0
+
+                        logger.info(f"Setting added token {token_id} to '{token_content}' (type: {token_type}, score: {token_score:.2f})")
+                        tokens[token_id] = token_content.encode("utf-8")
+                        toktypes[token_id] = token_type
+                        scores[token_id] = token_score
+
+        self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
+        self.gguf_writer.add_token_list(tokens)
+        self.gguf_writer.add_token_scores(scores)
+        self.gguf_writer.add_token_types(toktypes)
+
+        special_vocab = gguf.SpecialVocab(self.dir_model, n_vocab=len(tokens))
+        special_vocab.add_to_gguf(self.gguf_writer)
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        hparams = self.hparams
+        self.gguf_writer.add_vocab_size(hparams["vocab_size"])
+        self.gguf_writer.add_rope_dimension_count(hparams["hidden_size"] // hparams["num_attention_heads"])
+
+    _experts: list[dict[str, Tensor]] | None = None
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        n_head = self.hparams["num_attention_heads"]
+        n_kv_head = self.hparams.get("num_key_value_heads")
+
+        if name.endswith("q_proj.weight"):
+            data_torch = LlamaModel.permute(data_torch, n_head, n_head)
+        if name.endswith("k_proj.weight"):
+            data_torch = LlamaModel.permute(data_torch, n_head, n_kv_head)
+
+        # process the experts separately
+        if name.find("block_sparse_moe.experts") != -1:
+            n_experts = self.hparams["num_local_experts"]
+
+            assert bid is not None
+
+            if self._experts is None:
+                self._experts = [{} for _ in range(self.block_count)]
+
+            self._experts[bid][name] = data_torch
+
+            if len(self._experts[bid]) >= n_experts * 3:
+                tensors: list[tuple[str, Tensor]] = []
+
+                # merge the experts into a single 3d tensor
+                for wid in ["w1", "w2", "w3"]:
+                    datas: list[Tensor] = []
+
+                    for xid in range(n_experts):
+                        ename = f"model.layers.{bid}.block_sparse_moe.experts.{xid}.{wid}.weight"
+                        datas.append(self._experts[bid][ename])
+                        del self._experts[bid][ename]
+
+                    data_torch = torch.stack(datas, dim=0)
+
+                    merged_name = f"layers.{bid}.feed_forward.experts.{wid}.weight"
+
+                    new_name = self.map_tensor_name(merged_name)
+
+                    tensors.append((new_name, data_torch))
+                return tensors
+            else:
+                return []
+
+        return [(self.map_tensor_name(name), data_torch)]
+
+    def write_tensors(self):
+        super().write_tensors()
+
+        if self._experts is not None:
+            # flatten `list[dict[str, Tensor]]` into `list[str]`
+            experts = [k for d in self._experts for k in d.keys()]
+            if len(experts) > 0:
+                raise ValueError(f"Unprocessed experts: {experts}")
+
+
 @Model.register("DeepseekV2ForCausalLM")
 class DeepseekV2Model(Model):
     model_arch = gguf.MODEL_ARCH.DEEPSEEK2
diff --git a/convert-persimmon-to-gguf.py b/convert-persimmon-to-gguf.py
deleted file mode 100755
index 07dcade74..000000000
--- a/convert-persimmon-to-gguf.py
+++ /dev/null
@@ -1,143 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import logging
-import argparse
-import os
-import sys
-from pathlib import Path
-from pprint import pprint
-
-import torch
-from sentencepiece import SentencePieceProcessor
-
-if 'NO_LOCAL_GGUF' not in os.environ:
-    sys.path.insert(1, str(Path(__file__).parent / 'gguf-py'))
-import gguf
-
-logger = logging.getLogger("persimmon-to-gguf")
-
-
-def _flatten_dict(dct, tensors, prefix=None):
-    assert isinstance(dct, dict)
-    for key in dct.keys():
-        new_prefix = prefix + '.' + key if prefix is not None else key
-        if isinstance(dct[key], torch.Tensor):
-            tensors[new_prefix] = dct[key]
-        elif isinstance(dct[key], dict):
-            _flatten_dict(dct[key], tensors, new_prefix)
-        else:
-            raise ValueError(type(dct[key]))
-    return None
-
-
-def _get_sentencepiece_tokenizer_info(dir_model: Path):
-    tokenizer_path = dir_model / 'adept_vocab.model'
-    logger.info('getting sentencepiece tokenizer from', tokenizer_path)
-    tokenizer = SentencePieceProcessor(str(tokenizer_path))
-    logger.info('adding tokens')
-    tokens: list[bytes] = []
-    scores: list[float] = []
-    toktypes: list[int] = []
-
-    for i in range(tokenizer.vocab_size()):
-        text: bytes
-        score: float
-
-        piece = tokenizer.id_to_piece(i)
-        text = piece.encode("utf-8")
-        score = tokenizer.get_score(i)
-
-        toktype = 1
-        if tokenizer.is_unknown(i):
-            toktype = 2
-        if tokenizer.is_control(i):
-            toktype = 3
-        if tokenizer.is_unused(i):
-            toktype = 5
-        if tokenizer.is_byte(i):
-            toktype = 6
-
-        tokens.append(text)
-        scores.append(score)
-        toktypes.append(toktype)
-        pass
-    return tokens, scores, toktypes
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Convert a Persimmon model from Adept (e.g. Persimmon 8b chat) to a GGML compatible file")
-    parser.add_argument("--outfile",             type=Path, help="path to write to; default: based on input")
-    parser.add_argument("--ckpt-path",           type=Path, help="path to persimmon checkpoint .pt file")
-    parser.add_argument("--model-dir",           type=Path, help="directory containing model e.g. 8b_chat_model_release")
-    parser.add_argument("--adept-inference-dir", type=str,  help="path to adept-inference code directory")
-    parser.add_argument("--verbose",  action="store_true",  help="increase output verbosity")
-    args = parser.parse_args()
-    logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
-    sys.path.append(str(args.adept_inference_dir))
-    persimmon_model = torch.load(args.ckpt_path)
-    hparams = persimmon_model['args']
-    pprint(hparams)
-    tensors: dict[str, torch.Tensor] = {}
-    _flatten_dict(persimmon_model['model'], tensors, None)
-
-    arch = gguf.MODEL_ARCH.PERSIMMON
-    gguf_writer = gguf.GGUFWriter(args.outfile, gguf.MODEL_ARCH_NAMES[arch])
-
-    block_count = hparams.num_layers
-    head_count = hparams.num_attention_heads
-    head_count_kv = head_count
-    ctx_length = hparams.seq_length
-    hidden_size = hparams.hidden_size
-
-    gguf_writer.add_name('persimmon-8b-chat')
-    gguf_writer.add_context_length(ctx_length)
-    gguf_writer.add_embedding_length(hidden_size)
-    gguf_writer.add_block_count(block_count)
-    gguf_writer.add_feed_forward_length(hparams.ffn_hidden_size)
-    # ref: https://github.com/ggerganov/llama.cpp/pull/4889/commits/eea19039fc52ea2dbd1aab45b59ab4e3e29a3443
-    gguf_writer.add_rope_dimension_count(hidden_size // head_count // 2)
-    gguf_writer.add_head_count(head_count)
-    gguf_writer.add_head_count_kv(head_count_kv)
-    gguf_writer.add_rope_freq_base(hparams.rotary_emb_base)
-    gguf_writer.add_layer_norm_eps(hparams.layernorm_epsilon)
-
-    tokens, scores, toktypes = _get_sentencepiece_tokenizer_info(args.model_dir)
-    gguf_writer.add_tokenizer_model('llama')
-    gguf_writer.add_tokenizer_pre('default')
-    gguf_writer.add_token_list(tokens)
-    gguf_writer.add_token_scores(scores)
-    gguf_writer.add_token_types(toktypes)
-    gguf_writer.add_bos_token_id(71013)
-    gguf_writer.add_eos_token_id(71013)
-
-    tensor_map = gguf.get_tensor_name_map(arch, block_count)
-    logger.info(tensor_map)
-    for name in tensors.keys():
-        data_torch = tensors[name]
-        if name.endswith(".self_attention.rotary_emb.inv_freq"):
-            continue
-        old_dtype = data_torch.dtype
-        # TODO: FP16 conversion produces garbage outputs. (Q8_0 does not, so..?)
-        data = data_torch.to(torch.float32).squeeze().numpy()
-        new_name = tensor_map.get_name(name, try_suffixes = (".weight", ".bias"))
-        if new_name is None:
-            raise ValueError(f"Can not map tensor '{name}'")
-
-        n_dims = len(data.shape)
-        logger.debug(f"{new_name}, n_dims = {str(n_dims)}, {str(old_dtype)} --> {str(data.dtype)}")
-        gguf_writer.add_tensor(new_name, data)
-    logger.info("gguf: write header")
-    gguf_writer.write_header_to_file()
-    logger.info("gguf: write metadata")
-    gguf_writer.write_kv_data_to_file()
-    logger.info("gguf: write tensors")
-    gguf_writer.write_tensors_to_file()
-
-    gguf_writer.close()
-
-    logger.info(f"gguf: model successfully exported to '{args.outfile}'")
-
-
-if __name__ == '__main__':
-    main()
diff --git a/examples/batched/batched.cpp b/examples/batched/batched.cpp
index be30d20bf..591bc6e57 100644
--- a/examples/batched/batched.cpp
+++ b/examples/batched/batched.cpp
@@ -48,7 +48,7 @@ int main(int argc, char ** argv) {
         params.prompt = "Hello my name is";
     }
 
-    process_escapes(params.prompt);
+    string_process_escapes(params.prompt);
 
     // init LLM
 
diff --git a/examples/embedding/embedding.cpp b/examples/embedding/embedding.cpp
index 0c921ed69..004399b5f 100644
--- a/examples/embedding/embedding.cpp
+++ b/examples/embedding/embedding.cpp
@@ -80,7 +80,7 @@ int main(int argc, char ** argv) {
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {
-        params.prompt = gpt_random_prompt(rng);
+        params.prompt = string_random_prompt(rng);
     }
 
     llama_backend_init();
@@ -107,7 +107,7 @@ int main(int argc, char ** argv) {
     // print system information
     {
         fprintf(stderr, "\n");
-        fprintf(stderr, "%s\n", get_system_info(params).c_str());
+        fprintf(stderr, "%s\n", gpt_params_get_system_info(params).c_str());
     }
 
     // split the prompt into lines
diff --git a/examples/eval-callback/eval-callback.cpp b/examples/eval-callback/eval-callback.cpp
index e670d3769..51d67d6d9 100644
--- a/examples/eval-callback/eval-callback.cpp
+++ b/examples/eval-callback/eval-callback.cpp
@@ -152,7 +152,7 @@ int main(int argc, char ** argv) {
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {
-        params.prompt = gpt_random_prompt(rng);
+        params.prompt = string_random_prompt(rng);
     }
 
     llama_backend_init();
@@ -176,7 +176,7 @@ int main(int argc, char ** argv) {
     // print system information
     {
         fprintf(stderr, "\n");
-        fprintf(stderr, "%s\n", get_system_info(params).c_str());
+        fprintf(stderr, "%s\n", gpt_params_get_system_info(params).c_str());
     }
 
     bool OK = run(ctx, params);
diff --git a/examples/finetune/finetune.cpp b/examples/finetune/finetune.cpp
index 22743b1bf..22425730f 100644
--- a/examples/finetune/finetune.cpp
+++ b/examples/finetune/finetune.cpp
@@ -563,8 +563,8 @@ static struct ggml_tensor * llama_build_lora_finetune_graphs(
         // not capturing these, to silcence warnings
         const int rope_mode = 0;
 
-        return ggml_rope_custom(ctx,
-            t, KQ_pos, n_rot, rope_mode, n_ctx, 0,
+        return ggml_rope_ext(ctx,
+            t, KQ_pos, nullptr, n_rot, rope_mode, n_ctx, 0,
             rope_freq_base, rope_freq_scale, 0.0f, 1.0f, 0.0f, 0.0f
         );
     };
@@ -643,7 +643,8 @@ static struct ggml_tensor * llama_build_lora_finetune_graphs(
         struct ggml_tensor * t15 = ggml_permute      (ctx, t12, 0, 3, 1, 2);                         set_name(t15, "t15");     assert_shape_4d(t15, N, n_embd_head, n_head_kv, n_batch);
         struct ggml_tensor * t16;
         if (enable_flash_attn) {
-            t16 = ggml_flash_attn(ctx, t13, t14, t15, true);                                         set_name(t16, "t16");     assert_shape_4d(t16, n_embd_head, N, n_head, n_batch);
+            GGML_ASSERT(false && "TODO: ggml_flash_attn_ext() not yet supported");
+            //t16 = ggml_flash_attn(ctx, t13, t14, t15, true);                                         set_name(t16, "t16");     assert_shape_4d(t16, n_embd_head, N, n_head, n_batch);
         } else {
             struct ggml_tensor * t16_0 = ggml_mul_mat              (ctx, t14, t13);                  set_name(t16_0, "t16_0"); assert_shape_4d(t16_0, N, N, n_head, n_batch);
             struct ggml_tensor * t16_1 = ggml_scale_inplace        (ctx, t16_0, kv_scale);           set_name(t16_1, "t16_1"); assert_shape_4d(t16_1, N, N, n_head, n_batch);
diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp
index 82b19fc4f..25a2351cc 100644
--- a/examples/imatrix/imatrix.cpp
+++ b/examples/imatrix/imatrix.cpp
@@ -598,7 +598,7 @@ int main(int argc, char ** argv) {
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {
-        params.prompt = gpt_random_prompt(rng);
+        params.prompt = string_random_prompt(rng);
     }
 
     sparams.dataset = params.prompt_file;
@@ -667,7 +667,7 @@ int main(int argc, char ** argv) {
     // print system information
     {
         fprintf(stderr, "\n");
-        fprintf(stderr, "%s\n", get_system_info(params).c_str());
+        fprintf(stderr, "%s\n", gpt_params_get_system_info(params).c_str());
     }
 
     bool OK = compute_imatrix(ctx, params, compute_ppl, from_chunk);
diff --git a/examples/infill/infill.cpp b/examples/infill/infill.cpp
index afac145f6..539f78184 100644
--- a/examples/infill/infill.cpp
+++ b/examples/infill/infill.cpp
@@ -50,9 +50,9 @@ static void write_logfile(
         return;
     }
 
-    const std::string timestamp = get_sortable_timestamp();
+    const std::string timestamp = string_get_sortable_timestamp();
 
-    const bool success = create_directory_with_parents(params.logdir);
+    const bool success = fs_create_directory_with_parents(params.logdir);
     if (!success) {
         fprintf(stderr, "%s: warning: failed to create logdir %s, cannot write logfile\n",
                 __func__, params.logdir.c_str());
@@ -70,7 +70,7 @@ static void write_logfile(
     fprintf(logfile, "binary: infill\n");
     char model_desc[128];
     llama_model_desc(model, model_desc, sizeof(model_desc));
-    dump_non_result_info_yaml(logfile, params, ctx, timestamp, input_tokens, model_desc);
+    yaml_dump_non_result_info(logfile, params, ctx, timestamp, input_tokens, model_desc);
 
     fprintf(logfile, "\n");
     fprintf(logfile, "######################\n");
@@ -78,8 +78,8 @@ static void write_logfile(
     fprintf(logfile, "######################\n");
     fprintf(logfile, "\n");
 
-    dump_string_yaml_multiline(logfile, "output", output.c_str());
-    dump_vector_int_yaml(logfile, "output_tokens", output_tokens);
+    yaml_dump_string_multiline(logfile, "output", output.c_str());
+    yaml_dump_vector_int(logfile, "output_tokens", output_tokens);
 
     llama_dump_timing_info_yaml(logfile, ctx);
     fclose(logfile);
@@ -236,7 +236,7 @@ int main(int argc, char ** argv) {
     // print system information
     {
         LOG_TEE("\n");
-        LOG_TEE("%s\n", get_system_info(params).c_str());
+        LOG_TEE("%s\n", gpt_params_get_system_info(params).c_str());
     }
     const bool add_bos = llama_should_add_bos_token(model);
     GGML_ASSERT(llama_add_eos_token(model) != 1);
@@ -621,8 +621,8 @@ int main(int argc, char ** argv) {
 
                 if (params.escape) {
                     //process escape sequences, for the initial prompt this is done in common.cpp when we load the params, but for the interactive mode we need to do it here
-                    process_escapes(params.input_prefix);
-                    process_escapes(params.input_suffix);
+                    string_process_escapes(params.input_prefix);
+                    string_process_escapes(params.input_suffix);
                 }
                 suff_rm_leading_spc = params.escape;
                 if (suff_rm_leading_spc && params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
diff --git a/examples/llama-bench/llama-bench.cpp b/examples/llama-bench/llama-bench.cpp
index 8b965e199..2afdb3abd 100644
--- a/examples/llama-bench/llama-bench.cpp
+++ b/examples/llama-bench/llama-bench.cpp
@@ -195,12 +195,12 @@ static const cmd_params cmd_params_defaults = {
     /* model         */ {"models/7B/ggml-model-q4_0.gguf"},
     /* n_prompt      */ {512},
     /* n_gen         */ {128},
-    /* n_pg          */ {{512, 128}},
+    /* n_pg          */ {},
     /* n_batch       */ {2048},
     /* n_ubatch      */ {512},
     /* type_k        */ {GGML_TYPE_F16},
     /* type_v        */ {GGML_TYPE_F16},
-    /* n_threads     */ {get_math_cpu_count()},
+    /* n_threads     */ {cpu_get_num_math()},
     /* n_gpu_layers  */ {99},
     /* split_mode    */ {LLAMA_SPLIT_MODE_LAYER},
     /* main_gpu      */ {0},
diff --git a/examples/llama.android/app/src/main/cpp/CMakeLists.txt b/examples/llama.android/app/src/main/cpp/CMakeLists.txt
index 85139329a..4536974a5 100644
--- a/examples/llama.android/app/src/main/cpp/CMakeLists.txt
+++ b/examples/llama.android/app/src/main/cpp/CMakeLists.txt
@@ -12,15 +12,20 @@ cmake_minimum_required(VERSION 3.22.1)
 # build script scope).
 project("llama-android")
 
-include(FetchContent)
-FetchContent_Declare(
-        llama
-        GIT_REPOSITORY https://github.com/ggerganov/llama.cpp
-        GIT_TAG        master
-)
+## Fetch latest llama.cpp from GitHub
+#include(FetchContent)
+#FetchContent_Declare(
+#        llama
+#        GIT_REPOSITORY https://github.com/ggerganov/llama.cpp
+#        GIT_TAG        master
+#)
+#
+## Also provides "common"
+#FetchContent_MakeAvailable(llama)
 
-# Also provides "common"
-FetchContent_MakeAvailable(llama)
+# llama.cpp CI uses the code from the current branch
+# ref: https://github.com/ggerganov/llama.cpp/pull/7341#issuecomment-2117617700
+add_subdirectory(../../../../../../ build-llama)
 
 # Creates and names a library, sets it as either STATIC
 # or SHARED, and provides the relative paths to its source code.
diff --git a/examples/llava/llava-cli.cpp b/examples/llava/llava-cli.cpp
index a6d67e5d7..c974900f2 100644
--- a/examples/llava/llava-cli.cpp
+++ b/examples/llava/llava-cli.cpp
@@ -290,7 +290,7 @@ int main(int argc, char ** argv) {
 #endif // LOG_DISABLE_LOGS
 
     if (params.mmproj.empty() || (params.image.empty() && !prompt_contains_image(params.prompt))) {
-        gpt_print_usage(argc, argv, params);
+        gpt_params_print_usage(argc, argv, params);
         show_additional_info(argc, argv);
         return 1;
     }
diff --git a/examples/lookahead/lookahead.cpp b/examples/lookahead/lookahead.cpp
index 9c3540b20..54f060a85 100644
--- a/examples/lookahead/lookahead.cpp
+++ b/examples/lookahead/lookahead.cpp
@@ -174,7 +174,7 @@ int main(int argc, char ** argv) {
         // debug
         if (dump_kv_cache) {
             llama_kv_cache_view_update(ctx, &kvc_view);
-            dump_kv_cache_view_seqs(kvc_view, 40);
+            llama_kv_cache_dump_view_seqs(kvc_view, 40);
         }
 
         // build the mask from https://lmsys.org/blog/2023-11-21-lookahead-decoding/
diff --git a/examples/lookup/lookup.cpp b/examples/lookup/lookup.cpp
index eebbd00a5..83dbee91a 100644
--- a/examples/lookup/lookup.cpp
+++ b/examples/lookup/lookup.cpp
@@ -121,7 +121,7 @@ int main(int argc, char ** argv){
         // debug
         if (dump_kv_cache) {
             llama_kv_cache_view_update(ctx, &kvc_view);
-            dump_kv_cache_view_seqs(kvc_view, 40);
+            llama_kv_cache_dump_view_seqs(kvc_view, 40);
         }
 
         // print current draft sequence
diff --git a/examples/main/README.md b/examples/main/README.md
index 97e2ae4c2..ee930f4e7 100644
--- a/examples/main/README.md
+++ b/examples/main/README.md
@@ -325,3 +325,5 @@ These options provide extra functionality and customization when running the LLa
 -   `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default the data is split in proportion to VRAM but this may not be optimal for performance.
 -   `--lora FNAME`: Apply a LoRA (Low-Rank Adaptation) adapter to the model (implies --no-mmap). This allows you to adapt the pretrained model to specific tasks or domains.
 -   `--lora-base FNAME`: Optional model to use as a base for the layers modified by the LoRA adapter. This flag is used in conjunction with the `--lora` flag, and specifies the base model for the adaptation.
+
+-   `-hfr URL --hf-repo URL`: The url to the Hugging Face model repository. Used in conjunction with `--hf-file` or `-hff`. The model is downloaded and stored in the file provided by `-m` or `--model`. If `-m` is not provided, the model is auto-stored in the path specified by the `LLAMA_CACHE` environment variable  or in an OS-specific local cache.
diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index 9dee41001..09fa85fce 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -60,9 +60,9 @@ static void write_logfile(
         return;
     }
 
-    const std::string timestamp = get_sortable_timestamp();
+    const std::string timestamp = string_get_sortable_timestamp();
 
-    const bool success = create_directory_with_parents(params.logdir);
+    const bool success = fs_create_directory_with_parents(params.logdir);
     if (!success) {
         fprintf(stderr, "%s: warning: failed to create logdir %s, cannot write logfile\n",
                 __func__, params.logdir.c_str());
@@ -80,7 +80,7 @@ static void write_logfile(
     fprintf(logfile, "binary: main\n");
     char model_desc[128];
     llama_model_desc(model, model_desc, sizeof(model_desc));
-    dump_non_result_info_yaml(logfile, params, ctx, timestamp, input_tokens, model_desc);
+    yaml_dump_non_result_info(logfile, params, ctx, timestamp, input_tokens, model_desc);
 
     fprintf(logfile, "\n");
     fprintf(logfile, "######################\n");
@@ -88,8 +88,8 @@ static void write_logfile(
     fprintf(logfile, "######################\n");
     fprintf(logfile, "\n");
 
-    dump_string_yaml_multiline(logfile, "output", output.c_str());
-    dump_vector_int_yaml(logfile, "output_tokens", output_tokens);
+    yaml_dump_string_multiline(logfile, "output", output.c_str());
+    yaml_dump_vector_int(logfile, "output_tokens", output_tokens);
 
     llama_dump_timing_info_yaml(logfile, ctx);
     fclose(logfile);
@@ -181,7 +181,7 @@ int main(int argc, char ** argv) {
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {
-        params.prompt = gpt_random_prompt(rng);
+        params.prompt = string_random_prompt(rng);
     }
 
     LOG("%s: llama backend init\n", __func__);
@@ -219,7 +219,7 @@ int main(int argc, char ** argv) {
     // print system information
     {
         LOG_TEE("\n");
-        LOG_TEE("%s\n", get_system_info(params).c_str());
+        LOG_TEE("%s\n", gpt_params_get_system_info(params).c_str());
     }
 
     std::string path_session = params.path_prompt_cache;
@@ -474,12 +474,12 @@ int main(int argc, char ** argv) {
     LOG_TEE("\n\n");
 
     if (params.interactive) {
-        const char *control_message;
+        const char * control_message;
         if (params.multiline_input) {
-            control_message = " - To return control to LLaMa, end your input with '\\'.\n"
+            control_message = " - To return control to the AI, end your input with '\\'.\n"
                               " - To return control without starting a new line, end your input with '/'.\n";
         } else {
-            control_message = " - Press Return to return control to LLaMa.\n"
+            control_message = " - Press Return to return control to the AI.\n"
                               " - To return control without starting a new line, end your input with '/'.\n"
                               " - If you want to submit another line, end your input with '\\'.\n";
         }
@@ -707,7 +707,7 @@ int main(int argc, char ** argv) {
 
             const llama_token id = llama_sampling_sample(ctx_sampling, ctx, ctx_guidance);
 
-            llama_sampling_accept(ctx_sampling, ctx, id, true);
+            llama_sampling_accept(ctx_sampling, ctx, id, /* apply_grammar= */ true);
 
             LOG("last: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, ctx_sampling->prev).c_str());
 
@@ -728,7 +728,7 @@ int main(int argc, char ** argv) {
 
                 // push the prompt in the sampling context in order to apply repetition penalties later
                 // for the prompt, we don't apply grammar rules
-                llama_sampling_accept(ctx_sampling, ctx, embd_inp[n_consumed], false);
+                llama_sampling_accept(ctx_sampling, ctx, embd_inp[n_consumed], /* apply_grammar= */ false);
 
                 ++n_consumed;
                 if ((int) embd.size() >= params.n_batch) {
@@ -879,7 +879,7 @@ int main(int argc, char ** argv) {
                         embd_inp.insert(embd_inp.end(), cml_pfx.begin(), cml_pfx.end());
                     }
                     if (params.escape) {
-                        process_escapes(buffer);
+                        string_process_escapes(buffer);
                     }
 
                     const auto line_pfx = ::llama_tokenize(ctx, params.input_prefix, false, true);
diff --git a/examples/parallel/parallel.cpp b/examples/parallel/parallel.cpp
index 7c5595d6e..c731abb72 100644
--- a/examples/parallel/parallel.cpp
+++ b/examples/parallel/parallel.cpp
@@ -210,7 +210,7 @@ int main(int argc, char ** argv) {
     while (true) {
         if (dump_kv_cache) {
             llama_kv_cache_view_update(ctx, &kvc_view);
-            dump_kv_cache_view_seqs(kvc_view, 40);
+            llama_kv_cache_dump_view_seqs(kvc_view, 40);
         }
 
         llama_batch_clear(batch);
diff --git a/examples/perplexity/README.md b/examples/perplexity/README.md
index c2a3c5ce9..33a46d1a2 100644
--- a/examples/perplexity/README.md
+++ b/examples/perplexity/README.md
@@ -42,10 +42,13 @@ In addition to the KL divergence the following statistics are calculated with `-
 
 Results were generated using the CUDA backend and are sorted by Kullback-Leibler divergence relative to FP16.
 The "WT" importance matrices were created using varying numbers of Wikitext tokens and can be found [here](https://huggingface.co/JohannesGaessler/llama.cpp_importance_matrices/blob/main/imatrix-llama_3-8b-f16-2.7m_tokens.dat).
+Note: the FP16 logits used for the calculation of all metrics other than perplexity are stored in a binary file between runs.
+In order to save space this file does **not** contain the exact same FP32 logits but instead casts them to 16 bit unsigned integers (with some scaling).
+So the "f16" results are to be understood as the difference resulting only from this downcast.
 
 | Quantization | imatrix | Model size [GiB] | PPL                    | ΔPPL                   | KLD                   | Mean Δp           | RMS Δp           |
 |--------------|---------|------------------|------------------------|------------------------|-----------------------|-------------------|------------------|
-| f16          | None    |            14.97 | 6.233160 ±   0.037828  | -                      | -                     | -                 | -                |
+| f16          | None    |            14.97 | 6.233160 ±   0.037828  | 0.001524 ±   0.000755  | 0.000551 ±   0.000002 |  0.001 ± 0.002 %  | 0.787 ± 0.004 %  |
 | q8_0         | None    |             7.96 | 6.234284 ±   0.037878  | 0.002650 ±   0.001006  | 0.001355 ±   0.000006 | -0.019 ± 0.003 %  | 1.198 ± 0.007 %  |
 | q6_K         | None    |             6.14 | 6.253382 ±   0.038078  | 0.021748 ±   0.001852  | 0.005452 ±   0.000035 | -0.007 ± 0.006 %  | 2.295 ± 0.019 %  |
 | q5_K_M       | None    |             5.33 | 6.288607 ±   0.038338  | 0.056974 ±   0.002598  | 0.010762 ±   0.000079 | -0.114 ± 0.008 %  | 3.160 ± 0.031 %  |
diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp
index db6e0949d..30e5e282e 100644
--- a/examples/perplexity/perplexity.cpp
+++ b/examples/perplexity/perplexity.cpp
@@ -44,9 +44,9 @@ static void write_logfile(
         return;
     }
 
-    const std::string timestamp = get_sortable_timestamp();
+    const std::string timestamp = string_get_sortable_timestamp();
 
-    const bool success = create_directory_with_parents(params.logdir);
+    const bool success = fs_create_directory_with_parents(params.logdir);
     if (!success) {
         fprintf(stderr, "%s: warning: failed to create logdir %s, cannot write logfile\n",
                 __func__, params.logdir.c_str());
@@ -64,7 +64,7 @@ static void write_logfile(
     fprintf(logfile, "binary: main\n");
     char model_desc[128];
     llama_model_desc(model, model_desc, sizeof(model_desc));
-    dump_non_result_info_yaml(logfile, params, ctx, timestamp, results.tokens, model_desc);
+    yaml_dump_non_result_info(logfile, params, ctx, timestamp, results.tokens, model_desc);
 
     fprintf(logfile, "\n");
     fprintf(logfile, "######################\n");
@@ -72,9 +72,9 @@ static void write_logfile(
     fprintf(logfile, "######################\n");
     fprintf(logfile, "\n");
 
-    dump_vector_float_yaml(logfile, "logits", results.logits);
+    yaml_dump_vector_float(logfile, "logits", results.logits);
     fprintf(logfile, "ppl_value: %f\n", results.ppl_value);
-    dump_vector_float_yaml(logfile, "probs", results.probs);
+    yaml_dump_vector_float(logfile, "probs", results.probs);
 
     llama_dump_timing_info_yaml(logfile, ctx);
     fclose(logfile);
@@ -1425,7 +1425,7 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params
         // Use all tasks
         tasks.resize(n_task);
         printf("%s: reading tasks", __func__);
-        int n_dot = n_task/100;
+        int n_dot = std::max((int) n_task/100, 1);
         int i = 0;
         for (auto& task : tasks) {
             ++i;
@@ -1675,7 +1675,7 @@ static void multiple_choice_score(llama_context * ctx, const gpt_params & params
 
     llama_batch_free(batch);
 
-    if (n_done < 100) return;
+    if (n_done < 100 && (params.multiple_choice_tasks != 0 && params.multiple_choice_tasks < (size_t)n_task)) return;
 
     float p = 1.f*n_correct/n_done;
     float sigma = sqrt(p*(1-p)/(n_done-1));
@@ -2007,7 +2007,7 @@ int main(int argc, char ** argv) {
 
     std::mt19937 rng(params.seed);
     if (params.random_prompt) {
-        params.prompt = gpt_random_prompt(rng);
+        params.prompt = string_random_prompt(rng);
     }
 
     llama_backend_init();
@@ -2035,7 +2035,7 @@ int main(int argc, char ** argv) {
     // print system information
     {
         fprintf(stderr, "\n");
-        fprintf(stderr, "%s\n", get_system_info(params).c_str());
+        fprintf(stderr, "%s\n", gpt_params_get_system_info(params).c_str());
     }
 
     struct results_perplexity results;
diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp
index 909eab283..28584e14b 100644
--- a/examples/quantize/quantize.cpp
+++ b/examples/quantize/quantize.cpp
@@ -259,7 +259,7 @@ int main(int argc, char ** argv) {
                 usage(argv[0]);
             }
         } else if (strcmp(argv[arg_idx], "--override-kv") == 0) {
-            if (arg_idx == argc-1 || !parse_kv_override(argv[++arg_idx], kv_overrides)) {
+            if (arg_idx == argc-1 || !string_parse_kv_override(argv[++arg_idx], kv_overrides)) {
                 usage(argv[0]);
             }
         } else if (strcmp(argv[arg_idx], "--allow-requantize") == 0) {
@@ -284,7 +284,7 @@ int main(int argc, char ** argv) {
             } else {
                 usage(argv[0]);
             }
-        } else if (strcmp(argv[arg_idx], "--keep-split")) {
+        } else if (strcmp(argv[arg_idx], "--keep-split") == 0) {
             params.keep_split = true;
         } else {
             usage(argv[0]);
diff --git a/examples/quantize/tests.sh b/examples/quantize/tests.sh
index 160c12bee..a3ca74c68 100644
--- a/examples/quantize/tests.sh
+++ b/examples/quantize/tests.sh
@@ -41,8 +41,8 @@ $SPLIT --split-max-tensors 28  $WORK_PATH/gemma-1.1-2b-it.Q8_0.gguf $WORK_PATH/g
 echo PASS
 echo
 
-# 3. Requant model with '--keep_split'
-$QUANTIZE --allow-requantize --keep_split $WORK_PATH/ggml-model-split-00001-of-00006.gguf $WORK_PATH/ggml-model-requant.gguf Q4_K
+# 3. Requant model with '--keep-split'
+$QUANTIZE --allow-requantize --keep-split $WORK_PATH/ggml-model-split-00001-of-00006.gguf $WORK_PATH/ggml-model-requant.gguf Q4_K
 echo PASS
 echo
 
@@ -51,7 +51,7 @@ $MAIN --model $WORK_PATH/ggml-model-requant-00001-of-00006.gguf --random-prompt
 echo PASS
 echo
 
-# 4. Requant mode without '--keep_split'
+# 4. Requant mode without '--keep-split'
 $QUANTIZE --allow-requantize $WORK_PATH/ggml-model-split-00001-of-00006.gguf $WORK_PATH/ggml-model-requant-merge.gguf Q4_K
 echo PASS
 echo
diff --git a/examples/retrieval/retrieval.cpp b/examples/retrieval/retrieval.cpp
index 5ba71e76a..4e7530706 100644
--- a/examples/retrieval/retrieval.cpp
+++ b/examples/retrieval/retrieval.cpp
@@ -11,7 +11,7 @@ struct retrieval_params {
 };
 
 static void retrieval_params_print_usage(int argc, char ** argv, gpt_params & gpt_params, retrieval_params & params) {
-    gpt_print_usage(argc, argv, gpt_params);
+    gpt_params_print_usage(argc, argv, gpt_params);
     printf("retrieval options:\n");
     printf("  --context-file FNAME  file containing context to embed.\n");
     printf("                        specify multiple files by providing --context-file option multiple times.\n");
@@ -226,7 +226,7 @@ int main(int argc, char ** argv) {
     // print system information
     {
         fprintf(stderr, "\n");
-        fprintf(stderr, "%s\n", get_system_info(params).c_str());
+        fprintf(stderr, "%s\n", gpt_params_get_system_info(params).c_str());
     }
 
     // max batch size
diff --git a/examples/server/README.md b/examples/server/README.md
index 13cbdcd2c..0c3db8c84 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -18,8 +18,8 @@ The project is under active development, and we are [looking for feedback and co
 **Command line options:**
 
 - `-v`, `--verbose`: Enable verbose server output. When using the `/completion` endpoint, this includes the tokenized prompt, the full request and the full response.
-- `-t N`, `--threads N`: Set the number of threads to use during generation. Not used if model layers are offloaded to GPU. The server is using batching. This parameter is used only if one token is to be processed on CPU backend.
-- `-tb N, --threads-batch N`: Set the number of threads to use during batch and prompt processing. If not specified, the number of threads will be set to the number of threads used for generation. Not used if model layers are offloaded to GPU.
+- `-t N`, `--threads N`: Set the number of threads to use by CPU layers during generation. Not used by model layers that are offloaded to GPU. This option has no effect when using the maximum number of GPU layers. Default: `std::thread::hardware_concurrency()` (number of CPU cores).
+- `-tb N, --threads-batch N`: Set the number of threads to use by CPU layers during batch and prompt processing (>= 32 tokens). This option has no effect if a GPU is available. Default: `--threads`.
 - `--threads-http N`: Number of threads in the http server pool to process requests. Default: `max(std::thread::hardware_concurrency() - 1, --parallel N + 2)`
 - `-m FNAME`, `--model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`).
 - `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file. Default: unused
@@ -48,7 +48,7 @@ The project is under active development, and we are [looking for feedback and co
 - `--api-key`: Set an api key for request authorization. By default, the server responds to every request. With an api key set, the requests must have the Authorization header set with the api key as Bearer token. May be used multiple times to enable multiple valid keys.
 - `--api-key-file`: Path to file containing api keys delimited by new lines. If set, requests must include one of the keys for access. May be used in conjunction with `--api-key`s.
 - `--embeddings`: Enable embedding vector output and the OAI compatible endpoint /v1/embeddings. Physical batch size (`--ubatch-size`) must be carefully defined. Default: disabled
-- `-np N`, `--parallel N`: Set the number of slots for process requests. Default: `1`
+- `-np N`, `--parallel N`: Set the number of slots for process requests. Default: `1`. Values > 1 will allow for higher throughput with multiple parallel requests but the results will **not** be deterministic due to differences in rounding error.
 - `-cb`, `--cont-batching`: Enable continuous batching (a.k.a dynamic batching).  Default: disabled
 - `-spf FNAME`, `--system-prompt-file FNAME` Set a file to load a system prompt (initial prompt of all slots). This is useful for chat applications. [See more](#change-system-prompt-on-runtime)
 - `--mmproj MMPROJ_FILE`: Path to a multimodal projector file for LLaVA.
diff --git a/examples/server/public_simplechat/index.html b/examples/server/public_simplechat/index.html
new file mode 100644
index 000000000..1eb390b85
--- /dev/null
+++ b/examples/server/public_simplechat/index.html
@@ -0,0 +1,52 @@
+<!DOCTYPE html>
+<html lang="en">
+    <head>
+        <title>SimpleChat (LlamaCPP, ...) </title>
+        <meta charset="UTF-8" />
+        <meta name="viewport" content="width=device-width, initial-scale=1" />
+        <meta name="message" content="Save Nature Save Earth" />
+        <meta name="description" content="SimpleChat: trigger LLM web service endpoints /chat/completions and /completions, single/multi chat sessions" />
+        <meta name="author" content="by Humans for All" />
+        <meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate" />
+        <script src="simplechat.js" defer></script>
+        <link rel="stylesheet" href="simplechat.css" />
+    </head>
+    <body>
+        <div class="samecolumn" id="fullbody">
+
+            <div class="sameline">
+                <p class="heading flex-grow" > <b> SimpleChat </b> </p>
+                <div class="sameline">
+                    <label for="api-ep">Mode:</label>
+                    <select name="api-ep" id="api-ep">
+                    <option value="chat" selected>Chat</option>
+                    <option value="completion">Completion</option>
+                    </select>
+                </div>
+            </div>
+
+            <div id="sessions-div" class="sameline"></div>
+
+            <hr>
+            <div class="sameline">
+                <label for="system-in">System</label>
+                <input type="text" name="system" id="system-in" class="flex-grow"/>
+            </div>
+
+            <hr>
+            <div id="chat-div">
+                <p> Enter the system prompt above, before entering/submitting any user query.</p>
+                <p> Enter your text to the ai assistant below.</p>
+                <p> Use shift+enter for inserting enter.</p>
+                <p> Refresh the page to start over fresh.</p>
+            </div>
+
+            <hr>
+            <div class="sameline">
+                <textarea id="user-in" class="flex-grow" rows="3"></textarea>
+                <button id="user-btn">submit</button>
+            </div>
+
+        </div>
+    </body>
+</html>
diff --git a/examples/server/public_simplechat/readme.md b/examples/server/public_simplechat/readme.md
new file mode 100644
index 000000000..5ac8258f2
--- /dev/null
+++ b/examples/server/public_simplechat/readme.md
@@ -0,0 +1,81 @@
+
+# SimpleChat
+
+by Humans for All.
+
+
+## overview
+
+This simple web frontend, allows triggering/testing the server's /completions or /chat/completions endpoints
+in a simple way with minimal code from a common code base. Inturn additionally it tries to allow single or
+multiple independent back and forth chatting to an extent, with the ai llm model at a basic level, with their
+own system prompts.
+
+The UI follows a responsive web design so that the layout can adapt to available display space in a usable
+enough manner, in general.
+
+NOTE: Given that the idea is for basic minimal testing, it doesnt bother with any model context length and
+culling of old messages from the chat.
+
+NOTE: It doesnt set any parameters other than temperature for now. However if someone wants they can update
+the js file as needed.
+
+
+## usage
+
+One could run this web frontend directly using server itself or if anyone is thinking of adding a built in web
+frontend to configure the server over http(s) or so, then run this web frontend using something like python's
+http module.
+
+### running using examples/server
+
+bin/server -m path/model.gguf --path ../examples/server/public_simplechat [--port PORT]
+
+### running using python3's server module
+
+first run examples/server
+* bin/server -m path/model.gguf
+
+next run this web front end in examples/server/public_simplechat
+* cd ../examples/server/public_simplechat
+* python3 -m http.server PORT
+
+### using the front end
+
+Open this simple web front end from your local browser
+* http://127.0.0.1:PORT/index.html
+
+Once inside
+* Select between chat and completion mode. By default it is set to chat mode.
+* If you want to provide a system prompt, then ideally enter it first, before entering any user query.
+  * if chat.add_system_begin is used
+    * you cant change the system prompt, after it is has been submitted once along with user query.
+    * you cant set a system prompt, after you have submitted any user query
+  * if chat.add_system_anytime is used
+    * one can change the system prompt any time during chat, by changing the contents of system prompt.
+    * inturn the updated/changed system prompt will be inserted into the chat session.
+    * this allows for the subsequent user chatting to be driven by the new system prompt set above.
+* Enter your query and either press enter or click on the submit button.
+  If you want to insert enter (\n) as part of your chat/query to ai model, use shift+enter.
+* Wait for the logic to communicate with the server and get the response.
+  * the user is not allowed to enter any fresh query during this time.
+  * the user input box will be disabled and a working message will be shown in it.
+* just refresh the page, to reset wrt the chat history and or system prompt and start afresh.
+* Using NewChat one can start independent chat sessions.
+  * two independent chat sessions are setup by default.
+
+
+## Devel note
+
+Sometimes the browser may be stuborn with caching of the file, so your updates to html/css/js
+may not be visible. Also remember that just refreshing/reloading page in browser or for that
+matter clearing site data, dont directly override site caching in all cases. Worst case you may
+have to change port. Or in dev tools of browser, you may be able to disable caching fully.
+
+Concept of multiple chat sessions with different servers, as well as saving and restoring of
+those across browser usage sessions, can be woven around the SimpleChat/MultiChatUI class and
+its instances relatively easily, however given the current goal of keeping this simple, it has
+not been added, for now.
+
+By switching between chat.add_system_begin/anytime, one can control whether one can change
+the system prompt, anytime during the conversation or only at the beginning.
diff --git a/examples/server/public_simplechat/simplechat.css b/examples/server/public_simplechat/simplechat.css
new file mode 100644
index 000000000..d45f50a95
--- /dev/null
+++ b/examples/server/public_simplechat/simplechat.css
@@ -0,0 +1,61 @@
+/**
+ * the styling of the simplechat web frontend
+ * by Humans for All
+ */
+
+#fullbody {
+    height: 98vh;
+}
+
+.heading {
+    background-color: lightgray;
+}
+
+.session-selected {
+    background-color: lightblue;
+}
+
+.role-system {
+    background-color: lightblue;
+}
+.role-user {
+    background-color: lightgray;
+}
+
+.flex-grow {
+    flex-grow: 1;
+}
+.float-right {
+    float: right;
+}
+
+#chat-div {
+    overflow: scroll;
+    flex-grow: 1;
+    flex-shrink: 1;
+    min-height: 40vh;
+}
+button {
+    min-width: 8vw;
+}
+
+.sameline {
+    display: flex;
+    flex-direction: row;
+}
+.samecolumn {
+    display: flex;
+    flex-direction: column;
+}
+
+* {
+    margin: 0.6vmin;
+}
+
+@media print {
+
+    #fullbody {
+        height: auto;
+    }
+
+}
diff --git a/examples/server/public_simplechat/simplechat.js b/examples/server/public_simplechat/simplechat.js
new file mode 100644
index 000000000..3fc4dbc20
--- /dev/null
+++ b/examples/server/public_simplechat/simplechat.js
@@ -0,0 +1,478 @@
+// @ts-check
+// A simple completions and chat/completions test related web front end logic
+// by Humans for All
+
+class Roles {
+    static System = "system";
+    static User = "user";
+    static Assistant = "assistant";
+}
+
+class ApiEP {
+    static Chat = "chat";
+    static Completion = "completion";
+}
+
+let gUsageMsg = `
+    <p> Enter the system prompt above, before entering/submitting any user query.</p>
+    <p> Enter your text to the ai assistant below.</p>
+    <p> Use shift+enter for inserting enter.</p>
+    <p> Refresh the page to start over fresh.</p>
+`;
+
+class SimpleChat {
+
+    constructor() {
+        /**
+         * Maintain in a form suitable for common LLM web service chat/completions' messages entry
+         * @type {{role: string, content: string}[]}
+         */
+        this.xchat = [];
+        this.iLastSys = -1;
+    }
+
+    /**
+     * Add an entry into xchat
+     * @param {string} role
+     * @param {string|undefined|null} content
+     */
+    add(role, content) {
+        if ((content == undefined) || (content == null) || (content == "")) {
+            return false;
+        }
+        this.xchat.push( {role: role, content: content} );
+        if (role == Roles.System) {
+            this.iLastSys = this.xchat.length - 1;
+        }
+        return true;
+    }
+
+    /**
+     * Show the contents in the specified div
+     * @param {HTMLDivElement} div
+     * @param {boolean} bClear
+     */
+    show(div, bClear=true) {
+        if (bClear) {
+            div.replaceChildren();
+        }
+        let last = undefined;
+        for(const x of this.xchat) {
+            let entry = document.createElement("p");
+            entry.className = `role-${x.role}`;
+            entry.innerText = `${x.role}: ${x.content}`;
+            div.appendChild(entry);
+            last = entry;
+        }
+        if (last !== undefined) {
+            last.scrollIntoView(false);
+        } else {
+            if (bClear) {
+                div.innerHTML = gUsageMsg;
+            }
+        }
+    }
+
+    /**
+     * Add needed fields wrt json object to be sent wrt LLM web services completions endpoint
+     * Convert the json into string.
+     * @param {Object} obj
+     */
+    request_jsonstr(obj) {
+        obj["temperature"] = 0.7;
+        return JSON.stringify(obj);
+    }
+
+    /**
+     * Return a string form of json object suitable for chat/completions
+     */
+    request_messages_jsonstr() {
+        let req = {
+            messages: this.xchat,
+        }
+        return this.request_jsonstr(req);
+    }
+
+    /**
+     * Return a string form of json object suitable for /completions
+     */
+    request_prompt_jsonstr() {
+        let prompt = "";
+        for(const chat of this.xchat) {
+            prompt += `${chat.role}: ${chat.content}\n`;
+        }
+        let req = {
+            prompt: prompt,
+        }
+        return this.request_jsonstr(req);
+    }
+
+    /**
+     * Allow setting of system prompt, but only at begining.
+     * @param {string} sysPrompt
+     * @param {string} msgTag
+     */
+    add_system_begin(sysPrompt, msgTag) {
+        if (this.xchat.length == 0) {
+            if (sysPrompt.length > 0) {
+                return this.add(Roles.System, sysPrompt);
+            }
+        } else {
+            if (sysPrompt.length > 0) {
+                if (this.xchat[0].role !== Roles.System) {
+                    console.error(`ERRR:SimpleChat:SC:${msgTag}:You need to specify system prompt before any user query, ignoring...`);
+                } else {
+                    if (this.xchat[0].content !== sysPrompt) {
+                        console.error(`ERRR:SimpleChat:SC:${msgTag}:You cant change system prompt, mid way through, ignoring...`);
+                    }
+                }
+            }
+        }
+        return false;
+    }
+
+    /**
+     * Allow setting of system prompt, at any time.
+     * @param {string} sysPrompt
+     * @param {string} msgTag
+     */
+    add_system_anytime(sysPrompt, msgTag) {
+        if (sysPrompt.length <= 0) {
+            return false;
+        }
+
+        if (this.iLastSys < 0) {
+            return this.add(Roles.System, sysPrompt);
+        }
+
+        let lastSys = this.xchat[this.iLastSys].content;
+        if (lastSys !== sysPrompt) {
+            return this.add(Roles.System, sysPrompt);
+        }
+        return false;
+    }
+
+    /**
+     * Retrieve the latest system prompt.
+     */
+    get_system_latest() {
+        if (this.iLastSys == -1) {
+            return "";
+        }
+        let sysPrompt = this.xchat[this.iLastSys].content;
+        return sysPrompt;
+    }
+
+}
+
+
+let gBaseURL = "http://127.0.0.1:8080";
+let gChatURL = {
+    'chat': `${gBaseURL}/chat/completions`,
+    'completion': `${gBaseURL}/completions`,
+}
+const gbCompletionFreshChatAlways = true;
+
+
+/**
+ * Set the class of the children, based on whether it is the idSelected or not.
+ * @param {HTMLDivElement} elBase
+ * @param {string} idSelected
+ * @param {string} classSelected
+ * @param {string} classUnSelected
+ */
+function el_children_config_class(elBase, idSelected, classSelected, classUnSelected="") {
+    for(let child of elBase.children) {
+        if (child.id == idSelected) {
+            child.className = classSelected;
+        } else {
+            child.className = classUnSelected;
+        }
+    }
+}
+
+/**
+ * Create button and set it up.
+ * @param {string} id
+ * @param {(this: HTMLButtonElement, ev: MouseEvent) => any} callback
+ * @param {string | undefined} name
+ * @param {string | undefined} innerText
+ */
+function el_create_button(id, callback, name=undefined, innerText=undefined) {
+    if (!name) {
+        name = id;
+    }
+    if (!innerText) {
+        innerText = id;
+    }
+    let btn = document.createElement("button");
+    btn.id = id;
+    btn.name = name;
+    btn.innerText = innerText;
+    btn.addEventListener("click", callback);
+    return btn;
+}
+
+
+class MultiChatUI {
+
+    constructor() {
+        /** @type {Object<string, SimpleChat>} */
+        this.simpleChats = {};
+        /** @type {string} */
+        this.curChatId = "";
+
+        // the ui elements
+        this.elInSystem = /** @type{HTMLInputElement} */(document.getElementById("system-in"));
+        this.elDivChat = /** @type{HTMLDivElement} */(document.getElementById("chat-div"));
+        this.elBtnUser = /** @type{HTMLButtonElement} */(document.getElementById("user-btn"));
+        this.elInUser = /** @type{HTMLInputElement} */(document.getElementById("user-in"));
+        this.elSelectApiEP = /** @type{HTMLSelectElement} */(document.getElementById("api-ep"));
+        this.elDivSessions = /** @type{HTMLDivElement} */(document.getElementById("sessions-div"));
+
+        this.validate_element(this.elInSystem, "system-in");
+        this.validate_element(this.elDivChat, "chat-div");
+        this.validate_element(this.elInUser, "user-in");
+        this.validate_element(this.elSelectApiEP, "api-ep");
+        this.validate_element(this.elDivChat, "sessions-div");
+    }
+
+    /**
+     * Check if the element got
+     * @param {HTMLElement | null} el
+     * @param {string} msgTag
+     */
+    validate_element(el, msgTag) {
+        if (el == null) {
+            throw Error(`ERRR:SimpleChat:MCUI:${msgTag} element missing in html...`);
+        } else {
+            console.debug(`INFO:SimpleChat:MCUI:${msgTag} Id[${el.id}] Name[${el["name"]}]`);
+        }
+    }
+
+    /**
+     * Reset user input ui.
+     * * clear user input
+     * * enable user input
+     * * set focus to user input
+     */
+    ui_reset_userinput() {
+        this.elInUser.value = "";
+        this.elInUser.disabled = false;
+        this.elInUser.focus();
+    }
+
+    /**
+     * Setup the needed callbacks wrt UI, curChatId to defaultChatId and
+     * optionally switch to specified defaultChatId.
+     * @param {string} defaultChatId
+     * @param {boolean} bSwitchSession
+     */
+    setup_ui(defaultChatId, bSwitchSession=false) {
+
+        this.curChatId = defaultChatId;
+        if (bSwitchSession) {
+            this.handle_session_switch(this.curChatId);
+        }
+
+        this.elBtnUser.addEventListener("click", (ev)=>{
+            if (this.elInUser.disabled) {
+                return;
+            }
+            this.handle_user_submit(this.curChatId, this.elSelectApiEP.value).catch((/** @type{Error} */reason)=>{
+                let msg = `ERRR:SimpleChat\nMCUI:HandleUserSubmit:${this.curChatId}\n${reason.name}:${reason.message}`;
+                console.debug(msg.replace("\n", ":"));
+                alert(msg);
+                this.ui_reset_userinput();
+            });
+        });
+
+        this.elInUser.addEventListener("keyup", (ev)=> {
+            // allow user to insert enter into their message using shift+enter.
+            // while just pressing enter key will lead to submitting.
+            if ((ev.key === "Enter") && (!ev.shiftKey)) {
+                this.elBtnUser.click();
+                ev.preventDefault();
+            }
+        });
+
+        this.elInSystem.addEventListener("keyup", (ev)=> {
+            // allow user to insert enter into the system prompt using shift+enter.
+            // while just pressing enter key will lead to setting the system prompt.
+            if ((ev.key === "Enter") && (!ev.shiftKey)) {
+                let chat = this.simpleChats[this.curChatId];
+                chat.add_system_anytime(this.elInSystem.value, this.curChatId);
+                chat.show(this.elDivChat);
+                ev.preventDefault();
+            }
+        });
+
+    }
+
+    /**
+     * Setup a new chat session and optionally switch to it.
+     * @param {string} chatId
+     * @param {boolean} bSwitchSession
+     */
+    new_chat_session(chatId, bSwitchSession=false) {
+        this.simpleChats[chatId] = new SimpleChat();
+        if (bSwitchSession) {
+            this.handle_session_switch(chatId);
+        }
+    }
+
+    /**
+     * Handle user query submit request, wrt specified chat session.
+     * @param {string} chatId
+     * @param {string} apiEP
+     */
+    async handle_user_submit(chatId, apiEP) {
+
+        let chat = this.simpleChats[chatId];
+
+        chat.add_system_anytime(this.elInSystem.value, chatId);
+
+        let content = this.elInUser.value;
+        if (!chat.add(Roles.User, content)) {
+            console.debug(`WARN:SimpleChat:MCUI:${chatId}:HandleUserSubmit:Ignoring empty user input...`);
+            return;
+        }
+        chat.show(this.elDivChat);
+
+        let theBody;
+        let theUrl = gChatURL[apiEP]
+        if (apiEP == ApiEP.Chat) {
+            theBody = chat.request_messages_jsonstr();
+        } else {
+            theBody = chat.request_prompt_jsonstr();
+        }
+
+        this.elInUser.value = "working...";
+        this.elInUser.disabled = true;
+        console.debug(`DBUG:SimpleChat:MCUI:${chatId}:HandleUserSubmit:${theUrl}:ReqBody:${theBody}`);
+        let resp = await fetch(theUrl, {
+            method: "POST",
+            headers: {
+                "Content-Type": "application/json",
+            },
+            body: theBody,
+        });
+
+        let respBody = await resp.json();
+        console.debug(`DBUG:SimpleChat:MCUI:${chatId}:HandleUserSubmit:RespBody:${JSON.stringify(respBody)}`);
+        let assistantMsg;
+        if (apiEP == ApiEP.Chat) {
+            assistantMsg = respBody["choices"][0]["message"]["content"];
+        } else {
+            try {
+                assistantMsg = respBody["choices"][0]["text"];
+            } catch {
+                assistantMsg = respBody["content"];
+            }
+        }
+        chat.add(Roles.Assistant, assistantMsg);
+        if (chatId == this.curChatId) {
+            chat.show(this.elDivChat);
+        } else {
+            console.debug(`DBUG:SimpleChat:MCUI:HandleUserSubmit:ChatId has changed:[${chatId}] [${this.curChatId}]`);
+        }
+        // Purposefully clear at end rather than begin of this function
+        // so that one can switch from chat to completion mode and sequece
+        // in a completion mode with multiple user-assistant chat data
+        // from before to be sent/occur once.
+        if ((apiEP == ApiEP.Completion) && (gbCompletionFreshChatAlways)) {
+            chat.xchat.length = 0;
+        }
+        this.ui_reset_userinput();
+    }
+
+    /**
+     * Show buttons for NewChat and available chat sessions, in the passed elDiv.
+     * If elDiv is undefined/null, then use this.elDivSessions.
+     * Take care of highlighting the selected chat-session's btn.
+     * @param {HTMLDivElement | undefined} elDiv
+     */
+    show_sessions(elDiv=undefined) {
+        if (!elDiv) {
+            elDiv = this.elDivSessions;
+        }
+        elDiv.replaceChildren();
+        // Btn for creating new chat session
+        let btnNew = el_create_button("New CHAT", (ev)=> {
+            if (this.elInUser.disabled) {
+                console.error(`ERRR:SimpleChat:MCUI:NewChat:Current session [${this.curChatId}] awaiting response, ignoring request...`);
+                alert("ERRR:SimpleChat\nMCUI:NewChat\nWait for response to pending query, before starting new chat session");
+                return;
+            }
+            let chatId = `Chat${Object.keys(this.simpleChats).length}`;
+            let chatIdGot = prompt("INFO:SimpleChat\nMCUI:NewChat\nEnter id for new chat session", chatId);
+            if (!chatIdGot) {
+                console.error("ERRR:SimpleChat:MCUI:NewChat:Skipping based on user request...");
+                return;
+            }
+            this.new_chat_session(chatIdGot, true);
+            this.create_session_btn(elDiv, chatIdGot);
+            el_children_config_class(elDiv, chatIdGot, "session-selected", "");
+        });
+        elDiv.appendChild(btnNew);
+        // Btns for existing chat sessions
+        let chatIds = Object.keys(this.simpleChats);
+        for(let cid of chatIds) {
+            let btn = this.create_session_btn(elDiv, cid);
+            if (cid == this.curChatId) {
+                btn.className = "session-selected";
+            }
+        }
+    }
+
+    create_session_btn(elDiv, cid) {
+        let btn = el_create_button(cid, (ev)=>{
+            let target = /** @type{HTMLButtonElement} */(ev.target);
+            console.debug(`DBUG:SimpleChat:MCUI:SessionClick:${target.id}`);
+            if (this.elInUser.disabled) {
+                console.error(`ERRR:SimpleChat:MCUI:SessionClick:${target.id}:Current session [${this.curChatId}] awaiting response, ignoring switch...`);
+                alert("ERRR:SimpleChat\nMCUI:SessionClick\nWait for response to pending query, before switching");
+                return;
+            }
+            this.handle_session_switch(target.id);
+            el_children_config_class(elDiv, target.id, "session-selected", "");
+        });
+        elDiv.appendChild(btn);
+        return btn;
+    }
+
+    /**
+     * Switch ui to the specified chatId and set curChatId to same.
+     * @param {string} chatId
+     */
+    async handle_session_switch(chatId) {
+        let chat = this.simpleChats[chatId];
+        if (chat == undefined) {
+            console.error(`ERRR:SimpleChat:MCUI:HandleSessionSwitch:${chatId} missing...`);
+            return;
+        }
+        this.elInSystem.value = chat.get_system_latest();
+        this.elInUser.value = "";
+        chat.show(this.elDivChat);
+        this.elInUser.focus();
+        this.curChatId = chatId;
+        console.log(`INFO:SimpleChat:MCUI:HandleSessionSwitch:${chatId} entered...`);
+    }
+
+}
+
+
+let gMuitChat;
+const gChatIds = [ "Default", "Other" ];
+
+function startme() {
+    console.log("INFO:SimpleChat:StartMe:Starting...");
+    gMuitChat = new MultiChatUI();
+    for (let cid of gChatIds) {
+        gMuitChat.new_chat_session(cid);
+    }
+    gMuitChat.setup_ui(gChatIds[0]);
+    gMuitChat.show_sessions();
+}
+
+document.addEventListener("DOMContentLoaded", startme);
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index b598076d3..e9904263d 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -102,7 +102,6 @@ struct slot_params {
     bool stream       = true;
     bool cache_prompt = false; // remember the prompt to avoid reprocessing all prompt
 
-    uint32_t seed      = -1; // RNG seed
     int32_t  n_keep    =  0; // number of tokens to keep from initial prompt
     int32_t  n_discard =  0; // number of tokens after n_keep that may be discarded when shifting context, 0 defaults to half
     int32_t  n_predict = -1; // new tokens to predict
@@ -1020,7 +1019,7 @@ struct server_context {
                         sampler_names.emplace_back(sampler_name);
                     }
                 }
-                slot.sparams.samplers_sequence = sampler_types_from_names(sampler_names, false);
+                slot.sparams.samplers_sequence = llama_sampling_types_from_names(sampler_names, false);
             } else {
                 slot.sparams.samplers_sequence = default_sparams.samplers_sequence;
             }
@@ -1257,14 +1256,14 @@ struct server_context {
         std::vector<std::string> samplers_sequence;
         samplers_sequence.reserve(slot.sparams.samplers_sequence.size());
         for (const auto & sampler_type : slot.sparams.samplers_sequence) {
-            samplers_sequence.emplace_back(sampler_type_to_name_string(sampler_type));
+            samplers_sequence.emplace_back(llama_sampling_type_to_str(sampler_type));
         }
 
         return json {
             {"n_ctx",                     slot.n_ctx},
             {"n_predict",                 slot.n_predict},
             {"model",                     params.model_alias},
-            {"seed",                      slot.params.seed},
+            {"seed",                      slot.sparams.seed},
             {"temperature",               slot.sparams.temp},
             {"dynatemp_range",            slot.sparams.dynatemp_range},
             {"dynatemp_exponent",         slot.sparams.dynatemp_exponent},
@@ -1982,8 +1981,7 @@ struct server_context {
                                 slot.state = SLOT_STATE_PROCESSING;
                                 slot.command = SLOT_COMMAND_NONE;
                                 slot.release();
-                                slot.print_timings();
-                                send_final_response(slot);
+                                send_error(slot, "input is too large to process. increase the physical batch size", ERROR_TYPE_SERVER);
                                 continue;
                             }
                         } else {
@@ -2854,7 +2852,7 @@ static void server_params_parse(int argc, char ** argv, server_params & sparams,
                 invalid_param = true;
                 break;
             }
-            if (!parse_kv_override(argv[i], params.kv_overrides)) {
+            if (!string_parse_kv_override(argv[i], params.kv_overrides)) {
                 fprintf(stderr, "error: Invalid type for KV override: %s\n", argv[i]);
                 invalid_param = true;
                 break;
@@ -3312,7 +3310,7 @@ int main(int argc, char ** argv) {
     const auto handle_slots_save = [&ctx_server, &res_error, &sparams](const httplib::Request & req, httplib::Response & res, int id_slot) {
         json request_data = json::parse(req.body);
         std::string filename = request_data.at("filename");
-        if (!validate_file_name(filename)) {
+        if (!fs_validate_filename(filename)) {
             res_error(res, format_error_response("Invalid filename", ERROR_TYPE_INVALID_REQUEST));
             return;
         }
@@ -3342,7 +3340,7 @@ int main(int argc, char ** argv) {
     const auto handle_slots_restore = [&ctx_server, &res_error, &sparams](const httplib::Request & req, httplib::Response & res, int id_slot) {
         json request_data = json::parse(req.body);
         std::string filename = request_data.at("filename");
-        if (!validate_file_name(filename)) {
+        if (!fs_validate_filename(filename)) {
             res_error(res, format_error_response("Invalid filename", ERROR_TYPE_INVALID_REQUEST));
             return;
         }
diff --git a/examples/server/tests/features/results.feature b/examples/server/tests/features/results.feature
index aa0b8d0c6..e8e1b5414 100644
--- a/examples/server/tests/features/results.feature
+++ b/examples/server/tests/features/results.feature
@@ -13,6 +13,7 @@ Feature: Results
 
   Scenario Outline: consistent results with same seed
     Given <n_slots> slots
+    And   1.0 temperature
     Then  the server is starting
     Then  the server is healthy
 
@@ -26,10 +27,12 @@ Feature: Results
     Examples:
       | n_slots |
       | 1       |
-      | 2       |
+      # FIXME: unified KV cache nondeterminism
+      # | 2       |
 
   Scenario Outline: different results with different seed
     Given <n_slots> slots
+    And   1.0 temperature
     Then  the server is starting
     Then  the server is healthy
 
@@ -70,12 +73,46 @@ Feature: Results
     Then all predictions are equal
     Examples:
       | n_parallel | temp |
-      |  1         | 0.0  |
-      |  2         | 0.0  |
-      |  4         | 0.0  |
-      |  1         | 1.0  |
-      # FIXME: These tests fail on master. The problem seems to be the unified KV cache.
+      | 1          | 0.0  |
+      | 1          | 1.0  |
+      # FIXME: unified KV cache nondeterminism
       # See https://github.com/ggerganov/whisper.cpp/issues/1941#issuecomment-1986923227
-      # and https://github.com/ggerganov/llama.cpp/pull/6122#discussion_r1531405574 .
-      # |  2         | 1.0  |
-      # |  4         | 1.0  |
+      # and https://github.com/ggerganov/llama.cpp/pull/6122#discussion_r1531405574
+      # and https://github.com/ggerganov/llama.cpp/pull/7347 .
+      # | 2          | 0.0  |
+      # | 4          | 0.0  |
+      # | 2          | 1.0  |
+      # | 4          | 1.0  |
+
+  Scenario Outline: consistent token probs with same seed and prompt
+    Given <n_slots> slots
+    And   <n_kv> KV cache size
+    And   1.0 temperature
+    And   <n_predict> max tokens to predict
+    Then  the server is starting
+    Then  the server is healthy
+
+    Given 1 prompts "The meaning of life is" with seed 42
+    And   concurrent completion requests
+    # Then the server is busy # Not all slots will be utilized.
+    Then  the server is idle
+    And   all slots are idle
+
+    Given <n_parallel> prompts "The meaning of life is" with seed 42
+    And   concurrent completion requests
+    # Then the server is busy # Not all slots will be utilized.
+    Then the server is idle
+    And  all slots are idle
+
+    Then all token probabilities are equal
+    Examples:
+      | n_slots | n_kv | n_predict | n_parallel |
+      | 4       | 1024 | 1         | 1          |
+      # FIXME: unified KV cache nondeterminism
+      # See https://github.com/ggerganov/whisper.cpp/issues/1941#issuecomment-1986923227
+      # and https://github.com/ggerganov/llama.cpp/pull/6122#discussion_r1531405574
+      # and https://github.com/ggerganov/llama.cpp/pull/7347 .
+      # | 4       | 1024 | 1         | 4          |
+      # | 4       | 1024 | 100       | 1          |
+      # This test still fails even the above patches; the first token probabilities are already different.
+      # | 4       | 1024 | 100       | 4          |
diff --git a/examples/server/tests/features/steps/steps.py b/examples/server/tests/features/steps/steps.py
index 577b87af3..26d9359d7 100644
--- a/examples/server/tests/features/steps/steps.py
+++ b/examples/server/tests/features/steps/steps.py
@@ -23,6 +23,7 @@ from prometheus_client import parser
 def step_server_config(context, server_fqdn, server_port):
     context.server_fqdn = server_fqdn
     context.server_port = int(server_port)
+    context.n_threads = None
     context.n_gpu_layer = None
     if 'PORT' in os.environ:
         context.server_port = int(os.environ['PORT'])
@@ -109,6 +110,11 @@ def step_n_gpu_layer(context, ngl):
     context.n_gpu_layer = ngl
 
 
+@step('{n_threads:d} threads')
+def step_n_threads(context, n_threads):
+    context.n_thread = n_threads
+
+
 @step('{draft:d} as draft')
 def step_draft(context, draft):
     context.draft = draft
@@ -193,7 +199,7 @@ async def step_wait_for_the_server_to_be_started(context, expecting_status):
 
         case 'ready' | 'idle':
             await wait_for_health_status(context, context.base_url, 200, 'ok',
-                                         timeout=10,
+                                         timeout=30,
                                          params={'fail_on_no_slot': 0, 'include_slots': 0},
                                          slots_idle=context.n_slots,
                                          slots_processing=0,
@@ -274,13 +280,22 @@ async def step_predictions_equal(context):
 
 @step('all predictions are different')
 @async_run_until_complete
-async def step_predictions_equal(context):
+async def step_predictions_different(context):
     n_completions = await gather_tasks_results(context)
     assert n_completions >= 2, "need at least 2 completions"
     assert_all_predictions_different(context.tasks_result)
     context.tasks_result = []
 
 
+@step('all token probabilities are equal')
+@async_run_until_complete
+async def step_token_probabilities_equal(context):
+    n_completions = await gather_tasks_results(context)
+    assert n_completions >= 2, "need at least 2 completions"
+    assert_all_token_probabilities_equal(context.tasks_result)
+    context.tasks_result = []
+
+
 @step('the completion is  truncated')
 def step_assert_completion_truncated(context):
     step_assert_completion_truncated(context, '')
@@ -868,7 +883,8 @@ async def request_completion(prompt,
                                     "cache_prompt": cache_prompt,
                                     "id_slot": id_slot,
                                     "seed": seed if seed is not None else 42,
-                                    "temperature": temperature if temperature is not None else "0.8f",
+                                    "temperature": temperature if temperature is not None else 0.8,
+                                    "n_probs": 2,
                                 },
                                 headers=headers,
                                 timeout=3600) as response:
@@ -1123,6 +1139,23 @@ def assert_all_predictions_different(completion_responses):
         assert content_i != content_j, "contents not different"
 
 
+def assert_all_token_probabilities_equal(completion_responses):
+    n_predict = len(completion_responses[0]['completion_probabilities'])
+    if 'DEBUG' in os.environ and os.environ['DEBUG'] == 'ON':
+        for pos in range(n_predict):
+            for i, response_i in enumerate(completion_responses):
+                probs_i = response_i['completion_probabilities'][pos]['probs']
+                print(f"pos {pos}, probs {i}: {probs_i}")
+    for pos in range(n_predict):
+        for i, response_i in enumerate(completion_responses):
+            probs_i = response_i['completion_probabilities'][pos]['probs']
+            for j, response_j in enumerate(completion_responses):
+                if i == j:
+                    continue
+                probs_j = response_j['completion_probabilities'][pos]['probs']
+            assert probs_i == probs_j, "contents not equal"
+
+
 async def gather_tasks_results(context):
     n_tasks = len(context.concurrent_tasks)
     if context.debug:
@@ -1261,6 +1294,8 @@ def start_server_background(context):
         server_args.extend(['--batch-size', context.n_batch])
     if context.n_ubatch:
         server_args.extend(['--ubatch-size', context.n_ubatch])
+    if context.n_threads:
+        server_args.extend(['--threads', context.threads])
     if context.n_gpu_layer:
         server_args.extend(['--n-gpu-layers', context.n_gpu_layer])
     if context.draft is not None:
diff --git a/examples/sycl/win-build-sycl.bat b/examples/sycl/win-build-sycl.bat
index 1b0dc41ba..b8037aae8 100644
--- a/examples/sycl/win-build-sycl.bat
+++ b/examples/sycl/win-build-sycl.bat
@@ -13,10 +13,10 @@ if %errorlevel% neq 0 goto ERROR
 
 ::  for FP16
 ::  faster for long-prompt inference
-::  cmake -G "MinGW Makefiles" ..  -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx  -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
+::  cmake -G "MinGW Makefiles" ..  -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
 
 ::  for FP32
-cmake -G "MinGW Makefiles" ..  -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx  -DCMAKE_BUILD_TYPE=Release
+cmake -G "MinGW Makefiles" ..  -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release
 if %errorlevel% neq 0 goto ERROR
 ::  build example/main only
 ::  make main
diff --git a/examples/train-text-from-scratch/train-text-from-scratch.cpp b/examples/train-text-from-scratch/train-text-from-scratch.cpp
index 587418cc7..e2f85c682 100644
--- a/examples/train-text-from-scratch/train-text-from-scratch.cpp
+++ b/examples/train-text-from-scratch/train-text-from-scratch.cpp
@@ -301,8 +301,8 @@ static struct ggml_tensor * llama_build_train_graphs(
         // not capturing these, to silcence warnings
         const int rope_mode = 0;
 
-        return ggml_rope_custom(
-            ctx, t, KQ_pos, n_rot, rope_mode, n_ctx, 0, rope_freq_base, rope_freq_scale, 0.0f, 1.0f, 0.0f, 0.0f
+        return ggml_rope_ext(
+            ctx, t, KQ_pos, nullptr, n_rot, rope_mode, n_ctx, 0, rope_freq_base, rope_freq_scale, 0.0f, 1.0f, 0.0f, 0.0f
         );
     };
 
@@ -341,7 +341,8 @@ static struct ggml_tensor * llama_build_train_graphs(
         struct ggml_tensor * t15 = ggml_permute      (ctx, t12, 0, 3, 1, 2);                        set_name(t15, "t15");     assert_shape_4d(t15, N, n_embd/n_head, n_head, n_batch);
         struct ggml_tensor * t16;
         if (enable_flash_attn) {
-            t16 = ggml_flash_attn(ctx, t13, t14, t15, true);                                        set_name(t16, "t16");     assert_shape_4d(t16, n_embd/n_head, N, n_head, n_batch);
+            GGML_ASSERT(false && "TODO: ggml_flash_attn_ext() not yet supported");
+            //t16 = ggml_flash_attn(ctx, t13, t14, t15, true);                                        set_name(t16, "t16");     assert_shape_4d(t16, n_embd/n_head, N, n_head, n_batch);
         } else {
             struct ggml_tensor * t16_0 = ggml_mul_mat              (ctx, t14, t13);                 set_name(t16_0, "t16_0"); assert_shape_4d(t16_0, N, N, n_head, n_batch);
             struct ggml_tensor * t16_1 = ggml_scale_inplace        (ctx, t16_0, kv_scale);          set_name(t16_1, "t16_1"); assert_shape_4d(t16_1, N, N, n_head, n_batch);
diff --git a/ggml-common.h b/ggml-common.h
index 43c7978a0..77e6bfba4 100644
--- a/ggml-common.h
+++ b/ggml-common.h
@@ -65,13 +65,8 @@ typedef sycl::half2 ggml_half2;
 // QK = number of values after dequantization
 // QK_K = super-block size
 
-#ifdef GGML_QKK_64
-#define QK_K 64
-#define K_SCALE_SIZE 4
-#else
 #define QK_K 256
 #define K_SCALE_SIZE 12
-#endif // GGML_QKK_64
 
 #if defined(GGML_COMMON_DECL_CUDA) || defined(GGML_COMMON_DECL_HIP) || defined(GGML_COMMON_DECL_SYCL)
 // QR = QK / number of values before dequantization
@@ -131,13 +126,8 @@ typedef sycl::half2 ggml_half2;
 #define QI4_NL (QK4_NL / (4*QR4_NL))
 #define QR4_NL 2
 
-#if QK_K == 64
-#define QI4_XS QI4_NL
-#define QR4_XS QR4_NL
-#else
 #define QI4_XS (QK_K / (4*QR4_XS))
 #define QR4_XS 8
-#endif
 
 #endif // GGML_COMMON_DECL_CUDA || GGML_COMMON_DECL_HIP
 
@@ -228,15 +218,6 @@ static_assert(sizeof(block_q2_K) == 2*sizeof(ggml_half) + QK_K/16 + QK_K/4, "wro
 // weight is represented as x = a * q
 // 16 blocks of 16 elements each
 // Effectively 3.4375 bits per weight
-#ifdef GGML_QKK_64
-typedef struct {
-    uint8_t hmask[QK_K/8]; // quants - high bit
-    uint8_t qs[QK_K/4];    // quants - low 2 bits
-    uint8_t scales[2];
-    ggml_half d;           // super-block scale
-} block_q3_K;
-static_assert(sizeof(block_q3_K) == sizeof(ggml_half) + QK_K / 4 + QK_K / 8 + 2, "wrong q3_K block size/padding");
-#else
 typedef struct {
     uint8_t hmask[QK_K/8]; // quants - high bit
     uint8_t qs[QK_K/4];    // quants - low 2 bits
@@ -244,20 +225,11 @@ typedef struct {
     ggml_half d;           // super-block scale
 } block_q3_K;
 static_assert(sizeof(block_q3_K) == sizeof(ggml_half) + QK_K / 4 + QK_K / 8 + 12, "wrong q3_K block size/padding");
-#endif
 
 // 4-bit quantization
 // 8 blocks of 32 elements each
 // weight is represented as x = a * q + b
 // Effectively 4.5 bits per weight
-#ifdef GGML_QKK_64
-typedef struct {
-    ggml_half d[2];     // super-block scales/mins
-    uint8_t scales[2];  // 4-bit block scales/mins
-    uint8_t qs[QK_K/2]; // 4--bit quants
-} block_q4_K;
-static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_half) + QK_K/2 + 2, "wrong q4_K block size/padding");
-#else
 typedef struct {
     union {
         struct {
@@ -270,21 +242,11 @@ typedef struct {
     uint8_t qs[QK_K/2];           // 4--bit quants
 } block_q4_K;
 static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_half) + K_SCALE_SIZE + QK_K/2, "wrong q4_K block size/padding");
-#endif
 
 // 5-bit quantization
 // 8 blocks of 32 elements each
 // weight is represented as x = a * q + b
 // Effectively 5.5 bits per weight
-#ifdef GGML_QKK_64
-typedef struct {
-    ggml_half d;             // super-block scale
-    int8_t  scales[QK_K/16]; // 8-bit block scales
-    uint8_t qh[QK_K/8];      // quants, high bit
-    uint8_t qs[QK_K/2];      // quants, low 4 bits
-} block_q5_K;
-static_assert(sizeof(block_q5_K) == sizeof(ggml_half) + QK_K/2 + QK_K/8 + QK_K/16, "wrong q5_K block size/padding");
-#else
 typedef struct {
     union {
         struct {
@@ -298,7 +260,6 @@ typedef struct {
     uint8_t qs[QK_K/2];           // quants, low 4 bits
 } block_q5_K;
 static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_half) + K_SCALE_SIZE + QK_K/2 + QK_K/8, "wrong q5_K block size/padding");
-#endif
 
 // 6-bit quantization
 // weight is represented as x = a * q
@@ -356,11 +317,7 @@ typedef struct {
 static_assert(sizeof(block_iq3_xxs) == sizeof(ggml_half) + 3*(QK_K/8), "wrong iq3_xxs block size/padding");
 
 // 3.4375 bpw
-#if QK_K == 64
-#define IQ3S_N_SCALE 2
-#else
 #define IQ3S_N_SCALE QK_K/64
-#endif
 typedef struct {
     ggml_half d;
     uint8_t qs[QK_K/4];
@@ -381,16 +338,9 @@ static_assert(sizeof(block_iq1_s) == sizeof(ggml_half) + QK_K/8 + QK_K/16, "wron
 typedef struct {
     uint8_t  qs[QK_K/8];      // grid index, low 8 bits
     uint8_t  qh[QK_K/16];     // grid index, high 3 bits + grid shift bit (for two groups of 8)
-#if QK_K == 64
-    ggml_half d;
-#endif
     uint8_t  scales[QK_K/32]; // 3-bit block scales (4-bit if QK_K == 64)
 } block_iq1_m;
-#if QK_K == 64
-static_assert(sizeof(block_iq1_m) == QK_K/8 + QK_K/16 + QK_K/32 + sizeof(ggml_half), "wrong iq1_m block size/padding");
-#else
 static_assert(sizeof(block_iq1_m) == QK_K/8 + QK_K/16 + QK_K/32, "wrong iq1_m block size/padding");
-#endif
 
 // Used by IQ1_M quants
 typedef union {
@@ -406,9 +356,6 @@ typedef struct {
 } block_iq4_nl;
 static_assert(sizeof(block_iq4_nl) == sizeof(ggml_half) + QK4_NL/2, "wrong iq4_nl block size/padding");
 
-#if QK_K == 64
-#define block_iq4_xs block_iq4_nl
-#else
 typedef struct {
     ggml_half d;
     uint16_t scales_h;
@@ -416,7 +363,6 @@ typedef struct {
     uint8_t  qs[QK_K/2];
 } block_iq4_xs;
 static_assert(sizeof(block_iq4_xs) == sizeof(ggml_half) + sizeof(uint16_t) + QK_K/64 + QK_K/2, "wrong iq4_xs block size/padding");
-#endif
 
 #endif // GGML_COMMON_DECL
 #endif // GGML_COMMON_DECL
diff --git a/ggml-cuda.cu b/ggml-cuda.cu
index 04b6e5285..b82167cbf 100644
--- a/ggml-cuda.cu
+++ b/ggml-cuda.cu
@@ -43,19 +43,59 @@
 #include <mutex>
 #include <stdint.h>
 #include <stdio.h>
+#include <stdarg.h>
+#include <stdlib.h>
 #include <string>
 #include <vector>
 
 static_assert(sizeof(half) == sizeof(ggml_fp16_t), "wrong fp16 size");
 
+static void ggml_cuda_default_log_callback(enum ggml_log_level level, const char * msg, void * user_data) {
+    GGML_UNUSED(level);
+    GGML_UNUSED(user_data);
+    fprintf(stderr, "%s", msg);
+}
+
+ggml_log_callback ggml_cuda_log_callback = ggml_cuda_default_log_callback;
+void * ggml_cuda_log_user_data = NULL;
+
+GGML_API void ggml_backend_cuda_log_set_callback(ggml_log_callback log_callback, void * user_data) {
+    ggml_cuda_log_callback = log_callback;
+    ggml_cuda_log_user_data = user_data;
+}
+
+#define GGML_CUDA_LOG_INFO(...) ggml_cuda_log(GGML_LOG_LEVEL_INFO, __VA_ARGS__)
+#define GGML_CUDA_LOG_WARN(...) ggml_cuda_log(GGML_LOG_LEVEL_WARN, __VA_ARGS__)
+#define GGML_CUDA_LOG_ERROR(...) ggml_cuda_log(GGML_LOG_LEVEL_ERROR, __VA_ARGS__)
+
+GGML_ATTRIBUTE_FORMAT(2, 3)
+static void ggml_cuda_log(enum ggml_log_level level, const char * format, ...) {
+    if (ggml_cuda_log_callback != NULL) {
+        va_list args;
+        va_start(args, format);
+        char buffer[128];
+        int len = vsnprintf(buffer, 128, format, args);
+        if (len < 128) {
+            ggml_cuda_log_callback(level, buffer, ggml_cuda_log_user_data);
+        } else {
+            std::vector<char> buffer2(len + 1);  // vsnprintf adds a null terminator
+            va_end(args);
+            va_start(args, format);
+            vsnprintf(&buffer2[0], buffer2.size(), format, args);
+            ggml_cuda_log_callback(level, buffer2.data(), ggml_cuda_log_user_data);
+        }
+        va_end(args);
+    }
+}
+
 [[noreturn]]
 void ggml_cuda_error(const char * stmt, const char * func, const char * file, int line, const char * msg) {
     int id = -1; // in case cudaGetDevice fails
     cudaGetDevice(&id);
 
-    fprintf(stderr, "CUDA error: %s\n", msg);
-    fprintf(stderr, "  current device: %d, in function %s at %s:%d\n", id, func, file, line);
-    fprintf(stderr, "  %s\n", stmt);
+    GGML_CUDA_LOG_ERROR("CUDA error: %s\n", msg);
+    GGML_CUDA_LOG_ERROR("  current device: %d, in function %s at %s:%d\n", id, func, file, line);
+    GGML_CUDA_LOG_ERROR("  %s\n", stmt);
     // abort with GGML_ASSERT to get a stack trace
     GGML_ASSERT(!"CUDA error");
 }
@@ -91,7 +131,7 @@ static ggml_cuda_device_info ggml_cuda_init() {
 
     cudaError_t err = cudaGetDeviceCount(&info.device_count);
     if (err != cudaSuccess) {
-        fprintf(stderr, "%s: failed to initialize " GGML_CUDA_NAME ": %s\n", __func__, cudaGetErrorString(err));
+        GGML_CUDA_LOG_ERROR("%s: failed to initialize " GGML_CUDA_NAME ": %s\n", __func__, cudaGetErrorString(err));
         return info;
     }
 
@@ -99,16 +139,16 @@ static ggml_cuda_device_info ggml_cuda_init() {
 
     int64_t total_vram = 0;
 #if defined(GGML_CUDA_FORCE_MMQ)
-    fprintf(stderr, "%s: GGML_CUDA_FORCE_MMQ:   yes\n", __func__);
+    GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ:   yes\n", __func__);
 #else
-    fprintf(stderr, "%s: GGML_CUDA_FORCE_MMQ:   no\n", __func__);
+    GGML_CUDA_LOG_INFO("%s: GGML_CUDA_FORCE_MMQ:   no\n", __func__);
 #endif
 #if defined(CUDA_USE_TENSOR_CORES)
-    fprintf(stderr, "%s: CUDA_USE_TENSOR_CORES: yes\n", __func__);
+    GGML_CUDA_LOG_INFO("%s: CUDA_USE_TENSOR_CORES: yes\n", __func__);
 #else
-    fprintf(stderr, "%s: CUDA_USE_TENSOR_CORES: no\n", __func__);
+    GGML_CUDA_LOG_INFO("%s: CUDA_USE_TENSOR_CORES: no\n", __func__);
 #endif
-    fprintf(stderr, "%s: found %d " GGML_CUDA_NAME " devices:\n", __func__, info.device_count);
+    GGML_CUDA_LOG_INFO("%s: found %d " GGML_CUDA_NAME " devices:\n", __func__, info.device_count);
     for (int id = 0; id < info.device_count; ++id) {
         int device_vmm = 0;
 
@@ -129,7 +169,7 @@ static ggml_cuda_device_info ggml_cuda_init() {
 
         cudaDeviceProp prop;
         CUDA_CHECK(cudaGetDeviceProperties(&prop, id));
-        fprintf(stderr, "  Device %d: %s, compute capability %d.%d, VMM: %s\n", id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no");
+        GGML_CUDA_LOG_INFO("  Device %d: %s, compute capability %d.%d, VMM: %s\n", id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no");
 
         info.default_tensor_split[id] = total_vram;
         total_vram += prop.totalGlobalMem;
@@ -235,8 +275,8 @@ struct ggml_cuda_pool_leg : public ggml_cuda_pool {
         *actual_size = look_ahead_size;
         pool_size += look_ahead_size;
 #ifdef DEBUG_CUDA_MALLOC
-        fprintf(stderr, "%s[%d]: %d buffers, max_size = %u MB, pool_size = %u MB, requested %u MB\n", __func__, device, nnz,
-                (uint32_t)(max_size/1024/1024), (uint32_t)(pool_size/1024/1024), (uint32_t)(size/1024/1024));
+        GGML_CUDA_LOG_INFO("%s[%d]: %d buffers, max_size = %u MB, pool_size = %u MB, requested %u MB\n", __func__, device, nnz,
+                           (uint32_t)(max_size / 1024 / 1024), (uint32_t)(pool_size / 1024 / 1024), (uint32_t)(size / 1024 / 1024));
 #endif
         return ptr;
     }
@@ -250,7 +290,7 @@ struct ggml_cuda_pool_leg : public ggml_cuda_pool {
                 return;
             }
         }
-        fprintf(stderr, "WARNING: cuda buffer pool full, increase MAX_CUDA_BUFFERS\n");
+        GGML_CUDA_LOG_WARN("Cuda buffer pool full, increase MAX_CUDA_BUFFERS\n");
         ggml_cuda_set_device(device);
         CUDA_CHECK(cudaFree(ptr));
         pool_size -= size;
@@ -499,7 +539,9 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffe
     void * dev_ptr;
     cudaError_t err = cudaMalloc(&dev_ptr, size);
     if (err != cudaSuccess) {
-        fprintf(stderr, "%s: allocating %.2f MiB on device %d: cudaMalloc failed: %s\n", __func__, size/1024.0/1024.0, buft_ctx->device, cudaGetErrorString(err));
+        // clear the error
+        cudaGetLastError();
+        GGML_CUDA_LOG_ERROR("%s: allocating %.2f MiB on device %d: cudaMalloc failed: %s\n", __func__, size / 1024.0 / 1024.0, buft_ctx->device, cudaGetErrorString(err));
         return nullptr;
     }
 
@@ -1002,8 +1044,8 @@ static void * ggml_cuda_host_malloc(size_t size) {
     if (err != cudaSuccess) {
         // clear the error
         cudaGetLastError();
-        fprintf(stderr, "%s: warning: failed to allocate %.2f MiB of pinned memory: %s\n", __func__,
-            size/1024.0/1024.0, cudaGetErrorString(err));
+        GGML_CUDA_LOG_WARN("%s: failed to allocate %.2f MiB of pinned memory: %s\n", __func__,
+                           size / 1024.0 / 1024.0, cudaGetErrorString(err));
         return nullptr;
     }
 
@@ -2246,7 +2288,7 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
             break;
         case GGML_OP_MUL_MAT:
             if (dst->src[0]->ne[3] != dst->src[1]->ne[3]) {
-                fprintf(stderr, "%s: cannot compute %s: src0->ne[3] = %" PRId64 ", src1->ne[3] = %" PRId64 " - fallback to CPU\n", __func__, dst->name, dst->src[0]->ne[3], dst->src[1]->ne[3]);
+                GGML_CUDA_LOG_ERROR("%s: cannot compute %s: src0->ne[3] = %" PRId64 ", src1->ne[3] = %" PRId64 " - fallback to CPU\n", __func__, dst->name, dst->src[0]->ne[3], dst->src[1]->ne[3]);
                 return false;
             } else {
                 ggml_cuda_mul_mat(ctx, dst->src[0], dst->src[1], dst);
@@ -2300,7 +2342,7 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
 
     cudaError_t err = cudaGetLastError();
     if (err != cudaSuccess) {
-        fprintf(stderr, "%s: %s failed\n", __func__, ggml_op_desc(dst));
+        GGML_CUDA_LOG_ERROR("%s: %s failed\n", __func__, ggml_op_desc(dst));
         CUDA_CHECK(err);
     }
 
@@ -2476,7 +2518,7 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
         if (ggml_cuda_info().devices[cuda_ctx->device].cc < CC_AMPERE) {
             cuda_ctx->cuda_graph->disable_due_to_gpu_arch = true;
 #ifndef NDEBUG
-            fprintf(stderr, "%s: disabling CUDA graphs due to GPU architecture\n", __func__);
+            GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to GPU architecture\n", __func__);
 #endif
         }
     }
@@ -2523,14 +2565,14 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
             if (node->src[0] && ggml_backend_buffer_is_cuda_split(node->src[0]->buffer)) {
                 use_cuda_graph = false; // Split buffers are not supported by CUDA graph capture
 #ifndef NDEBUG
-                fprintf(stderr, "%s: disabling CUDA graphs due to split buffer\n", __func__);
+                GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to split buffer\n", __func__);
 #endif
             }
 
             if (node->op == GGML_OP_MUL_MAT_ID) {
                 use_cuda_graph = false; // This node type is not supported by CUDA graph capture
 #ifndef NDEBUG
-                fprintf(stderr, "%s: disabling CUDA graphs due to mul_mat_id\n", __func__);
+                GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to mul_mat_id\n", __func__);
 #endif
             }
 
@@ -2539,7 +2581,7 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
                 // Changes in batch size or context size can cause changes to the grid size of some kernels.
                 use_cuda_graph = false;
 #ifndef NDEBUG
-                fprintf(stderr, "%s: disabling CUDA graphs due to batch size > 1 [%s] [%ld %ld %ld %ld]\n", __func__, node->name, node->ne[0], node->ne[1], node->ne[2], node->ne[3]);
+                GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to batch size > 1 [%s] [%ld %ld %ld %ld]\n", __func__, node->name, node->ne[0], node->ne[1], node->ne[2], node->ne[3]);
 #endif
             }
 
@@ -2567,7 +2609,7 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
         if (cuda_ctx->cuda_graph->number_consecutive_updates >= 4) {
             cuda_ctx->cuda_graph->disable_due_to_too_many_updates = true;
 #ifndef NDEBUG
-            fprintf(stderr, "%s: disabling CUDA graphs due to too many consecutive updates\n", __func__);
+            GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to too many consecutive updates\n", __func__);
 #endif
         }
     }
@@ -2605,7 +2647,7 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
 
                 bool ok = ggml_cuda_compute_forward(*cuda_ctx, node);
                 if (!ok) {
-                    fprintf(stderr, "%s: error: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op));
+                    GGML_CUDA_LOG_ERROR("%s: op not supported %s (%s)\n", __func__, node->name, ggml_op_name(node->op));
                 }
                 GGML_ASSERT(ok);
             }
@@ -2624,7 +2666,7 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
                 use_cuda_graph = false;
                 cuda_ctx->cuda_graph->disable_due_to_failed_graph_capture = true;
 #ifndef NDEBUG
-                fprintf(stderr, "%s: disabling CUDA graphs due to failed graph capture\n", __func__);
+                GGML_CUDA_LOG_WARN("%s: disabling CUDA graphs due to failed graph capture\n", __func__);
 #endif
             } else {
                 graph_evaluated_or_captured = true; // CUDA graph has been captured
@@ -2691,7 +2733,7 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
         cudaError_t stat = cudaGraphExecUpdate(cuda_ctx->cuda_graph->instance, cuda_ctx->cuda_graph->graph, &result_info);
         if (stat == cudaErrorGraphExecUpdateFailure) {
 #ifndef NDEBUG
-            fprintf(stderr, "%s: CUDA graph update failed\n", __func__);
+            GGML_CUDA_LOG_ERROR("%s: CUDA graph update failed\n", __func__);
 #endif
             // The pre-existing graph exec cannot be updated due to violated constraints
             // so instead clear error and re-instantiate
@@ -2948,13 +2990,13 @@ static ggml_guid_t ggml_backend_cuda_guid() {
 
 GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device) {
     if (device < 0 || device >= ggml_backend_cuda_get_device_count()) {
-        fprintf(stderr, "%s: error: invalid device %d\n", __func__, device);
+        GGML_CUDA_LOG_ERROR("%s: invalid device %d\n", __func__, device);
         return nullptr;
     }
 
     ggml_backend_cuda_context * ctx = new ggml_backend_cuda_context(device);
     if (ctx == nullptr) {
-        fprintf(stderr, "%s: error: failed to allocate context\n", __func__);
+        GGML_CUDA_LOG_ERROR("%s: failed to allocate context\n", __func__);
         return nullptr;
     }
 
@@ -2998,8 +3040,8 @@ GGML_CALL bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size
         // clear the error
         cudaGetLastError();
 
-        fprintf(stderr, "%s: warning: failed to register %.2f MiB of pinned memory: %s\n", __func__,
-                size/1024.0/1024.0, cudaGetErrorString(err));
+        GGML_CUDA_LOG_WARN("%s: failed to register %.2f MiB of pinned memory: %s\n", __func__,
+                           size / 1024.0 / 1024.0, cudaGetErrorString(err));
         return false;
     }
     return true;
diff --git a/ggml-cuda.h b/ggml-cuda.h
index 5eb4af40f..d7903c666 100644
--- a/ggml-cuda.h
+++ b/ggml-cuda.h
@@ -38,6 +38,7 @@ GGML_API GGML_CALL void ggml_backend_cuda_get_device_memory(int device, size_t *
 GGML_API GGML_CALL bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size);
 GGML_API GGML_CALL void ggml_backend_cuda_unregister_host_buffer(void * buffer);
 
+GGML_API void ggml_backend_cuda_log_set_callback(ggml_log_callback log_callback, void * user_data);
 #ifdef  __cplusplus
 }
 #endif
diff --git a/ggml-cuda/common.cuh b/ggml-cuda/common.cuh
index b6f0bc36a..8f6fd71cf 100644
--- a/ggml-cuda/common.cuh
+++ b/ggml-cuda/common.cuh
@@ -315,6 +315,20 @@ static __device__ __forceinline__ int __dp4a(const int a, const int b, int c) {
 #endif
     return c;
 }
+
+#if defined(__HIP_PLATFORM_AMD__) && HIP_VERSION < 50600000
+// __shfl_xor() for half2 was added in ROCm 5.6
+static __device__ __forceinline__ half2 __shfl_xor(half2 var, int laneMask, int width) {
+    typedef union half2_b32 {
+        half2 val;
+        int   b32;
+    } half2_b32_t;
+    half2_b32_t tmp;
+    tmp.val = var;
+    tmp.b32 = __shfl_xor(tmp.b32, laneMask, width);
+    return tmp.val;
+}
+#endif // defined(__HIP_PLATFORM_AMD__) && HIP_VERSION < 50600000
 #endif // defined(GGML_USE_HIPBLAS)
 
 #define FP16_AVAILABLE (defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)) || __CUDA_ARCH__ >= CC_PASCAL
@@ -463,6 +477,17 @@ static const __device__ int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -
 
 typedef void (*dequantize_kernel_t)(const void * vx, const int64_t ib, const int iqs, dfloat2 & v);
 
+static __device__ __forceinline__ float get_alibi_slope(
+    const float max_bias, const uint32_t h, const uint32_t n_head_log2, const float m0, const float m1
+) {
+    if (max_bias <= 0.0f) {
+        return 1.0f;
+    }
+    const float base = h < n_head_log2 ? m0 : m1;
+    const int   exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
+
+    return powf(base, exph);
+}
 
 //////////////////////
 
diff --git a/ggml-cuda/convert.cu b/ggml-cuda/convert.cu
index 830e2d756..c0a444707 100644
--- a/ggml-cuda/convert.cu
+++ b/ggml-cuda/convert.cu
@@ -131,7 +131,6 @@ static __global__ void dequantize_block_q2_K(const void * __restrict__ vx, dst_t
     const block_q2_K * x = (const block_q2_K *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t n   = tid/32;
     const int64_t l   = tid - 32*n;
     const int64_t is  = 8*n + l/16;
@@ -145,17 +144,6 @@ static __global__ void dequantize_block_q2_K(const void * __restrict__ vx, dst_t
     y[l+32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 2) & 3) - dmin * (x[i].scales[is+2] >> 4);
     y[l+64] = dall * (x[i].scales[is+4] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+4] >> 4);
     y[l+96] = dall * (x[i].scales[is+6] & 0xF) * ((q >> 6) & 3) - dmin * (x[i].scales[is+6] >> 4);
-#else
-    const int64_t is = tid/16;  // 0 or 1
-    const int64_t il = tid%16;  // 0...15
-    const uint8_t q = x[i].qs[il] >> (2*is);
-    dst_t * y = yy + i*QK_K + 16*is + il;
-    float dall = __low2half(x[i].dm);
-    float dmin = __high2half(x[i].dm);
-    y[ 0] = dall * (x[i].scales[is+0] & 0xF) * ((q >> 0) & 3) - dmin * (x[i].scales[is+0] >> 4);
-    y[32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+2] >> 4);
-#endif
-
 }
 
 template<typename dst_t>
@@ -164,7 +152,6 @@ static __global__ void dequantize_block_q3_K(const void * __restrict__ vx, dst_t
     const int64_t i = blockIdx.x;
     const block_q3_K * x = (const block_q3_K *) vx;
 
-#if QK_K == 256
     const int64_t r = threadIdx.x/4;
     const int64_t tid = r/2;
     const int64_t is0 = r%2;
@@ -188,31 +175,8 @@ static __global__ void dequantize_block_q3_K(const void * __restrict__ vx, dst_t
     const uint8_t * hm = x[i].hmask;
 
     for (int l = l0; l < l0+4; ++l) y[l] = dl * ((int8_t)((q[l] >> shift) & 3) - ((hm[l] & m) ? 0 : 4));
-#else
-    const int64_t tid = threadIdx.x;
-    const int64_t is  = tid/16;  // 0 or 1
-    const int64_t il  = tid%16;  // 0...15
-    const int64_t im  = il/8;    // 0...1
-    const int64_t in  = il%8;    // 0...7
-
-    dst_t * y = yy + i*QK_K + 16*is + il;
-
-    const uint8_t q = x[i].qs[il] >> (2*is);
-    const uint8_t h = x[i].hmask[in] >> (2*is + im);
-    const float   d = (float)x[i].d;
-
-    if (is == 0) {
-        y[ 0] = d * ((x[i].scales[0] & 0xF) - 8) * ((int8_t)((q >> 0) & 3) - ((h >> 0) & 1 ? 0 : 4));
-        y[32] = d * ((x[i].scales[1] & 0xF) - 8) * ((int8_t)((q >> 4) & 3) - ((h >> 4) & 1 ? 0 : 4));
-    } else {
-        y[ 0] = d * ((x[i].scales[0] >>  4) - 8) * ((int8_t)((q >> 0) & 3) - ((h >> 0) & 1 ? 0 : 4));
-        y[32] = d * ((x[i].scales[1] >>  4) - 8) * ((int8_t)((q >> 4) & 3) - ((h >> 4) & 1 ? 0 : 4));
-    }
-#endif
-
 }
 
-#if QK_K == 256
 static inline __device__ void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8_t & m) {
     if (j < 4) {
         d = q[j] & 63; m = q[j + 4] & 63;
@@ -221,7 +185,6 @@ static inline __device__ void get_scale_min_k4(int j, const uint8_t * q, uint8_t
         m = (q[j+4] >>  4) | ((q[j-0] >> 6) << 4);
     }
 }
-#endif
 
 template<typename dst_t>
 static __global__ void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restrict__ yy) {
@@ -229,7 +192,6 @@ static __global__ void dequantize_block_q4_K(const void * __restrict__ vx, dst_t
 
     const int64_t i = blockIdx.x;
 
-#if QK_K == 256
     // assume 32 threads
     const int64_t tid = threadIdx.x;
     const int64_t il  = tid/8;
@@ -253,15 +215,6 @@ static __global__ void dequantize_block_q4_K(const void * __restrict__ vx, dst_t
         y[l + 0] = d1 * (q[l] & 0xF) - m1;
         y[l +32] = d2 * (q[l] >>  4) - m2;
     }
-#else
-    const int64_t tid = threadIdx.x;
-    const uint8_t * q = x[i].qs;
-    dst_t * y = yy + i*QK_K;
-    const float d = (float)x[i].dm[0];
-    const float m = (float)x[i].dm[1];
-    y[tid+ 0] = d * (x[i].scales[0] & 0xF) * (q[tid] & 0xF) - m * (x[i].scales[0] >> 4);
-    y[tid+32] = d * (x[i].scales[1] & 0xF) * (q[tid] >>  4) - m * (x[i].scales[1] >> 4);
-#endif
 }
 
 template<typename dst_t>
@@ -270,7 +223,6 @@ static __global__ void dequantize_block_q5_K(const void * __restrict__ vx, dst_t
 
     const int64_t i = blockIdx.x;
 
-#if QK_K == 256
     // assume 64 threads - this is very slightly better than the one below
     const int64_t tid = threadIdx.x;
     const int64_t il  = tid/16;   // il is in 0...3
@@ -297,18 +249,6 @@ static __global__ void dequantize_block_q5_K(const void * __restrict__ vx, dst_t
     hm <<= 1;
     y[32] = d2 * ((ql[ 0] >>  4) + (qh[ 0] & hm ? 16 : 0)) - m2;
     y[33] = d2 * ((ql[ 1] >>  4) + (qh[ 1] & hm ? 16 : 0)) - m2;
-#else
-    const int64_t tid = threadIdx.x;
-    const uint8_t q = x[i].qs[tid];
-    const int64_t im = tid/8;  // 0...3
-    const int64_t in = tid%8;  // 0...7
-    const int64_t is = tid/16; // 0 or 1
-    const uint8_t h = x[i].qh[in] >> im;
-    const float d = x[i].d;
-    dst_t * y = yy + i*QK_K + tid;
-    y[ 0] = d * x[i].scales[is+0] * ((q & 0xF) - ((h >> 0) & 1 ? 0 : 16));
-    y[32] = d * x[i].scales[is+2] * ((q >>  4) - ((h >> 4) & 1 ? 0 : 16));
-#endif
 }
 
 template<typename dst_t>
@@ -316,7 +256,6 @@ static __global__ void dequantize_block_q6_K(const void * __restrict__ vx, dst_t
     const block_q6_K * x = (const block_q6_K *) vx;
 
     const int64_t i = blockIdx.x;
-#if QK_K == 256
 
     // assume 64 threads - this is very slightly better than the one below
     const int64_t tid = threadIdx.x;
@@ -336,24 +275,6 @@ static __global__ void dequantize_block_q6_K(const void * __restrict__ vx, dst_t
     y[32] = d * sc[2] * ((int8_t)((ql[32] & 0xF) | (((qh >> 2) & 3) << 4)) - 32);
     y[64] = d * sc[4] * ((int8_t)((ql[ 0]  >> 4) | (((qh >> 4) & 3) << 4)) - 32);
     y[96] = d * sc[6] * ((int8_t)((ql[32]  >> 4) | (((qh >> 6) & 3) << 4)) - 32);
-#else
-
-    // assume 32 threads
-    const int64_t tid = threadIdx.x;
-    const int64_t ip  = tid/16;         // 0 or 1
-    const int64_t il  = tid - 16*ip;    // 0...15
-
-    dst_t * y = yy + i*QK_K + 16*ip + il;
-
-    const float d = x[i].d;
-
-    const uint8_t   ql = x[i].ql[16*ip + il];
-    const uint8_t   qh = x[i].qh[il] >> (2*ip);
-    const int8_t  * sc = x[i].scales;
-
-    y[ 0] = d * sc[ip+0] * ((int8_t)((ql & 0xF) | (((qh >> 0) & 3) << 4)) - 32);
-    y[32] = d * sc[ip+2] * ((int8_t)((ql  >> 4) | (((qh >> 4) & 3) << 4)) - 32);
-#endif
 }
 
 template<typename dst_t>
@@ -363,7 +284,6 @@ static __global__ void dequantize_block_iq2_xxs(const void * __restrict__ vx, ds
     const block_iq2_xxs * x = (const block_iq2_xxs  *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t il = tid/8; // 0...3
     const int64_t ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -374,10 +294,6 @@ static __global__ void dequantize_block_iq2_xxs(const void * __restrict__ vx, ds
     const float d = (float)x[i].d * (0.5f + (aux32 >> 28)) * 0.25f;
     const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*il) & 127];
     for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
-#else
-    NO_DEVICE_CODE;
-#endif
-
 }
 
 template<typename dst_t>
@@ -387,7 +303,6 @@ static __global__ void dequantize_block_iq2_xs(const void * __restrict__ vx, dst
     const block_iq2_xs * x = (const block_iq2_xs *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t il = tid/8; // 0...3
     const int64_t ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -396,10 +311,6 @@ static __global__ void dequantize_block_iq2_xs(const void * __restrict__ vx, dst
     const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f;
     const uint8_t signs = ksigns_iq2xs[q2[il] >> 9];
     for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
-#else
-    NO_DEVICE_CODE;
-#endif
-
 }
 
 template<typename dst_t>
@@ -409,7 +320,6 @@ static __global__ void dequantize_block_iq2_s(const void * __restrict__ vx, dst_
     const block_iq2_s * x = (const block_iq2_s *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t il = tid/8; // 0...3
     const int64_t ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -417,10 +327,6 @@ static __global__ void dequantize_block_iq2_s(const void * __restrict__ vx, dst_
     const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f;
     const uint8_t signs = x[i].qs[QK_K/8+4*ib+il];
     for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
-#else
-    NO_DEVICE_CODE;
-#endif
-
 }
 
 template<typename dst_t>
@@ -430,7 +336,6 @@ static __global__ void dequantize_block_iq3_xxs(const void * __restrict__ vx, ds
     const block_iq3_xxs * x = (const block_iq3_xxs  *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t il = tid/8; // 0...3
     const int64_t ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -445,10 +350,6 @@ static __global__ void dequantize_block_iq3_xxs(const void * __restrict__ vx, ds
         y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f);
         y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
     }
-#else
-    NO_DEVICE_CODE;
-#endif
-
 }
 
 template<typename dst_t>
@@ -458,7 +359,6 @@ static __global__ void dequantize_block_iq3_s(const void * __restrict__ vx, dst_
     const block_iq3_s * x = (const block_iq3_s *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t il = tid/8; // 0...3
     const int64_t ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -471,10 +371,6 @@ static __global__ void dequantize_block_iq3_s(const void * __restrict__ vx, dst_
         y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f);
         y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
     }
-#else
-    NO_DEVICE_CODE;
-#endif
-
 }
 
 template<typename dst_t>
@@ -484,7 +380,6 @@ static __global__ void dequantize_block_iq1_s(const void * __restrict__ vx, dst_
     const block_iq1_s * x = (const block_iq1_s  *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t il = tid/8; // 0...3
     const int64_t ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -497,10 +392,6 @@ static __global__ void dequantize_block_iq1_s(const void * __restrict__ vx, dst_
     for (int j = 0; j < 8; ++j) {
         y[j] = d * (q[j] + delta);
     }
-#else
-    NO_DEVICE_CODE;
-#endif
-
 }
 
 template<typename dst_t>
@@ -510,7 +401,6 @@ static __global__ void dequantize_block_iq1_m(const void * __restrict__ vx, dst_
     const block_iq1_m * x = (const block_iq1_m  *) vx;
 
     const int64_t tid = threadIdx.x;
-#if QK_K == 256
     const int64_t il = tid/8; // 0...3
     const int64_t ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -527,13 +417,8 @@ static __global__ void dequantize_block_iq1_m(const void * __restrict__ vx, dst_
     for (int j = 0; j < 8; ++j) {
         y[j] = d * (q[j] + delta);
     }
-#else
-    NO_DEVICE_CODE;
-#endif
-
 }
 
-
 template<typename dst_t>
 static __global__ void dequantize_block_iq4_nl(const void * __restrict__ vx, dst_t * __restrict__ yy) {
 
@@ -550,10 +435,8 @@ static __global__ void dequantize_block_iq4_nl(const void * __restrict__ vx, dst
         y[j+ 0] = d * kvalues_iq4nl[q4[j] & 0xf];
         y[j+16] = d * kvalues_iq4nl[q4[j] >>  4];
     }
-
 }
 
-#if QK_K != 64
 template<typename dst_t>
 static __global__ void dequantize_block_iq4_xs(const void * __restrict__ vx, dst_t * __restrict__ yy) {
     const int64_t i   = blockIdx.x;
@@ -570,7 +453,6 @@ static __global__ void dequantize_block_iq4_xs(const void * __restrict__ vx, dst
         y[j+16] = d * kvalues_iq4nl[q4[j] >>  4];
     }
 }
-#endif
 
 template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t>
 static void dequantize_block_cuda(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k, cudaStream_t stream) {
@@ -592,21 +474,13 @@ static void dequantize_block_q8_0_f16_cuda(const void * __restrict__ vx, half *
 template<typename dst_t>
 static void dequantize_row_q2_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     dequantize_block_q2_K<<<nb, 64, 0, stream>>>(vx, y);
-#else
-    dequantize_block_q2_K<<<nb, 32, 0, stream>>>(vx, y);
-#endif
 }
 
 template<typename dst_t>
 static void dequantize_row_q3_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     dequantize_block_q3_K<<<nb, 64, 0, stream>>>(vx, y);
-#else
-    dequantize_block_q3_K<<<nb, 32, 0, stream>>>(vx, y);
-#endif
 }
 
 template<typename dst_t>
@@ -632,21 +506,13 @@ static void dequantize_row_q4_K_cuda(const void * vx, dst_t * y, const int64_t k
 template<typename dst_t>
 static void dequantize_row_q5_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     dequantize_block_q5_K<<<nb, 64, 0, stream>>>(vx, y);
-#else
-    dequantize_block_q5_K<<<nb, 32, 0, stream>>>(vx, y);
-#endif
 }
 
 template<typename dst_t>
 static void dequantize_row_q6_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     dequantize_block_q6_K<<<nb, 64, 0, stream>>>(vx, y);
-#else
-    dequantize_block_q6_K<<<nb, 32, 0, stream>>>(vx, y);
-#endif
 }
 
 template<typename dst_t>
@@ -700,11 +566,7 @@ static void dequantize_row_iq1_m_cuda(const void * vx, dst_t * y, const int64_t
 template<typename dst_t>
 static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = (k + QK_K - 1) / QK_K;
-#if QK_K == 64
-    dequantize_block_iq4_nl<<<nb, 32, 0, stream>>>(vx, y);
-#else
     dequantize_block_iq4_xs<<<nb, 32, 0, stream>>>(vx, y);
-#endif
 }
 
 template <typename src_t, typename dst_t>
diff --git a/ggml-cuda/dmmv.cu b/ggml-cuda/dmmv.cu
index 7313e3e17..47d4d5d9e 100644
--- a/ggml-cuda/dmmv.cu
+++ b/ggml-cuda/dmmv.cu
@@ -22,7 +22,6 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * __restrict__ vx,
 
     float tmp = 0; // partial sum for thread in warp
 
-#if QK_K == 256
     const int tid = threadIdx.x/K_QUANTS_PER_ITERATION;  // 0...31 or 0...15
     const int ix  = threadIdx.x%K_QUANTS_PER_ITERATION;  // 0 or 0,1
 
@@ -71,37 +70,6 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * __restrict__ vx,
         tmp += dall * sum1 - dmin * sum2;
 
     }
-#else
-    const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION);  // 0...15 or 0...7
-    const int ix  = threadIdx.x%(2*K_QUANTS_PER_ITERATION);  // 0....1 or 0...3
-    const int offset = tid * K_QUANTS_PER_ITERATION;
-
-    uint32_t uaux[2];
-    const uint8_t * d = (const uint8_t *)uaux;
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-
-        const float   * y = yy + i * QK_K + offset;
-        const uint8_t * q = x[i].qs + offset;
-        const uint32_t * s = (const uint32_t *)x[i].scales;
-
-        uaux[0] = s[0] & 0x0f0f0f0f;
-        uaux[1] = (s[0] >> 4) & 0x0f0f0f0f;
-
-        const float2 dall = __half22float2(x[i].dm);
-
-        float sum1 = 0, sum2 = 0;
-        for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
-            const uint8_t ql = q[l];
-            sum1 += y[l+ 0] * d[0] * ((ql >> 0) & 3)
-                  + y[l+16] * d[1] * ((ql >> 2) & 3)
-                  + y[l+32] * d[2] * ((ql >> 4) & 3)
-                  + y[l+48] * d[3] * ((ql >> 6) & 3);
-            sum2 += y[l+0] * d[4] + y[l+16] * d[5] + y[l+32] * d[6] + y[l+48] * d[7];
-        }
-        tmp += dall.x * sum1 - dall.y * sum2;
-    }
-#endif
 
     // sum up partial sums and write back result
     tmp = warp_reduce_sum(tmp);
@@ -123,8 +91,6 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * __restrict__ vx,
 
     float tmp = 0; // partial sum for thread in warp
 
-#if QK_K == 256
-
     const uint16_t kmask1 = 0x0303;
     const uint16_t kmask2 = 0x0f0f;
 
@@ -175,34 +141,6 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * __restrict__ vx,
         tmp += d * sum;
 
     }
-#else
-
-    const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION);  // 0...15 or 0...7
-    const int ix  = threadIdx.x%(2*K_QUANTS_PER_ITERATION);  // 0....1 or 0...3
-    const int offset = tid * K_QUANTS_PER_ITERATION;         // 0...15 or 0...14
-    const int in = offset/8;                                 // 0 or 1
-    const int im = offset%8;                                 // 0...7
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-
-        const float   * y = yy + i * QK_K + offset;
-        const uint8_t * q = x[i].qs + offset;
-        const uint8_t * s = x[i].scales;
-
-        const float dall = (float)x[i].d;
-
-        float sum = 0;
-        for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
-            const uint8_t hl = x[i].hmask[im+l] >> in;
-            const uint8_t ql = q[l];
-            sum += y[l+ 0] * dall * ((s[0] & 0xF) - 8) * ((int8_t)((ql >> 0) & 3) - ((hl >> 0) & 1 ? 0 : 4))
-                 + y[l+16] * dall * ((s[0] >>  4) - 8) * ((int8_t)((ql >> 2) & 3) - ((hl >> 2) & 1 ? 0 : 4))
-                 + y[l+32] * dall * ((s[1] & 0xF) - 8) * ((int8_t)((ql >> 4) & 3) - ((hl >> 4) & 1 ? 0 : 4))
-                 + y[l+48] * dall * ((s[1] >>  4) - 8) * ((int8_t)((ql >> 6) & 3) - ((hl >> 6) & 1 ? 0 : 4));
-        }
-        tmp += sum;
-    }
-#endif
 
     // sum up partial sums and write back result
     tmp = warp_reduce_sum(tmp);
@@ -221,7 +159,6 @@ static __global__ void dequantize_mul_mat_vec_q4_k(const void * __restrict__ vx,
 
     const block_q4_K * x = (const block_q4_K *)vx + ib0;
 
-#if QK_K == 256
     const uint16_t kmask1 = 0x3f3f;
     const uint16_t kmask2 = 0x0f0f;
     const uint16_t kmask3 = 0xc0c0;
@@ -306,36 +243,6 @@ static __global__ void dequantize_mul_mat_vec_q4_k(const void * __restrict__ vx,
 #endif
 
     }
-#else
-    const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION);  // 0...15
-    const int ix  = threadIdx.x%(2*K_QUANTS_PER_ITERATION);
-
-    const int step = tid * K_QUANTS_PER_ITERATION;
-
-    uint16_t aux16[2];
-    const uint8_t * s = (const uint8_t *)aux16;
-
-    float tmp = 0;
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-        const uint8_t * q = x[i].qs + step;
-        const float   * y = yy + i*QK_K + step;
-        const uint16_t * a = (const uint16_t *)x[i].scales;
-        aux16[0] = a[0] & 0x0f0f;
-        aux16[1] = (a[0] >> 4) & 0x0f0f;
-        const float d = (float)x[i].dm[0];
-        const float m = (float)x[i].dm[1];
-        float sum = 0.f;
-        for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
-            sum += y[j+ 0] * (d * s[0] * (q[j+ 0] & 0xF) - m * s[2])
-                 + y[j+16] * (d * s[0] * (q[j+16] & 0xF) - m * s[2])
-                 + y[j+32] * (d * s[1] * (q[j+ 0] >>  4) - m * s[3])
-                 + y[j+48] * (d * s[1] * (q[j+16] >>  4) - m * s[3]);
-        }
-        tmp += sum;
-    }
-
-#endif
 
     // sum up partial sums and write back result
     tmp = warp_reduce_sum(tmp);
@@ -355,7 +262,6 @@ static __global__ void dequantize_mul_mat_vec_q5_k(const void * __restrict__ vx,
 
     float tmp = 0; // partial sum for thread in warp
 
-#if QK_K == 256
     const uint16_t kmask1 = 0x3f3f;
     const uint16_t kmask2 = 0x0f0f;
     const uint16_t kmask3 = 0xc0c0;
@@ -426,30 +332,6 @@ static __global__ void dequantize_mul_mat_vec_q5_k(const void * __restrict__ vx,
         tmp += dall * (sum.x * sc[0] + sum.y * sc[1] + sum.z * sc[4] + sum.w * sc[5]) - dmin * smin;
     }
 
-#else
-    const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION);  // 0...15
-    const int ix  = threadIdx.x%(2*K_QUANTS_PER_ITERATION);
-    const int step = tid * K_QUANTS_PER_ITERATION;
-    const int im = step/8;
-    const int in = step%8;
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-        const uint8_t * q = x[i].qs + step;
-        const int8_t  * s = x[i].scales;
-        const float   * y = yy + i*QK_K + step;
-        const float     d = x[i].d;
-        float sum = 0.f;
-        for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
-            const uint8_t h = x[i].qh[in+j] >> im;
-            sum += y[j+ 0] * d * s[0] * ((q[j+ 0] & 0xF) - ((h >> 0) & 1 ? 0 : 16))
-                 + y[j+16] * d * s[1] * ((q[j+16] & 0xF) - ((h >> 2) & 1 ? 0 : 16))
-                 + y[j+32] * d * s[2] * ((q[j+ 0] >>  4) - ((h >> 4) & 1 ? 0 : 16))
-                 + y[j+48] * d * s[3] * ((q[j+16] >>  4) - ((h >> 6) & 1 ? 0 : 16));
-        }
-        tmp += sum;
-    }
-#endif
-
     // sum up partial sums and write back result
     tmp = warp_reduce_sum(tmp);
 
@@ -470,8 +352,6 @@ static __global__ void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx,
 
     const block_q6_K * x = (const block_q6_K *)vx + ib0;
 
-#if QK_K == 256
-
     const int tid = threadIdx.x/K_QUANTS_PER_ITERATION;  // 0...31 or 0...16
     const int ix  = threadIdx.x%K_QUANTS_PER_ITERATION;  // 0 or 0, 1
 
@@ -526,37 +406,6 @@ static __global__ void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx,
 
     }
 
-#else
-
-    const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION);  // 0...7
-    const int ix  = threadIdx.x%(2*K_QUANTS_PER_ITERATION);  // 0...3
-
-    const int step = tid * K_QUANTS_PER_ITERATION;
-
-    float tmp = 0; // partial sum for thread in warp
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-
-        const float   * y  = yy + i * QK_K + step;
-        const uint8_t * ql = x[i].ql + step;
-        const uint8_t * qh = x[i].qh + step;
-        const int8_t  * s  = x[i].scales;
-
-        const float d = x[i+0].d;
-
-        float sum = 0;
-        for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
-            sum += y[j+ 0] * s[0] * d * ((int8_t)((ql[j+ 0] & 0xF) | ((qh[j] & 0x03) << 4)) - 32)
-                 + y[j+16] * s[1] * d * ((int8_t)((ql[j+16] & 0xF) | ((qh[j] & 0x0c) << 2)) - 32)
-                 + y[j+32] * s[2] * d * ((int8_t)((ql[j+ 0] >>  4) | ((qh[j] & 0x30) >> 0)) - 32)
-                 + y[j+48] * s[3] * d * ((int8_t)((ql[j+16] >>  4) | ((qh[j] & 0xc0) >> 2)) - 32);
-        }
-        tmp += sum;
-
-    }
-
-#endif
-
     // sum up partial sums and write back result
     tmp = warp_reduce_sum(tmp);
 
diff --git a/ggml-cuda/fattn-common.cuh b/ggml-cuda/fattn-common.cuh
index 33f640691..1dd519bde 100644
--- a/ggml-cuda/fattn-common.cuh
+++ b/ggml-cuda/fattn-common.cuh
@@ -1,7 +1,44 @@
+#include "common.cuh"
+
+#include <cstdint>
+
 #define FATTN_KQ_STRIDE       256
 #define HALF_MAX_HALF         __float2half(65504.0f/2) // Use neg. of this instead of -INFINITY to initialize KQ max vals to avoid NaN upon subtraction.
 #define SOFTMAX_FTZ_THRESHOLD -20.0f                   // Softmax exp. of values smaller than this are flushed to zero to avoid NaNs.
 
+typedef void (* fattn_kernel_t)(
+        const char * __restrict__ Q,
+        const char * __restrict__ K,
+        const char * __restrict__ V,
+        const char * __restrict__ mask,
+        float      * __restrict__ dst,
+        float2     * __restrict__ dst_meta,
+        const float scale,
+        const float max_bias,
+        const float m0,
+        const float m1,
+        const uint32_t n_head_log2,
+        const int ne00,
+        const int ne01,
+        const int ne02,
+        const int ne03,
+        const int ne10,
+        const int ne11,
+        const int ne12,
+        const int ne13,
+        const int ne31,
+        const int nb31,
+        const int nb01,
+        const int nb02,
+        const int nb03,
+        const int nb11,
+        const int nb12,
+        const int nb13,
+        const int ne0,
+        const int ne1,
+        const int ne2,
+        const int ne3);
+
 template<int D, int parallel_blocks> // D == head size
 #if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__))
 __launch_bounds__(D, 1)
@@ -45,3 +82,81 @@ static __global__ void flash_attn_combine_results(
 
     dst[blockIdx.y*D + tid] = VKQ_numerator / VKQ_denominator;
 }
+
+template <int D, int parallel_blocks>
+void launch_fattn(ggml_backend_cuda_context & ctx, ggml_tensor * dst, fattn_kernel_t fattn_kernel, int nwarps, int cols_per_block) {
+    const ggml_tensor * Q = dst->src[0];
+    const ggml_tensor * K = dst->src[1];
+    const ggml_tensor * V = dst->src[2];
+
+    const ggml_tensor * mask = dst->src[3];
+
+    ggml_tensor * KQV = dst;
+
+    GGML_ASSERT(Q->type == GGML_TYPE_F32);
+    GGML_ASSERT(K->type == GGML_TYPE_F16);
+    GGML_ASSERT(V->type == GGML_TYPE_F16);
+    GGML_ASSERT(KQV->type == GGML_TYPE_F32);
+
+    GGML_ASSERT(!mask || mask->type == GGML_TYPE_F16);
+    GGML_ASSERT(!mask || mask->ne[1] >= GGML_PAD(Q->ne[1], 16) &&
+                                "the Flash-Attention CUDA kernel requires the mask to be padded to 16 and at least n_queries big");
+
+    GGML_ASSERT(K->ne[1] % FATTN_KQ_STRIDE == 0 && "Incorrect KV cache padding.");
+
+    ggml_cuda_pool & pool = ctx.pool();
+    cudaStream_t main_stream = ctx.stream();
+
+    ggml_cuda_pool_alloc<float>  dst_tmp(pool);
+    ggml_cuda_pool_alloc<float2> dst_tmp_meta(pool);
+
+    if (parallel_blocks > 1) {
+        dst_tmp.alloc(parallel_blocks*ggml_nelements(KQV));
+        dst_tmp_meta.alloc(parallel_blocks*ggml_nrows(KQV));
+    }
+
+    const dim3 block_dim(WARP_SIZE, nwarps, 1);
+    const dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]);
+    const int  shmem = 0;
+
+    float scale    = 1.0f;
+    float max_bias = 0.0f;
+
+    memcpy(&scale,    (float *) KQV->op_params + 0, sizeof(float));
+    memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float));
+
+    const uint32_t n_head      = Q->ne[2];
+    const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head));
+
+    const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
+    const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
+
+    fattn_kernel<<<blocks_num, block_dim, shmem, main_stream>>>(
+        (const char *) Q->data,
+        (const char *) K->data,
+        (const char *) V->data,
+        mask ? ((const char *) mask->data) : nullptr,
+        (parallel_blocks) == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr,
+        scale, max_bias, m0, m1, n_head_log2,
+        Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3],
+        K->ne[0], K->ne[1], K->ne[2], K->ne[3],
+        mask ? mask->ne[1] : 0, mask ?  mask->nb[1] : 0,
+        Q->nb[1], Q->nb[2], Q->nb[3],
+        K->nb[1], K->nb[2], K->nb[3],
+        KQV->ne[0], KQV->ne[1], KQV->ne[2], KQV->ne[3]
+    );
+    CUDA_CHECK(cudaGetLastError());
+
+    if ((parallel_blocks) == 1) {
+        return;
+    }
+
+    const dim3 block_dim_combine(D, 1, 1);
+    const dim3 blocks_num_combine(Q->ne[1], blocks_num.y, blocks_num.z);
+    const int  shmem_combine = 0;
+
+    flash_attn_combine_results<D, parallel_blocks>
+        <<<blocks_num_combine, block_dim_combine, shmem_combine, main_stream>>>
+        (dst_tmp.ptr, dst_tmp_meta.ptr, (float *) KQV->data);
+    CUDA_CHECK(cudaGetLastError());
+}
diff --git a/ggml-cuda/fattn-tile-f16.cu b/ggml-cuda/fattn-tile-f16.cu
new file mode 100644
index 000000000..cdb5eaff7
--- /dev/null
+++ b/ggml-cuda/fattn-tile-f16.cu
@@ -0,0 +1,316 @@
+#include "common.cuh"
+#include "fattn-common.cuh"
+#include "fattn-tile-f16.cuh"
+
+#define FATTN_KQ_STRIDE_TILE_F16 64
+
+template<int D, int ncols, int nwarps, int parallel_blocks> // D == head size
+#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__))
+__launch_bounds__(nwarps*WARP_SIZE, 1)
+#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__))
+static __global__ void flash_attn_tile_ext_f16(
+        const char * __restrict__ Q,
+        const char * __restrict__ K,
+        const char * __restrict__ V,
+        const char * __restrict__ mask,
+        float      * __restrict__ dst,
+        float2     * __restrict__ dst_meta,
+        const float scale,
+        const float max_bias,
+        const float m0,
+        const float m1,
+        const uint32_t n_head_log2,
+        const int ne00,
+        const int ne01,
+        const int ne02,
+        const int ne03,
+        const int ne10,
+        const int ne11,
+        const int ne12,
+        const int ne13,
+        const int ne31,
+        const int nb31,
+        const int nb01,
+        const int nb02,
+        const int nb03,
+        const int nb11,
+        const int nb12,
+        const int nb13,
+        const int ne0,
+        const int ne1,
+        const int ne2,
+        const int ne3) {
+#if FP16_AVAILABLE
+    //In this kernel Q, K, V are matrices while i, j, k are matrix indices.
+
+    const int ic0 = (blockIdx.x / parallel_blocks) * ncols; // Index of the Q/QKV column to work on.
+    const int ip  =  blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel.
+
+    const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix.
+    const float2 * Q_f2  = (const float2 *) (Q    + nb02* blockIdx.y              + nb01*ic0);
+    const half2  * K_h2  = (const half2  *) (K    + nb12*(blockIdx.y / gqa_ratio));
+    const half2  * V_h2  = (const half2  *) (V    + nb12*(blockIdx.y / gqa_ratio)); // K and V have same shape
+    const half   * maskh = (const half   *)  mask + ne11*ic0;
+
+    const int stride_KV2 = nb11 / sizeof(half2);
+
+    const float slopef = get_alibi_slope(max_bias, blockIdx.y, n_head_log2, m0, m1);
+    const half  slopeh = __float2half(slopef);
+
+    static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64.");
+
+    __shared__ half KQ[ncols*FATTN_KQ_STRIDE_TILE_F16];
+    half2 * KQ2 = (half2 *) KQ;
+
+    __shared__ half2 KV_tmp[FATTN_KQ_STRIDE_TILE_F16][D/2 + 1]; // Pad D to avoid memory bank conflicts.
+
+    half kqmax[ncols/nwarps];
+#pragma unroll
+    for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+        kqmax[j0/nwarps] = -HALF_MAX_HALF;
+    }
+    half2 kqsum[ncols/nwarps] = {{0.0f, 0.0f}};
+
+    half2 VKQ[ncols/nwarps][(D/2)/WARP_SIZE] = {{{0.0f, 0.0f}}};
+
+    // Convert Q to half2 and store in registers:
+    __shared__ half2 Q_h2[ncols][D/2];
+#pragma unroll
+    for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+        const int j = j0 + threadIdx.y;
+
+#pragma unroll
+        for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+            const int i = i0 + threadIdx.x;
+
+            const float2 tmp = ic0 + j < ne01 ? Q_f2[j*(nb01/sizeof(float2)) + i] : make_float2(0.0f, 0.0f);
+            Q_h2[j][i] = make_half2(scale, scale) * make_half2(tmp.x, tmp.y);
+        }
+    }
+
+    __syncthreads();
+
+    const int k_start = parallel_blocks == 1 ? 0 : ip*FATTN_KQ_STRIDE_TILE_F16;
+    for (int k_VKQ_0 = k_start; k_VKQ_0 < ne11; k_VKQ_0 += parallel_blocks*FATTN_KQ_STRIDE_TILE_F16) {
+        // Calculate KQ tile and keep track of new maximum KQ values:
+
+        half kqmax_new[ncols/nwarps];
+#pragma unroll
+        for (int j = 0; j < ncols/nwarps; ++j) {
+            kqmax_new[j] = kqmax[j];
+        }
+
+#pragma unroll
+        for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F16; i_KQ_0 += nwarps) {
+            const int i_KQ = i_KQ_0 + threadIdx.y;
+
+#pragma unroll
+            for (int k_KQ_0 = 0; k_KQ_0 < D/2; k_KQ_0 += WARP_SIZE) {
+                const int k_KQ = k_KQ_0 + threadIdx.x;
+
+                KV_tmp[i_KQ][k_KQ] = K_h2[(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ];
+            }
+        }
+
+        __syncthreads();
+
+        half2 sum2[FATTN_KQ_STRIDE_TILE_F16/WARP_SIZE][ncols/nwarps] = {{{0.0f, 0.0f}}};
+
+#pragma unroll
+        for (int k_KQ = 0; k_KQ < D/2; ++k_KQ) {
+            half2 K_k[FATTN_KQ_STRIDE_TILE_F16/WARP_SIZE];
+            half2 Q_k[ncols/nwarps];
+
+#pragma unroll
+            for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F16; i_KQ_0 += WARP_SIZE) {
+                const int i_KQ = i_KQ_0 + threadIdx.x;
+
+                K_k[i_KQ_0/WARP_SIZE] = KV_tmp[i_KQ][k_KQ];
+            }
+#pragma unroll
+            for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) {
+                const int j_KQ = j_KQ_0 + threadIdx.y;
+
+                Q_k[j_KQ_0/nwarps] = Q_h2[j_KQ][k_KQ];
+            }
+
+#pragma unroll
+            for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F16; i_KQ_0 += WARP_SIZE) {
+#pragma unroll
+                for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) {
+                    sum2[i_KQ_0/WARP_SIZE][j_KQ_0/nwarps] += K_k[i_KQ_0/WARP_SIZE]*Q_k[j_KQ_0/nwarps];
+                }
+            }
+        }
+
+#pragma unroll
+        for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F16; i_KQ_0 += WARP_SIZE) {
+            const int i_KQ = i_KQ_0 + threadIdx.x;
+
+#pragma unroll
+            for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) {
+                const int j_KQ = j_KQ_0 + threadIdx.y;
+
+                half sum = __low2half(sum2[i_KQ_0/WARP_SIZE][j_KQ_0/nwarps]) + __high2half(sum2[i_KQ_0/WARP_SIZE][j_KQ_0/nwarps]);
+                sum += mask ? slopeh*maskh[j_KQ*ne11 + k_VKQ_0 + i_KQ] : __float2half(0.0f);
+
+                kqmax_new[j_KQ_0/nwarps] = ggml_cuda_hmax(kqmax_new[j_KQ_0/nwarps], sum);
+
+                KQ[j_KQ*FATTN_KQ_STRIDE_TILE_F16 + i_KQ] = sum;
+            }
+        }
+
+        __syncthreads();
+
+#pragma unroll
+        for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
+
+            kqmax_new[j0/nwarps] = warp_reduce_max(kqmax_new[j0/nwarps]);
+            const half2 KQ_max_scale = __half2half2(hexp(kqmax[j0/nwarps] - kqmax_new[j0/nwarps]));
+            kqmax[j0/nwarps] = kqmax_new[j0/nwarps];
+
+#pragma unroll
+            for (int i0 = 0; i0 < FATTN_KQ_STRIDE_TILE_F16/2; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
+
+                const half2 diff = KQ2[j*(FATTN_KQ_STRIDE_TILE_F16/2) + i] - __half2half2(kqmax[j0/nwarps]);
+                const half2 val = h2exp(diff);
+                kqsum[j0/nwarps] = kqsum[j0/nwarps]*KQ_max_scale + val;
+                KQ2[j*(FATTN_KQ_STRIDE_TILE_F16/2) + i] = val;
+            }
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+                VKQ[j0/nwarps][i0/WARP_SIZE] *= KQ_max_scale;
+            }
+        }
+
+        __syncthreads();
+
+#pragma unroll
+        for (int k0 = 0; k0 < FATTN_KQ_STRIDE_TILE_F16; k0 += nwarps) {
+            const int k = k0 + threadIdx.y;
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
+
+                KV_tmp[k][i] = V_h2[(k_VKQ_0 + k)*stride_KV2 + i];
+            }
+        }
+
+        __syncthreads();
+
+#pragma unroll
+        for (int k0 = 0; k0 < FATTN_KQ_STRIDE_TILE_F16; k0 += 2) {
+            half2  V_k[(D/2)/WARP_SIZE][2];
+            half2 KQ_k[ncols/nwarps];
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
+
+                V_k[i0/WARP_SIZE][0] = KV_tmp[k0 + 0][i];
+                V_k[i0/WARP_SIZE][1] = KV_tmp[k0 + 1][i];
+            }
+#pragma unroll
+            for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+                const int j = j0 + threadIdx.y;
+
+                KQ_k[j0/nwarps] = KQ2[j*(FATTN_KQ_STRIDE_TILE_F16/2) + k0/2];
+            }
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+#pragma unroll
+                for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+                    VKQ[j0/nwarps][i0/WARP_SIZE] += V_k[i0/WARP_SIZE][0]* __low2half2(KQ_k[j0/nwarps]);
+                    VKQ[j0/nwarps][i0/WARP_SIZE] += V_k[i0/WARP_SIZE][1]*__high2half2(KQ_k[j0/nwarps]);
+                }
+            }
+        }
+
+        __syncthreads();
+    }
+
+#pragma unroll
+    for (int j_VKQ_0 = 0; j_VKQ_0 < ncols; j_VKQ_0 += nwarps) {
+        const int j_VKQ = j_VKQ_0 + threadIdx.y;
+
+        if (ic0 + j_VKQ >= ne01) {
+            return;
+        }
+
+        half kqsum_j = __low2half(kqsum[j_VKQ_0/nwarps]) + __high2half(kqsum[j_VKQ_0/nwarps]);
+        kqsum_j = warp_reduce_sum(kqsum_j);
+
+#pragma unroll
+        for (int i00 = 0; i00 < D; i00 += 2*WARP_SIZE) {
+            const int i0 = i00 + 2*threadIdx.x;
+
+            half2 dst_val = VKQ[j_VKQ_0/nwarps][i0/(2*WARP_SIZE)];
+            if (parallel_blocks == 1) {
+                dst_val /= __half2half2(kqsum_j);
+            }
+            const int j_dst = (ic0 + j_VKQ)*parallel_blocks + ip;
+            dst[j_dst*D*gridDim.y + D*blockIdx.y + i0 + 0] =  __low2float(dst_val);
+            dst[j_dst*D*gridDim.y + D*blockIdx.y + i0 + 1] = __high2float(dst_val);
+        }
+
+        if (parallel_blocks != 1 && threadIdx.x == 0) {
+            dst_meta[(ic0 + j_VKQ)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j_VKQ_0/nwarps], kqsum_j);
+        }
+    }
+#else
+   NO_DEVICE_CODE;
+#endif // FP16_AVAILABLE
+}
+
+template <int cols_per_block, int parallel_blocks>
+void launch_fattn_tile_f16_64_128(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * Q = dst->src[0];
+    switch (Q->ne[0]) {
+        case  64: {
+            constexpr int      D = 64;
+            constexpr int nwarps = 8;
+            fattn_kernel_t fattn_kernel = flash_attn_tile_ext_f16<D, cols_per_block, nwarps, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        case 128: {
+            constexpr int      D = 128;
+            constexpr int nwarps = 8;
+            fattn_kernel_t fattn_kernel = flash_attn_tile_ext_f16<D, cols_per_block, nwarps, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        default: {
+            GGML_ASSERT(false && "FlashAttention without tensor cores only supports head sizes 64 and 128.");
+        } break;
+    }
+}
+
+void ggml_cuda_flash_attn_ext_tile_f16(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * KQV = dst;
+    const ggml_tensor * Q   = dst->src[0];
+
+    const int32_t precision = KQV->op_params[2];
+    GGML_ASSERT(precision == GGML_PREC_DEFAULT);
+
+    if (Q->ne[1] <= 16) {
+        constexpr int cols_per_block = 16;
+        constexpr int parallel_blocks = 4;
+        launch_fattn_tile_f16_64_128<cols_per_block, parallel_blocks>(ctx, dst);
+        return;
+    }
+
+    if (Q->ne[1] <= 32) {
+        constexpr int cols_per_block = 32;
+        constexpr int parallel_blocks = 4;
+        launch_fattn_tile_f16_64_128<cols_per_block, parallel_blocks>(ctx, dst);
+        return;
+    }
+
+    constexpr int cols_per_block = 32;
+    constexpr int parallel_blocks = 1;
+    launch_fattn_tile_f16_64_128<cols_per_block, parallel_blocks>(ctx, dst);
+}
diff --git a/ggml-cuda/fattn-tile-f16.cuh b/ggml-cuda/fattn-tile-f16.cuh
new file mode 100644
index 000000000..ffc587842
--- /dev/null
+++ b/ggml-cuda/fattn-tile-f16.cuh
@@ -0,0 +1,3 @@
+#include "common.cuh"
+
+void ggml_cuda_flash_attn_ext_tile_f16(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
diff --git a/ggml-cuda/fattn-tile-f32.cu b/ggml-cuda/fattn-tile-f32.cu
new file mode 100644
index 000000000..5a3de2918
--- /dev/null
+++ b/ggml-cuda/fattn-tile-f32.cu
@@ -0,0 +1,309 @@
+#include "common.cuh"
+#include "fattn-common.cuh"
+#include "fattn-tile-f32.cuh"
+
+#define FATTN_KQ_STRIDE_TILE_F32 32
+
+template<int D, int ncols, int nwarps, int parallel_blocks> // D == head size
+#if !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__))
+__launch_bounds__(nwarps*WARP_SIZE, 1)
+#endif // !(defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__))
+static __global__ void flash_attn_tile_ext_f32(
+        const char * __restrict__ Q,
+        const char * __restrict__ K,
+        const char * __restrict__ V,
+        const char * __restrict__ mask,
+        float      * __restrict__ dst,
+        float2     * __restrict__ dst_meta,
+        const float scale,
+        const float max_bias,
+        const float m0,
+        const float m1,
+        const uint32_t n_head_log2,
+        const int ne00,
+        const int ne01,
+        const int ne02,
+        const int ne03,
+        const int ne10,
+        const int ne11,
+        const int ne12,
+        const int ne13,
+        const int ne31,
+        const int nb31,
+        const int nb01,
+        const int nb02,
+        const int nb03,
+        const int nb11,
+        const int nb12,
+        const int nb13,
+        const int ne0,
+        const int ne1,
+        const int ne2,
+        const int ne3) {
+    //In this kernel Q, K, V are matrices while i, j, k are matrix indices.
+
+    const int ic0 = (blockIdx.x / parallel_blocks) * ncols; // Index of the Q/QKV column to work on.
+    const int ip  =  blockIdx.x % parallel_blocks; // Index in group of blocks running for the same column in parallel.
+
+    const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix.
+    const float2 * Q_f2  = (const float2 *) (Q    + nb02* blockIdx.y              + nb01*ic0);
+    const half2  * K_h2  = (const half2  *) (K    + nb12*(blockIdx.y / gqa_ratio));
+    const half2  * V_h2  = (const half2  *) (V    + nb12*(blockIdx.y / gqa_ratio)); // K and V have same shape
+    const half   * maskh = (const half   *)  mask + ne11*ic0;
+
+    const int stride_KV2 = nb11 / sizeof(half2);
+
+    const float slope = get_alibi_slope(max_bias, blockIdx.y, n_head_log2, m0, m1);
+
+    static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64.");
+
+    __shared__ float KQ[ncols*FATTN_KQ_STRIDE_TILE_F32];
+
+    __shared__ float KV_tmp[FATTN_KQ_STRIDE_TILE_F32][D + 1]; // Pad D to avoid memory bank conflicts.
+    float2 * KV_tmp2 = (float2 *) KV_tmp;
+
+    float kqmax[ncols/nwarps];
+#pragma unroll
+    for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+        kqmax[j0/nwarps] = -FLT_MAX/2.0f;
+    }
+    float kqsum[ncols/nwarps] = {0.0f};
+
+    float2 VKQ[ncols/nwarps][(D/2)/WARP_SIZE] = {{{0.0f, 0.0f}}};
+
+    // Convert Q to half2 and store in registers:
+    __shared__ float Q_f[ncols][D];
+#pragma unroll
+    for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+        const int j = j0 + threadIdx.y;
+
+#pragma unroll
+        for (int i0 = 0; i0 < D; i0 += 2*WARP_SIZE) {
+            float2 tmp = ic0 + j < ne01 ? Q_f2[j*(nb01/sizeof(float2)) + i0/2 + threadIdx.x] : make_float2(0.0f, 0.0f);
+            Q_f[j][i0 + 0*WARP_SIZE + threadIdx.x] = tmp.x * scale;
+            Q_f[j][i0 + 1*WARP_SIZE + threadIdx.x] = tmp.y * scale;
+        }
+    }
+
+    __syncthreads();
+
+    const int k_start = parallel_blocks == 1 ? 0 : ip*FATTN_KQ_STRIDE_TILE_F32;
+    for (int k_VKQ_0 = k_start; k_VKQ_0 < ne11; k_VKQ_0 += parallel_blocks*FATTN_KQ_STRIDE_TILE_F32) {
+        // Calculate KQ tile and keep track of new maximum KQ values:
+
+        float kqmax_new[ncols/nwarps];
+#pragma unroll
+        for (int j = 0; j < ncols/nwarps; ++j) {
+            kqmax_new[j] = kqmax[j];
+        }
+
+#pragma unroll
+        for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F32; i_KQ_0 += nwarps) {
+            const int i_KQ = i_KQ_0 + threadIdx.y;
+
+#pragma unroll
+            for (int k_KQ_0 = 0; k_KQ_0 < D; k_KQ_0 += 2*WARP_SIZE) {
+                const half2 tmp = K_h2[(k_VKQ_0 + i_KQ)*stride_KV2 + k_KQ_0/2 + threadIdx.x];
+                KV_tmp[i_KQ][k_KQ_0 + 0*WARP_SIZE + threadIdx.x] =  __low2float(tmp);
+                KV_tmp[i_KQ][k_KQ_0 + 1*WARP_SIZE + threadIdx.x] = __high2float(tmp);
+            }
+        }
+
+        __syncthreads();
+
+        float sum[FATTN_KQ_STRIDE_TILE_F32/WARP_SIZE][ncols/nwarps] = {{0.0f}};
+
+#pragma unroll
+        for (int k_KQ = 0; k_KQ < D; ++k_KQ) {
+            float K_k[FATTN_KQ_STRIDE_TILE_F32/WARP_SIZE];
+            float Q_k[ncols/nwarps];
+
+#pragma unroll
+            for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F32; i_KQ_0 += WARP_SIZE) {
+                const int i_KQ = i_KQ_0 + threadIdx.x;
+
+                K_k[i_KQ_0/WARP_SIZE] = KV_tmp[i_KQ][k_KQ];
+            }
+#pragma unroll
+            for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) {
+                const int j_KQ = j_KQ_0 + threadIdx.y;
+
+                Q_k[j_KQ_0/nwarps] = Q_f[j_KQ][k_KQ];
+            }
+
+#pragma unroll
+            for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F32; i_KQ_0 += WARP_SIZE) {
+#pragma unroll
+                for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) {
+                    sum[i_KQ_0/WARP_SIZE][j_KQ_0/nwarps] += K_k[i_KQ_0/WARP_SIZE] * Q_k[j_KQ_0/nwarps];
+                }
+            }
+        }
+
+#pragma unroll
+        for (int i_KQ_0 = 0; i_KQ_0 < FATTN_KQ_STRIDE_TILE_F32; i_KQ_0 += WARP_SIZE) {
+            const int i_KQ = i_KQ_0 + threadIdx.x;
+
+#pragma unroll
+            for (int j_KQ_0 = 0; j_KQ_0 < ncols; j_KQ_0 += nwarps) {
+                const int j_KQ = j_KQ_0 + threadIdx.y;
+
+                sum[i_KQ_0/WARP_SIZE][j_KQ_0/nwarps] += mask ? slope*__half2float(maskh[j_KQ*ne11 + k_VKQ_0 + i_KQ]) : 0.0f;
+
+                kqmax_new[j_KQ_0/nwarps] = fmaxf(kqmax_new[j_KQ_0/nwarps], sum[i_KQ_0/WARP_SIZE][j_KQ_0/nwarps]);
+
+                KQ[j_KQ*FATTN_KQ_STRIDE_TILE_F32 + i_KQ] = sum[i_KQ_0/WARP_SIZE][j_KQ_0/nwarps];
+            }
+        }
+
+        __syncthreads();
+
+#pragma unroll
+        for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+            const int j = j0 + threadIdx.y;
+
+            kqmax_new[j0/nwarps] = warp_reduce_max(kqmax_new[j0/nwarps]);
+            const float KQ_max_scale = expf(kqmax[j0/nwarps] - kqmax_new[j0/nwarps]);
+            kqmax[j0/nwarps] = kqmax_new[j0/nwarps];
+
+            float kqsum_add = 0.0f;
+#pragma unroll
+            for (int i0 = 0; i0 < FATTN_KQ_STRIDE_TILE_F32; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
+
+                const float diff = KQ[j*FATTN_KQ_STRIDE_TILE_F32 + i] - kqmax[j0/nwarps];
+                const float val = expf(diff);
+                kqsum_add += val;
+                KQ[j*FATTN_KQ_STRIDE_TILE_F32 + i] = val;
+            }
+            kqsum[j0/nwarps] = kqsum[j0/nwarps]*KQ_max_scale + kqsum_add;
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+                VKQ[j0/nwarps][i0/WARP_SIZE].x *= KQ_max_scale;
+                VKQ[j0/nwarps][i0/WARP_SIZE].y *= KQ_max_scale;
+            }
+        }
+
+        __syncthreads();
+
+#pragma unroll
+        for (int k0 = 0; k0 < FATTN_KQ_STRIDE_TILE_F32; k0 += nwarps) {
+            const int k = k0 + threadIdx.y;
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
+
+                KV_tmp2[k*(D/2) + i].x =  __low2float(V_h2[(k_VKQ_0 + k)*stride_KV2 + i]);
+                KV_tmp2[k*(D/2) + i].y = __high2float(V_h2[(k_VKQ_0 + k)*stride_KV2 + i]);
+            }
+        }
+
+        __syncthreads();
+
+#pragma unroll
+        for (int k = 0; k < FATTN_KQ_STRIDE_TILE_F32; ++k) {
+            float2 V_k[(D/2)/WARP_SIZE];
+            float  KQ_k[ncols/nwarps];
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+                const int i = i0 + threadIdx.x;
+
+                V_k[i0/WARP_SIZE] = KV_tmp2[k*(D/2) + i];
+            }
+#pragma unroll
+            for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+                const int j = j0 + threadIdx.y;
+
+                KQ_k[j0/nwarps] = KQ[j*FATTN_KQ_STRIDE_TILE_F32 + k];
+            }
+
+#pragma unroll
+            for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
+#pragma unroll
+                for (int j0 = 0; j0 < ncols; j0 += nwarps) {
+                    VKQ[j0/nwarps][i0/WARP_SIZE].x += V_k[i0/WARP_SIZE].x*KQ_k[j0/nwarps];
+                    VKQ[j0/nwarps][i0/WARP_SIZE].y += V_k[i0/WARP_SIZE].y*KQ_k[j0/nwarps];
+                }
+            }
+        }
+
+        __syncthreads();
+    }
+
+#pragma unroll
+    for (int j_VKQ_0 = 0; j_VKQ_0 < ncols; j_VKQ_0 += nwarps) {
+        const int j_VKQ = j_VKQ_0 + threadIdx.y;
+
+        if (ic0 + j_VKQ >= ne01) {
+            return;
+        }
+
+        float kqsum_j = kqsum[j_VKQ_0/nwarps];
+        kqsum_j = warp_reduce_sum(kqsum_j);
+
+#pragma unroll
+        for (int i00 = 0; i00 < D; i00 += 2*WARP_SIZE) {
+            const int i0 = i00 + 2*threadIdx.x;
+
+            float2 dst_val = VKQ[j_VKQ_0/nwarps][i0/(2*WARP_SIZE)];
+            if (parallel_blocks == 1) {
+                dst_val.x /= kqsum_j;
+                dst_val.y /= kqsum_j;
+            }
+            const int j_dst = (ic0 + j_VKQ)*parallel_blocks + ip;
+            dst[j_dst*D*gridDim.y + D*blockIdx.y + i0 + 0] = dst_val.x;
+            dst[j_dst*D*gridDim.y + D*blockIdx.y + i0 + 1] = dst_val.y;
+        }
+
+        if (parallel_blocks != 1 && threadIdx.x == 0) {
+            dst_meta[(ic0 + j_VKQ)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j_VKQ_0/nwarps], kqsum_j);
+        }
+    }
+}
+
+template <int cols_per_block, int parallel_blocks>
+void launch_fattn_tile_f32_64_128(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * Q = dst->src[0];
+    switch (Q->ne[0]) {
+        case  64: {
+            constexpr int      D = 64;
+            constexpr int nwarps = 8;
+            fattn_kernel_t fattn_kernel = flash_attn_tile_ext_f32<D, cols_per_block, nwarps, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        case 128: {
+            constexpr int      D = 128;
+            constexpr int nwarps = 8;
+            fattn_kernel_t fattn_kernel = flash_attn_tile_ext_f32<D, cols_per_block, nwarps, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        default: {
+            GGML_ASSERT(false && "FlashAttention without tensor cores only supports head sizes 64 and 128.");
+        } break;
+    }
+}
+
+void ggml_cuda_flash_attn_ext_tile_f32(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * Q = dst->src[0];
+
+    if (Q->ne[1] <= 16) {
+        constexpr int cols_per_block = 16;
+        constexpr int parallel_blocks = 4;
+        launch_fattn_tile_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
+        return;
+    }
+
+    if (Q->ne[1] <= 32) {
+        constexpr int cols_per_block = 32;
+        constexpr int parallel_blocks = 4;
+        launch_fattn_tile_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
+        return;
+    }
+
+    constexpr int cols_per_block = 32;
+    constexpr int parallel_blocks = 1;
+    launch_fattn_tile_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
+}
diff --git a/ggml-cuda/fattn-tile-f32.cuh b/ggml-cuda/fattn-tile-f32.cuh
new file mode 100644
index 000000000..b1c546c80
--- /dev/null
+++ b/ggml-cuda/fattn-tile-f32.cuh
@@ -0,0 +1,3 @@
+#include "common.cuh"
+
+void ggml_cuda_flash_attn_ext_tile_f32(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
diff --git a/ggml-cuda/fattn-vec-f16.cu b/ggml-cuda/fattn-vec-f16.cu
index cbf5f7835..808e8f362 100644
--- a/ggml-cuda/fattn-vec-f16.cu
+++ b/ggml-cuda/fattn-vec-f16.cu
@@ -53,17 +53,8 @@ static __global__ void flash_attn_vec_ext_f16(
     const int stride_KV  = nb11 / sizeof(half);
     const int stride_KV2 = nb11 / sizeof(half2);
 
-    half  slopeh = __float2half(1.0f);
-
-    // ALiBi
-    if (max_bias > 0.0f) {
-        const int h = blockIdx.y;
-
-        const float base = h < n_head_log2 ? m0 : m1;
-        const int   exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
-
-        slopeh = __float2half(powf(base, exph));
-    }
+    const float slopef = get_alibi_slope(max_bias, blockIdx.y, n_head_log2, m0, m1);
+    const half  slopeh = __float2half(slopef);
 
     static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64.");
     constexpr int nwarps = D / WARP_SIZE;
@@ -103,7 +94,7 @@ static __global__ void flash_attn_vec_ext_f16(
         for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
             const int i = i0 + threadIdx.x;
 
-            const float2 tmp = Q_f2[j*(nb01/sizeof(float2)) + i];
+            const float2 tmp = ncols <= 2 || ic0 + j < ne01 ? Q_f2[j*(nb01/sizeof(float2)) + i] : make_float2(0.0f, 0.0f);
             Q_h2[j][i0/WARP_SIZE] = make_half2(scale, scale) * make_half2(tmp.x, tmp.y);
         }
     }
@@ -221,6 +212,10 @@ static __global__ void flash_attn_vec_ext_f16(
 
 #pragma unroll
     for (int j_VKQ = 0; j_VKQ < ncols; ++j_VKQ) {
+        if (ncols > 2 && ic0 + j_VKQ >= ne01) {
+            break;
+        }
+
         kqsum[j_VKQ] = kqsum_shared[j_VKQ][threadIdx.x];
         kqsum[j_VKQ] = warp_reduce_sum(kqsum[j_VKQ]);
 
@@ -232,199 +227,104 @@ static __global__ void flash_attn_vec_ext_f16(
         dst[j_dst*D*gridDim.y + D*blockIdx.y + tid] = dst_val;
     }
 
-    if (parallel_blocks != 1 && tid != 0) {
-#pragma unroll
-        for (int j = 0; j < ncols; ++j) {
-            dst_meta[(ic0 + j)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j], kqsum[j]);
-        }
+    if (parallel_blocks != 1 && tid < ncols && (ncols <= 2 || ic0 + tid < ne01)) {
+        dst_meta[(ic0 + tid)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[tid], kqsum[tid]);
     }
 #else
    NO_DEVICE_CODE;
 #endif // FP16_AVAILABLE
 }
 
-template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_f16(
-        const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask,
-        ggml_cuda_pool & pool, cudaStream_t main_stream
-) {
-    ggml_cuda_pool_alloc<float>  dst_tmp(pool);
-    ggml_cuda_pool_alloc<float2> dst_tmp_meta(pool);
-
-    if (parallel_blocks > 1) {
-        dst_tmp.alloc(parallel_blocks*ggml_nelements(KQV));
-        dst_tmp_meta.alloc(parallel_blocks*ggml_nrows(KQV));
-    }
-
-    constexpr int  nwarps = (D + WARP_SIZE - 1) / WARP_SIZE;
-    const     dim3 block_dim(WARP_SIZE, nwarps, 1);
-    const     dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]);
-    const     int  shmem = 0;
-
-    float scale    = 1.0f;
-    float max_bias = 0.0f;
-
-    memcpy(&scale,    (float *) KQV->op_params + 0, sizeof(float));
-    memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float));
-
-    const uint32_t n_head      = Q->ne[2];
-    const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head));
-
-    const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
-    const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
-
-    flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks>
-        <<<blocks_num, block_dim, shmem, main_stream>>> (
-                (const char *) Q->data,
-                (const char *) K->data,
-                (const char *) V->data,
-                mask ? ((const char *) mask->data) : nullptr,
-                parallel_blocks == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr,
-                scale, max_bias, m0, m1, n_head_log2,
-                Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3],
-                K->ne[0], K->ne[1], K->ne[2], K->ne[3],
-                mask ? mask->ne[1] : 0, mask ?  mask->nb[1] : 0,
-                Q->nb[1], Q->nb[2], Q->nb[3],
-                K->nb[1], K->nb[2], K->nb[3],
-                KQV->ne[0], KQV->ne[1], KQV->ne[2], KQV->ne[3]
-                );
-    CUDA_CHECK(cudaGetLastError());
-
-    if (parallel_blocks == 1) {
-        return;
-    }
-
-    const dim3 block_dim_combine(D, 1, 1);
-    const dim3 blocks_num_combine(Q->ne[1], blocks_num.y, blocks_num.z);
-    const int  shmem_combine = 0;
-
-    flash_attn_combine_results<D, parallel_blocks>
-        <<<blocks_num_combine, block_dim_combine, shmem_combine, main_stream>>>
-        (dst_tmp.ptr, dst_tmp_meta.ptr, (float *) KQV->data);
-    CUDA_CHECK(cudaGetLastError());
-}
-
 void ggml_cuda_flash_attn_ext_vec_f16(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
-    const ggml_tensor * Q = dst->src[0];
-    const ggml_tensor * K = dst->src[1];
-    const ggml_tensor * V = dst->src[2];
-
-    const ggml_tensor * mask = dst->src[3];
-
     ggml_tensor * KQV = dst;
+    ggml_tensor * Q   = dst->src[0];
 
     const int32_t precision = KQV->op_params[2];
     GGML_ASSERT(precision == GGML_PREC_DEFAULT);
 
-    constexpr int cols_per_block = 1;
+    constexpr int cols_per_block  = 1;
     constexpr int parallel_blocks = 4;
     switch (Q->ne[0]) {
-        case 64:
-            launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-            break;
-        case 128:
-            launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-            break;
-        case 256:
-            launch_fattn_vec_f16<256, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-            break;
+        case  64: {
+            constexpr int      D = 64;
+            constexpr int nwarps = D/WARP_SIZE;
+            fattn_kernel_t fattn_kernel = flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        case 128: {
+            constexpr int      D = 128;
+            constexpr int nwarps = D/WARP_SIZE;
+            fattn_kernel_t fattn_kernel = flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        case 256: {
+            constexpr int      D = 256;
+            constexpr int nwarps = D/WARP_SIZE;
+            fattn_kernel_t fattn_kernel = flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
         default:
             GGML_ASSERT(false);
             break;
     }
 }
 
+template <int cols_per_block, int parallel_blocks>
+void launch_fattn_vec_f16_64_128(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * Q = dst->src[0];
+    switch (Q->ne[0]) {
+        case  64: {
+            constexpr int      D = 64;
+            constexpr int nwarps = D/WARP_SIZE;
+            fattn_kernel_t fattn_kernel = flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        case 128: {
+            constexpr int      D = 128;
+            constexpr int nwarps = D/WARP_SIZE;
+            fattn_kernel_t fattn_kernel = flash_attn_vec_ext_f16<D, cols_per_block, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        default: {
+            GGML_ASSERT(false && "FlashAttention without tensor cores only supports head sizes 64 and 128.");
+        } break;
+    }
+}
+
 void ggml_cuda_flash_attn_ext_vec_f16_no_mma(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
-    const ggml_tensor * Q = dst->src[0];
-    const ggml_tensor * K = dst->src[1];
-    const ggml_tensor * V = dst->src[2];
-
-    const ggml_tensor * mask = dst->src[3];
-
-    ggml_tensor * KQV = dst;
+    const ggml_tensor * KQV = dst;
+    const ggml_tensor * Q   = dst->src[0];
 
     const int32_t precision = KQV->op_params[2];
     GGML_ASSERT(precision == GGML_PREC_DEFAULT);
-    GGML_ASSERT(Q->ne[0] == 64 || Q->ne[0] == 128 && "FlashAttention without tensor cores only supports head sizes 64 and 128.");
 
     if (Q->ne[1] == 1) {
-        constexpr int cols_per_block = 1;
-        constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        ggml_cuda_flash_attn_ext_vec_f16(ctx, dst);
         return;
     }
 
     if (Q->ne[1] == 2) {
-        constexpr int cols_per_block = 2;
+        constexpr int cols_per_block  = 2;
         constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        launch_fattn_vec_f16_64_128<cols_per_block, parallel_blocks>(ctx, dst);
         return;
     }
 
     if (Q->ne[1] <= 4) {
-        constexpr int cols_per_block = 4;
+        constexpr int cols_per_block  = 4;
         constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        launch_fattn_vec_f16_64_128<cols_per_block, parallel_blocks>(ctx, dst);
         return;
     }
 
     if (Q->ne[1] <= 8) {
-        constexpr int cols_per_block = 8;
+        constexpr int cols_per_block  = 8;
         constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        launch_fattn_vec_f16_64_128<cols_per_block, parallel_blocks>(ctx, dst);
         return;
     }
 
-    constexpr int cols_per_block = 8;
+    constexpr int cols_per_block  = 8;
     constexpr int parallel_blocks = 1;
-    switch (Q->ne[0]) {
-        case 64:
-            launch_fattn_vec_f16< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-            break;
-        case 128:
-            launch_fattn_vec_f16<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-            break;
-        default:
-            GGML_ASSERT(false);
-            break;
-    }
+    launch_fattn_vec_f16_64_128<cols_per_block, parallel_blocks>(ctx, dst);
 }
diff --git a/ggml-cuda/fattn-vec-f32.cu b/ggml-cuda/fattn-vec-f32.cu
index 40c336ce3..b4652301b 100644
--- a/ggml-cuda/fattn-vec-f32.cu
+++ b/ggml-cuda/fattn-vec-f32.cu
@@ -52,17 +52,7 @@ static __global__ void flash_attn_vec_ext_f32(
     const int stride_KV  = nb11 / sizeof(half);
     const int stride_KV2 = nb11 / sizeof(half2);
 
-    float slope = 1.0f;
-
-    // ALiBi
-    if (max_bias > 0.0f) {
-        const int h = blockIdx.y;
-
-        const float base = h < n_head_log2 ? m0 : m1;
-        const int   exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
-
-        slope = powf(base, exph);
-    }
+    const float slope = get_alibi_slope(max_bias, blockIdx.y, n_head_log2, m0, m1);
 
     static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64.");
     constexpr int nwarps = D / WARP_SIZE;
@@ -101,7 +91,7 @@ static __global__ void flash_attn_vec_ext_f32(
         for (int i0 = 0; i0 < D/2; i0 += WARP_SIZE) {
             const int i = i0 + threadIdx.x;
 
-            Q_h2[j][i0/WARP_SIZE]    = Q_f2[j*(nb01/sizeof(float2)) + i];
+            Q_h2[j][i0/WARP_SIZE]    = ncols <= 2 || ic0 + j ? Q_f2[j*(nb01/sizeof(float2)) + i] : make_float2(0.0f, 0.0f);
             Q_h2[j][i0/WARP_SIZE].x *= scale;
             Q_h2[j][i0/WARP_SIZE].y *= scale;
         }
@@ -210,6 +200,10 @@ static __global__ void flash_attn_vec_ext_f32(
 
 #pragma unroll
     for (int j_VKQ = 0; j_VKQ < ncols; ++j_VKQ) {
+        if (ncols > 2 && ic0 + j_VKQ >= ne01) {
+            break;
+        }
+
         kqsum[j_VKQ] = kqsum_shared[j_VKQ][threadIdx.x];
         kqsum[j_VKQ] = warp_reduce_sum(kqsum[j_VKQ]);
 
@@ -221,164 +215,65 @@ static __global__ void flash_attn_vec_ext_f32(
         dst[j_dst*D*gridDim.y + D*blockIdx.y + tid] = dst_val;
     }
 
-    if (parallel_blocks != 1 && tid != 0) {
-#pragma unroll
-        for (int j = 0; j < ncols; ++j) {
-            dst_meta[(ic0 + j)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[j], kqsum[j]);
-        }
+    if (parallel_blocks != 1 && tid < ncols && (ncols <= 2 || ic0 + tid < ne01)) {
+        dst_meta[(ic0 + tid)*gridDim.y*parallel_blocks + blockIdx.y*parallel_blocks + ip] = make_float2(kqmax[tid], kqsum[tid]);
     }
 }
 
-template <int D, int cols_per_block, int parallel_blocks> void launch_fattn_vec_f32(
-        const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask,
-        ggml_cuda_pool & pool, cudaStream_t main_stream
-) {
-    ggml_cuda_pool_alloc<float>  dst_tmp(pool);
-    ggml_cuda_pool_alloc<float2> dst_tmp_meta(pool);
-
-    if (parallel_blocks > 1) {
-        dst_tmp.alloc(parallel_blocks*ggml_nelements(KQV));
-        dst_tmp_meta.alloc(parallel_blocks*ggml_nrows(KQV));
+template <int cols_per_block, int parallel_blocks>
+void launch_fattn_vec_f32_64_128(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * Q = dst->src[0];
+    switch (Q->ne[0]) {
+        case  64: {
+            constexpr int      D = 64;
+            constexpr int nwarps = D/WARP_SIZE;
+            fattn_kernel_t fattn_kernel = flash_attn_vec_ext_f32<D, cols_per_block, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        case 128: {
+            constexpr int      D = 128;
+            constexpr int nwarps = D/WARP_SIZE;
+            fattn_kernel_t fattn_kernel = flash_attn_vec_ext_f32<D, cols_per_block, parallel_blocks>;
+            launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
+        } break;
+        default: {
+            GGML_ASSERT(false && "FlashAttention without tensor cores only supports head sizes 64 and 128.");
+        } break;
     }
-
-    constexpr int  nwarps = (D + WARP_SIZE - 1) / WARP_SIZE;
-    const     dim3 block_dim(WARP_SIZE, nwarps, 1);
-    const     dim3 blocks_num(parallel_blocks*((Q->ne[1] + cols_per_block - 1) / cols_per_block), Q->ne[2], Q->ne[3]);
-    const     int  shmem = 0;
-
-    float scale    = 1.0f;
-    float max_bias = 0.0f;
-
-    memcpy(&scale,    (float *) KQV->op_params + 0, sizeof(float));
-    memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float));
-
-    const uint32_t n_head      = Q->ne[2];
-    const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head));
-
-    const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
-    const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
-
-    flash_attn_vec_ext_f32<D, cols_per_block, parallel_blocks>
-        <<<blocks_num, block_dim, shmem, main_stream>>> (
-                (const char *) Q->data,
-                (const char *) K->data,
-                (const char *) V->data,
-                mask ? ((const char *) mask->data) : nullptr,
-                parallel_blocks == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr,
-                scale, max_bias, m0, m1, n_head_log2,
-                Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3],
-                K->ne[0], K->ne[1], K->ne[2], K->ne[3],
-                mask ? mask->ne[1] : 0, mask ?  mask->nb[1] : 0,
-                Q->nb[1], Q->nb[2], Q->nb[3],
-                K->nb[1], K->nb[2], K->nb[3],
-                KQV->ne[0], KQV->ne[1], KQV->ne[2], KQV->ne[3]
-                );
-    CUDA_CHECK(cudaGetLastError());
-
-    if (parallel_blocks == 1) {
-        return;
-    }
-
-    const dim3 block_dim_combine(D, 1, 1);
-    const dim3 blocks_num_combine(Q->ne[1], blocks_num.y, blocks_num.z);
-    const int  shmem_combine = 0;
-
-    flash_attn_combine_results<D, parallel_blocks>
-        <<<blocks_num_combine, block_dim_combine, shmem_combine, main_stream>>>
-        (dst_tmp.ptr, dst_tmp_meta.ptr, (float *) KQV->data);
-    CUDA_CHECK(cudaGetLastError());
 }
 
 void ggml_cuda_flash_attn_ext_vec_f32(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
     const ggml_tensor * Q = dst->src[0];
-    const ggml_tensor * K = dst->src[1];
-    const ggml_tensor * V = dst->src[2];
-
-    const ggml_tensor * mask = dst->src[3];
-
-    ggml_tensor * KQV = dst;
-
-    GGML_ASSERT(Q->ne[0] == 64 || Q->ne[0] == 128 && "FlashAttention without tensor cores only supports head sizes 64 and 128.");
 
     if (Q->ne[1] == 1) {
-        constexpr int cols_per_block = 1;
+        constexpr int cols_per_block  = 1;
         constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        launch_fattn_vec_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
         return;
     }
 
     if (Q->ne[1] == 2) {
-        constexpr int cols_per_block = 2;
+        constexpr int cols_per_block  = 2;
         constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        launch_fattn_vec_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
         return;
     }
 
     if (Q->ne[1] <= 4) {
-        constexpr int cols_per_block = 4;
+        constexpr int cols_per_block  = 4;
         constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        launch_fattn_vec_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
         return;
     }
 
     if (Q->ne[1] <= 8) {
-        constexpr int cols_per_block = 8;
+        constexpr int cols_per_block  = 8;
         constexpr int parallel_blocks = 4;
-        switch (Q->ne[0]) {
-            case 64:
-                launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            case 128:
-                launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-                break;
-            default:
-                GGML_ASSERT(false);
-                break;
-        }
+        launch_fattn_vec_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
         return;
     }
 
-    constexpr int cols_per_block = 8;
+    constexpr int cols_per_block  = 8;
     constexpr int parallel_blocks = 1;
-    switch (Q->ne[0]) {
-        case 64:
-            launch_fattn_vec_f32< 64, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-            break;
-        case 128:
-            launch_fattn_vec_f32<128, cols_per_block, parallel_blocks>(Q, K, V, KQV, mask, ctx.pool(), ctx.stream());
-            break;
-        default:
-            GGML_ASSERT(false);
-            break;
-    }
+    launch_fattn_vec_f32_64_128<cols_per_block, parallel_blocks>(ctx, dst);
 }
diff --git a/ggml-cuda/fattn.cu b/ggml-cuda/fattn.cu
index 419f8e752..af7c95232 100644
--- a/ggml-cuda/fattn.cu
+++ b/ggml-cuda/fattn.cu
@@ -1,5 +1,7 @@
 #include "common.cuh"
 #include "fattn-common.cuh"
+#include "fattn-tile-f16.cuh"
+#include "fattn-tile-f32.cuh"
 #include "fattn-vec-f16.cuh"
 #include "fattn-vec-f32.cuh"
 #include "fattn.cuh"
@@ -83,19 +85,9 @@ static __global__ void flash_attn_ext_f16(
     const int stride_Q  = nb01 / sizeof(float);
     const int stride_KV = nb11 / sizeof(half);
 
-    half  slopeh = __float2half(1.0f);
-    half2 slope2 = make_half2(1.0f, 1.0f);
-
-    // ALiBi
-    if (max_bias > 0.0f) {
-        const int h = blockIdx.y;
-
-        const float base = h < n_head_log2 ? m0 : m1;
-        const int   exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
-
-        slopeh = __float2half(powf(base, exph));
-        slope2 = make_half2(slopeh, slopeh);
-    }
+    const float slopef = get_alibi_slope(max_bias, blockIdx.y, n_head_log2, m0, m1);
+    const half  slopeh = __float2half(slopef);
+    const half2 slope2 = make_half2(slopef, slopef);
 
     frag_b Q_b[D/16][ncols/frag_n];
 
@@ -437,117 +429,64 @@ static_assert(get_VKQ_stride( 80, 1, 16) ==  16, "Test failed.");
 static_assert(get_VKQ_stride( 80, 2, 16) ==  16, "Test failed.");
 static_assert(get_VKQ_stride( 80, 4, 16) ==  16, "Test failed.");
 
-template <int D, int cols_per_block, int nwarps, int parallel_blocks, typename KQ_acc_t> void launch_fattn_f16_impl(
-        const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask,
-        ggml_cuda_pool & pool, cudaStream_t main_stream
-) {
-    ggml_cuda_pool_alloc<float>  dst_tmp(pool);
-    ggml_cuda_pool_alloc<float2> dst_tmp_meta(pool);
+template <int D, int cols_per_block, int nwarps, typename KQ_acc_t>
+void launch_fattn_f16(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+    const ggml_tensor * Q = dst->src[0];
 
-    if (parallel_blocks > 1) {
-        dst_tmp.alloc(parallel_blocks*ggml_nelements(KQV));
-        dst_tmp_meta.alloc(parallel_blocks*ggml_nrows(KQV));
-    }
-
-    constexpr int  frag_m = (cols_per_block) == 8 && (D) % 32 == 0 ? 32 : 16;
-    const     dim3 block_dim(WARP_SIZE, nwarps, 1);
-    const     dim3 blocks_num(parallel_blocks*(Q->ne[1] + cols_per_block - 1) / cols_per_block, Q->ne[2], Q->ne[3]);
-    const     int  shmem = 0;
-
-    float scale    = 1.0f;
-    float max_bias = 0.0f;
-
-    memcpy(&scale,    (float *) KQV->op_params + 0, sizeof(float));
-    memcpy(&max_bias, (float *) KQV->op_params + 1, sizeof(float));
-
-    const uint32_t n_head      = Q->ne[2];
-    const uint32_t n_head_log2 = 1u << (uint32_t) floorf(log2f((float) n_head));
-
-    const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
-    const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
-
-    flash_attn_ext_f16<D, cols_per_block, nwarps, get_VKQ_stride(D, nwarps, frag_m), parallel_blocks, KQ_acc_t>
-        <<<blocks_num, block_dim, shmem, main_stream>>> (
-                (const char *) Q->data,
-                (const char *) K->data,
-                (const char *) V->data,
-                mask ? ((const char *) mask->data) : nullptr,
-                (parallel_blocks) == 1 ? (float *) KQV->data : dst_tmp.ptr, dst_tmp_meta.ptr,
-                scale, max_bias, m0, m1, n_head_log2,
-                Q->ne[0], Q->ne[1], Q->ne[2], Q->ne[3],
-                K->ne[0], K->ne[1], K->ne[2], K->ne[3],
-                mask ? mask->ne[1] : 0, mask ?  mask->nb[1] : 0,
-                Q->nb[1], Q->nb[2], Q->nb[3],
-                K->nb[1], K->nb[2], K->nb[3],
-                KQV->ne[0], KQV->ne[1], KQV->ne[2], KQV->ne[3]
-                );
-    CUDA_CHECK(cudaGetLastError());
-
-    if ((parallel_blocks) == 1) {
-        return;
-    }
-
-    const dim3 block_dim_combine(D, 1, 1);
-    const dim3 blocks_num_combine(Q->ne[1], blocks_num.y, blocks_num.z);
-    const int  shmem_combine = 0;
-
-    flash_attn_combine_results<D, parallel_blocks>
-        <<<blocks_num_combine, block_dim_combine, shmem_combine, main_stream>>>
-        (dst_tmp.ptr, dst_tmp_meta.ptr, (float *) KQV->data);
-    CUDA_CHECK(cudaGetLastError());
-}
-
-template <int D, int cols_per_block, int nwarps, typename KQ_acc_t> void launch_fattn_f16(
-        const ggml_tensor * Q, const ggml_tensor * K, const ggml_tensor * V, ggml_tensor * KQV, const ggml_tensor * mask,
-        const int nsm, ggml_cuda_pool & pool, cudaStream_t main_stream
-) {
+    constexpr int frag_m = cols_per_block == 8 && D % 32 == 0 ? 32 : 16;
     const int blocks_num_pb1 = ((Q->ne[1] + cols_per_block - 1) / cols_per_block)*Q->ne[2]*Q->ne[3];
+    const int nsm = ggml_cuda_info().devices[ggml_cuda_get_device()].nsm;
 
     if (4*blocks_num_pb1 < 2*nsm) {
-        launch_fattn_f16_impl<D, cols_per_block, nwarps, 4, KQ_acc_t>(Q, K, V, KQV, mask, pool, main_stream);
+        constexpr int parallel_blocks = 4;
+        fattn_kernel_t fattn_kernel = flash_attn_ext_f16<D, cols_per_block, nwarps, get_VKQ_stride(D, nwarps, frag_m), parallel_blocks, KQ_acc_t>;
+        launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
         return;
     }
     if (2*blocks_num_pb1 < 2*nsm) {
-        launch_fattn_f16_impl<D, cols_per_block, nwarps, 2, KQ_acc_t>(Q, K, V, KQV, mask, pool, main_stream);
+        constexpr int parallel_blocks = 2;
+        fattn_kernel_t fattn_kernel = flash_attn_ext_f16<D, cols_per_block, nwarps, get_VKQ_stride(D, nwarps, frag_m), parallel_blocks, KQ_acc_t>;
+        launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
         return;
     }
-    launch_fattn_f16_impl<D, cols_per_block, nwarps, 1, KQ_acc_t>(Q, K, V, KQV, mask, pool, main_stream);
+    constexpr int parallel_blocks = 1;
+    fattn_kernel_t fattn_kernel = flash_attn_ext_f16<D, cols_per_block, nwarps, get_VKQ_stride(D, nwarps, frag_m), parallel_blocks, KQ_acc_t>;
+    launch_fattn<D, parallel_blocks>(ctx, dst, fattn_kernel, nwarps, cols_per_block);
 }
 
 void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
-    const ggml_tensor * Q = dst->src[0];
-    const ggml_tensor * K = dst->src[1];
-    const ggml_tensor * V = dst->src[2];
-
-    const ggml_tensor * mask = dst->src[3];
-
-    ggml_tensor * KQV = dst;
-
-    GGML_ASSERT(Q->type == GGML_TYPE_F32);
-    GGML_ASSERT(K->type == GGML_TYPE_F16);
-    GGML_ASSERT(V->type == GGML_TYPE_F16);
-    GGML_ASSERT(KQV->type == GGML_TYPE_F32);
-
-    GGML_ASSERT(!mask || mask->type == GGML_TYPE_F16);
-    GGML_ASSERT(!mask || mask->ne[1] >= GGML_PAD(Q->ne[1], 16) &&
-                                "the Flash-Attention CUDA kernel requires the mask to be padded to 16 and at least n_queries big");
-
-    GGML_ASSERT(K->ne[1] % FATTN_KQ_STRIDE == 0 && "Incorrect KV cache padding.");
+    const ggml_tensor * KQV = dst;
+    const ggml_tensor * Q   = dst->src[0];
 
     ggml_cuda_set_device(ctx.device);
-
-    const int cc  = ggml_cuda_info().devices[ggml_cuda_get_device()].cc;
-    const int nsm = ggml_cuda_info().devices[ggml_cuda_get_device()].nsm;
-
+    const int cc = ggml_cuda_info().devices[ggml_cuda_get_device()].cc;
     const int32_t precision = KQV->op_params[2];
 
+    // On AMD the tile kernels perform poorly, use the vec kernel instead:
+    if (cc >= CC_OFFSET_AMD) {
+        if (precision == GGML_PREC_DEFAULT) {
+            ggml_cuda_flash_attn_ext_vec_f16_no_mma(ctx, dst);
+        } else {
+            ggml_cuda_flash_attn_ext_vec_f32(ctx, dst);
+        }
+        return;
+    }
+
     if (!fast_fp16_available(cc)) {
-        ggml_cuda_flash_attn_ext_vec_f32(ctx, dst);
+        if (Q->ne[1] <= 8) {
+            ggml_cuda_flash_attn_ext_vec_f32(ctx, dst);
+        } else {
+            ggml_cuda_flash_attn_ext_tile_f32(ctx, dst);
+        }
         return;
     }
 
     if (!fp16_mma_available(cc)) {
-        ggml_cuda_flash_attn_ext_vec_f16_no_mma(ctx, dst);
+        if (Q->ne[1] <= 8) {
+            ggml_cuda_flash_attn_ext_vec_f16_no_mma(ctx, dst);
+        } else {
+            ggml_cuda_flash_attn_ext_tile_f16(ctx, dst);
+        }
         return;
     }
 
@@ -562,22 +501,22 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst
             constexpr int nwarps         =  4;
             switch (Q->ne[0]) {
                 case 64:
-                    launch_fattn_f16< 64, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16< 64, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 80:
-                    launch_fattn_f16< 80, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16< 80, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 96:
-                    launch_fattn_f16< 96, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16< 96, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 112:
-                    launch_fattn_f16<112, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16<112, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 128:
-                    launch_fattn_f16<128, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16<128, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 256:
-                    launch_fattn_f16<256, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16<256, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 default:
                     GGML_ASSERT(false);
@@ -588,22 +527,22 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst
             constexpr int nwarps         =  4;
             switch (Q->ne[0]) {
                 case 64:
-                    launch_fattn_f16< 64, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16< 64, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 80:
-                    launch_fattn_f16< 80, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16< 80, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 96:
-                    launch_fattn_f16< 96, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16< 96, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 112:
-                    launch_fattn_f16<112, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16<112, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 case 128:
-                    launch_fattn_f16<128, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                    launch_fattn_f16<128, cols_per_block, nwarps, float>(ctx, dst);
                     break;
                 // case 256:
-                //     launch_fattn_f16<256, cols_per_block, nwarps, float>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                //     launch_fattn_f16<256, cols_per_block, nwarps, float>(ctx, dst);
                 //     break;
                 default:
                     GGML_ASSERT(false);
@@ -623,16 +562,16 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst
         constexpr int nwarps         = 4;
         switch (Q->ne[0]) {
             case 64:
-                launch_fattn_f16< 64, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16< 64, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 96:
-                launch_fattn_f16< 96, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16< 96, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 128:
-                launch_fattn_f16<128, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16<128, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 256:
-                launch_fattn_f16<256, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16<256, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             default:
                 GGML_ASSERT(false);
@@ -646,22 +585,22 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst
         constexpr int nwarps         =  4;
         switch (Q->ne[0]) {
             case 64:
-                launch_fattn_f16< 64, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16< 64, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 80:
-                launch_fattn_f16< 80, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16< 80, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 96:
-                launch_fattn_f16< 96, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16< 96, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 112:
-                launch_fattn_f16<112, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16<112, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 128:
-                launch_fattn_f16<128, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16<128, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             case 256:
-                launch_fattn_f16<256, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+                launch_fattn_f16<256, cols_per_block, nwarps, half>(ctx, dst);
                 break;
             default:
                 GGML_ASSERT(false);
@@ -674,22 +613,22 @@ void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst
     constexpr int nwarps         =  4;
     switch (Q->ne[0]) {
         case 64:
-            launch_fattn_f16< 64, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+            launch_fattn_f16< 64, cols_per_block, nwarps, half>(ctx, dst);
             break;
         case 80:
-            launch_fattn_f16< 80, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+            launch_fattn_f16< 80, cols_per_block, nwarps, half>(ctx, dst);
             break;
         case 96:
-            launch_fattn_f16< 96, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+            launch_fattn_f16< 96, cols_per_block, nwarps, half>(ctx, dst);
             break;
         case 112:
-            launch_fattn_f16<112, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+            launch_fattn_f16<112, cols_per_block, nwarps, half>(ctx, dst);
             break;
         case 128:
-            launch_fattn_f16<128, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+            launch_fattn_f16<128, cols_per_block, nwarps, half>(ctx, dst);
             break;
         case 256:
-            launch_fattn_f16<256, cols_per_block, nwarps, half>(Q, K, V, KQV, mask, nsm, ctx.pool(), ctx.stream());
+            launch_fattn_f16<256, cols_per_block, nwarps, half>(ctx, dst);
             break;
         default:
             GGML_ASSERT(false);
diff --git a/ggml-cuda/mmq.cu b/ggml-cuda/mmq.cu
index 7948f1b12..c0a66d9b6 100644
--- a/ggml-cuda/mmq.cu
+++ b/ggml-cuda/mmq.cu
@@ -9,6 +9,135 @@ typedef float (*vec_dot_q_mul_mat_cuda_t)(
     const int * __restrict__ x_ql, const half2 * __restrict__ x_dm, const int * __restrict__ x_qh, const int * __restrict__ x_sc,
     const int * __restrict__ y_qs, const half2 * __restrict__ y_ms, const int & i, const int & j, const int & k);
 typedef void (*dot_kernel_k_t)(const void * __restrict__ vx, const int ib, const int iqs, const float * __restrict__ y, float & v);
+typedef void (mul_mat_q_t)(
+    const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
+    const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst);
+
+struct mmq_arch_config_t {
+    int x;
+    int y;
+    int nwarps;
+};
+
+struct mmq_config_t {
+    mmq_arch_config_t rdna2;
+    mmq_arch_config_t rdna1;
+    mmq_arch_config_t ampere;
+    mmq_arch_config_t pascal;
+};
+
+constexpr mmq_config_t MMQ_CONFIG_Q4_0 = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 64,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        { 64, 128, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q4_1 = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 64,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        { 64, 128, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q5_0 = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 64,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        {128,  64, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q5_1 = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 64,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        {128,  64, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q8_0 = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 64,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        {128,  64, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q2_K = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        {128,  32, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        { 64, 128, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q3_K = {
+//        x    y  nwarps
+        {128,  64, 8},
+        { 32, 128, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        {128, 128, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q4_K = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 32,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        { 64, 128, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q5_K = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 32,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        { 64, 128, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+constexpr mmq_config_t MMQ_CONFIG_Q6_K = {
+//        x    y  nwarps
+        { 64, 128, 8},
+        { 32,  64, 8},
+#ifdef CUDA_USE_TENSOR_CORES
+        {  4,  32, 4},
+#else
+        { 64,  64, 4},
+#endif // CUDA_USE_TENSOR_CORES
+        { 64,  64, 8},
+};
+
+// ------------------------------------------------------------
 
 template <int mmq_y> static __device__ __forceinline__ void allocate_tiles_q4_0(int ** x_ql, half2 ** x_dm, int ** x_qh, int ** x_sc) {
     GGML_UNUSED(x_qh);
@@ -697,11 +826,7 @@ template <int mmq_y, int nwarps, bool need_check> static __device__ __forceinlin
 
         const block_q4_K * bxi = bx0 + i*blocks_per_row + kbxd;
 
-#if QK_K == 256
         x_dm[i * (WARP_SIZE/QI4_K) + i / QI4_K + kbxd] = bxi->dm;
-#else
-        x_dm[i * (WARP_SIZE/QI4_K) + i / QI4_K + kbxd] = {bxi->dm[0], bxi->dm[1]};
-#endif
     }
 
 #pragma unroll
@@ -804,9 +929,7 @@ template <int mmq_y, int nwarps, bool need_check> static __device__ __forceinlin
 
         const block_q5_K * bxi = bx0 + i*blocks_per_row + kbxd;
 
-#if QK_K == 256
         x_dm[i * (WARP_SIZE/QI5_K) + i / QI5_K + kbxd] = bxi->dm;
-#endif
     }
 
 #pragma unroll
@@ -943,25 +1066,6 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1_mul_mat(
     return vec_dot_q6_K_q8_1_impl_mmq(&x_ql[index_x], &y_qs[index_y], sc, x_dmf[i * (WARP_SIZE/QI6_K) + i/QI6_K], &y_df[index_y/QI8_1]);
 }
 
-#define  MMQ_X_Q4_0_RDNA2  64
-#define  MMQ_Y_Q4_0_RDNA2  128
-#define NWARPS_Q4_0_RDNA2  8
-#define  MMQ_X_Q4_0_RDNA1  64
-#define  MMQ_Y_Q4_0_RDNA1  64
-#define NWARPS_Q4_0_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q4_0_AMPERE 4
-#define  MMQ_Y_Q4_0_AMPERE 32
-#define NWARPS_Q4_0_AMPERE 4
-#else
-#define  MMQ_X_Q4_0_AMPERE 64
-#define  MMQ_Y_Q4_0_AMPERE 128
-#define NWARPS_Q4_0_AMPERE 4
-#endif
-#define  MMQ_X_Q4_0_PASCAL 64
-#define  MMQ_Y_Q4_0_PASCAL 64
-#define NWARPS_Q4_0_PASCAL 8
-
 template <int qk, int qr, int qi, bool need_sum, typename block_q_t, int mmq_x, int mmq_y, int nwarps,
               allocate_tiles_cuda_t allocate_tiles, load_tiles_cuda_t load_tiles, int vdr, vec_dot_q_mul_mat_cuda_t vec_dot>
 static __device__ __forceinline__ void mul_mat_q(
@@ -1072,1107 +1176,275 @@ static __device__ __forceinline__ void mul_mat_q(
     }
 }
 
+static constexpr __device__ mmq_arch_config_t get_arch_config_device(mmq_config_t mmq_config) {
+
+#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
+
+#if defined(RDNA3) || defined(RDNA2)
+    return mmq_config.rdna2;
+#else
+    return mmq_config.rdna1;
+#endif // defined(RDNA3) || defined(RDNA2)
+
+#else
+
+#if __CUDA_ARCH__ >= CC_VOLTA
+    return mmq_config.ampere;
+#else
+    return mmq_config.pascal;
+#endif // __CUDA_ARCH__ >= CC_VOLTA
+
+#endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
+}
+
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q4_0_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q4_0.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
     mul_mat_q4_0(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q4_0_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q4_0_RDNA2;
-    const int nwarps = NWARPS_Q4_0_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q4_0_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q4_0_RDNA1;
-    const int nwarps = NWARPS_Q4_0_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q4_0);
 
-    mul_mat_q<QK4_0, QR4_0, QI4_0, true, block_q4_0, mmq_x, mmq_y, nwarps, allocate_tiles_q4_0<mmq_y>,
-        load_tiles_q4_0<mmq_y, nwarps, need_check>, VDR_Q4_0_Q8_1_MMQ, vec_dot_q4_0_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q4_0_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q4_0_AMPERE;
-    const int nwarps = NWARPS_Q4_0_AMPERE;
-
-    mul_mat_q<QK4_0, QR4_0, QI4_0, true, block_q4_0, mmq_x, mmq_y, nwarps, allocate_tiles_q4_0<mmq_y>,
-        load_tiles_q4_0<mmq_y, nwarps, need_check>, VDR_Q4_0_Q8_1_MMQ, vec_dot_q4_0_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q4_0_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q4_0_PASCAL;
-    const int nwarps = NWARPS_Q4_0_PASCAL;
-
-    mul_mat_q<QK4_0, QR4_0, QI4_0, true, block_q4_0, mmq_x, mmq_y, nwarps, allocate_tiles_q4_0<mmq_y>,
-        load_tiles_q4_0<mmq_y, nwarps, need_check>, VDR_Q4_0_Q8_1_MMQ, vec_dot_q4_0_q8_1_mul_mat>
+    mul_mat_q<QK4_0, QR4_0, QI4_0, true, block_q4_0, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q4_0<arch_config.y>,
+        load_tiles_q4_0<arch_config.y, arch_config.nwarps, need_check>, VDR_Q4_0_Q8_1_MMQ, vec_dot_q4_0_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q4_0_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q4_1_RDNA2  64
-#define  MMQ_Y_Q4_1_RDNA2  128
-#define NWARPS_Q4_1_RDNA2  8
-#define  MMQ_X_Q4_1_RDNA1  64
-#define  MMQ_Y_Q4_1_RDNA1  64
-#define NWARPS_Q4_1_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q4_1_AMPERE 4
-#define  MMQ_Y_Q4_1_AMPERE 32
-#define NWARPS_Q4_1_AMPERE 4
-#else
-#define  MMQ_X_Q4_1_AMPERE 64
-#define  MMQ_Y_Q4_1_AMPERE 128
-#define NWARPS_Q4_1_AMPERE 4
-#endif
-#define  MMQ_X_Q4_1_PASCAL 64
-#define  MMQ_Y_Q4_1_PASCAL 64
-#define NWARPS_Q4_1_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q4_1_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q4_1.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #elif __CUDA_ARCH__ < CC_VOLTA
-    __launch_bounds__(WARP_SIZE*NWARPS_Q4_1_PASCAL, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q4_1.pascal.nwarps, 2)
 #endif // __CUDA_ARCH__ < CC_VOLTA
     mul_mat_q4_1(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q4_1_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q4_1_RDNA2;
-    const int nwarps = NWARPS_Q4_1_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q4_1_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q4_1_RDNA1;
-    const int nwarps = NWARPS_Q4_1_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q4_1);
 
-    mul_mat_q<QK4_1, QR4_1, QI4_1, true, block_q4_1, mmq_x, mmq_y, nwarps, allocate_tiles_q4_1<mmq_y>,
-        load_tiles_q4_1<mmq_y, nwarps, need_check>, VDR_Q4_1_Q8_1_MMQ, vec_dot_q4_1_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q4_1_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q4_1_AMPERE;
-    const int nwarps = NWARPS_Q4_1_AMPERE;
-
-    mul_mat_q<QK4_1, QR4_1, QI4_1, true, block_q4_1, mmq_x, mmq_y, nwarps, allocate_tiles_q4_1<mmq_y>,
-        load_tiles_q4_1<mmq_y, nwarps, need_check>, VDR_Q4_1_Q8_1_MMQ, vec_dot_q4_1_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q4_1_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q4_1_PASCAL;
-    const int nwarps = NWARPS_Q4_1_PASCAL;
-
-    mul_mat_q<QK4_1, QR4_1, QI4_1, true, block_q4_1, mmq_x, mmq_y, nwarps, allocate_tiles_q4_1<mmq_y>,
-        load_tiles_q4_1<mmq_y, nwarps, need_check>, VDR_Q4_1_Q8_1_MMQ, vec_dot_q4_1_q8_1_mul_mat>
+    mul_mat_q<QK4_1, QR4_1, QI4_1, true, block_q4_1, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q4_1<arch_config.y>,
+        load_tiles_q4_1<arch_config.y, arch_config.nwarps, need_check>, VDR_Q4_1_Q8_1_MMQ, vec_dot_q4_1_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q4_1_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q5_0_RDNA2  64
-#define  MMQ_Y_Q5_0_RDNA2  128
-#define NWARPS_Q5_0_RDNA2  8
-#define  MMQ_X_Q5_0_RDNA1  64
-#define  MMQ_Y_Q5_0_RDNA1  64
-#define NWARPS_Q5_0_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q5_0_AMPERE 4
-#define  MMQ_Y_Q5_0_AMPERE 32
-#define NWARPS_Q5_0_AMPERE 4
-#else
-#define  MMQ_X_Q5_0_AMPERE 128
-#define  MMQ_Y_Q5_0_AMPERE 64
-#define NWARPS_Q5_0_AMPERE 4
-#endif
-#define  MMQ_X_Q5_0_PASCAL 64
-#define  MMQ_Y_Q5_0_PASCAL 64
-#define NWARPS_Q5_0_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q5_0_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q5_0.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
     mul_mat_q5_0(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q5_0_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q5_0_RDNA2;
-    const int nwarps = NWARPS_Q5_0_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q5_0_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q5_0_RDNA1;
-    const int nwarps = NWARPS_Q5_0_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q5_0);
 
-    mul_mat_q<QK5_0, QR5_0, QI5_0, false, block_q5_0, mmq_x, mmq_y, nwarps, allocate_tiles_q5_0<mmq_y>,
-        load_tiles_q5_0<mmq_y, nwarps, need_check>, VDR_Q5_0_Q8_1_MMQ, vec_dot_q5_0_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q5_0_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q5_0_AMPERE;
-    const int nwarps = NWARPS_Q5_0_AMPERE;
-
-    mul_mat_q<QK5_0, QR5_0, QI5_0, false, block_q5_0, mmq_x, mmq_y, nwarps, allocate_tiles_q5_0<mmq_y>,
-        load_tiles_q5_0<mmq_y, nwarps, need_check>, VDR_Q5_0_Q8_1_MMQ, vec_dot_q5_0_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q5_0_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q5_0_PASCAL;
-    const int nwarps = NWARPS_Q5_0_PASCAL;
-
-    mul_mat_q<QK5_0, QR5_0, QI5_0, false, block_q5_0, mmq_x, mmq_y, nwarps, allocate_tiles_q5_0<mmq_y>,
-        load_tiles_q5_0<mmq_y, nwarps, need_check>, VDR_Q5_0_Q8_1_MMQ, vec_dot_q5_0_q8_1_mul_mat>
+    mul_mat_q<QK5_0, QR5_0, QI5_0, false, block_q5_0, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q5_0<arch_config.y>,
+        load_tiles_q5_0<arch_config.y, arch_config.nwarps, need_check>, VDR_Q5_0_Q8_1_MMQ, vec_dot_q5_0_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q5_0_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q5_1_RDNA2  64
-#define  MMQ_Y_Q5_1_RDNA2  128
-#define NWARPS_Q5_1_RDNA2  8
-#define  MMQ_X_Q5_1_RDNA1  64
-#define  MMQ_Y_Q5_1_RDNA1  64
-#define NWARPS_Q5_1_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q5_1_AMPERE 4
-#define  MMQ_Y_Q5_1_AMPERE 32
-#define NWARPS_Q5_1_AMPERE 4
-#else
-#define  MMQ_X_Q5_1_AMPERE 128
-#define  MMQ_Y_Q5_1_AMPERE 64
-#define NWARPS_Q5_1_AMPERE 4
-#endif
-#define  MMQ_X_Q5_1_PASCAL 64
-#define  MMQ_Y_Q5_1_PASCAL 64
-#define NWARPS_Q5_1_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q5_1_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q5_1.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 mul_mat_q5_1(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q5_1_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q5_1_RDNA2;
-    const int nwarps = NWARPS_Q5_1_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q5_1_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q5_1_RDNA1;
-    const int nwarps = NWARPS_Q5_1_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q5_1);
 
-    mul_mat_q<QK5_1, QR5_1, QI5_1, true, block_q5_1, mmq_x, mmq_y, nwarps, allocate_tiles_q5_1<mmq_y>,
-        load_tiles_q5_1<mmq_y, nwarps, need_check>, VDR_Q5_1_Q8_1_MMQ, vec_dot_q5_1_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q5_1_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q5_1_AMPERE;
-    const int nwarps = NWARPS_Q5_1_AMPERE;
-
-    mul_mat_q<QK5_1, QR5_1, QI5_1, true, block_q5_1, mmq_x, mmq_y, nwarps, allocate_tiles_q5_1<mmq_y>,
-        load_tiles_q5_1<mmq_y, nwarps, need_check>, VDR_Q5_1_Q8_1_MMQ, vec_dot_q5_1_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q5_1_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q5_1_PASCAL;
-    const int nwarps = NWARPS_Q5_1_PASCAL;
-
-    mul_mat_q<QK5_1, QR5_1, QI5_1, true, block_q5_1, mmq_x, mmq_y, nwarps, allocate_tiles_q5_1<mmq_y>,
-        load_tiles_q5_1<mmq_y, nwarps, need_check>, VDR_Q5_1_Q8_1_MMQ, vec_dot_q5_1_q8_1_mul_mat>
+    mul_mat_q<QK5_1, QR5_1, QI5_1, true, block_q5_1, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q5_1<arch_config.y>,
+        load_tiles_q5_1<arch_config.y, arch_config.nwarps, need_check>, VDR_Q5_1_Q8_1_MMQ, vec_dot_q5_1_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q5_1_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q8_0_RDNA2  64
-#define  MMQ_Y_Q8_0_RDNA2  128
-#define NWARPS_Q8_0_RDNA2  8
-#define  MMQ_X_Q8_0_RDNA1  64
-#define  MMQ_Y_Q8_0_RDNA1  64
-#define NWARPS_Q8_0_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q8_0_AMPERE 4
-#define  MMQ_Y_Q8_0_AMPERE 32
-#define NWARPS_Q8_0_AMPERE 4
-#else
-#define  MMQ_X_Q8_0_AMPERE 128
-#define  MMQ_Y_Q8_0_AMPERE 64
-#define NWARPS_Q8_0_AMPERE 4
-#endif
-#define  MMQ_X_Q8_0_PASCAL 64
-#define  MMQ_Y_Q8_0_PASCAL 64
-#define NWARPS_Q8_0_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q8_0_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q8_0.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
     mul_mat_q8_0(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q8_0_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q8_0_RDNA2;
-    const int nwarps = NWARPS_Q8_0_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q8_0_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q8_0_RDNA1;
-    const int nwarps = NWARPS_Q8_0_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q8_0);
 
-    mul_mat_q<QK8_0, QR8_0, QI8_0, false, block_q8_0, mmq_x, mmq_y, nwarps, allocate_tiles_q8_0<mmq_y>,
-        load_tiles_q8_0<mmq_y, nwarps, need_check>, VDR_Q8_0_Q8_1_MMQ, vec_dot_q8_0_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q8_0_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q8_0_AMPERE;
-    const int nwarps = NWARPS_Q8_0_AMPERE;
-
-    mul_mat_q<QK8_0, QR8_0, QI8_0, false, block_q8_0, mmq_x, mmq_y, nwarps, allocate_tiles_q8_0<mmq_y>,
-        load_tiles_q8_0<mmq_y, nwarps, need_check>, VDR_Q8_0_Q8_1_MMQ, vec_dot_q8_0_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q8_0_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q8_0_PASCAL;
-    const int nwarps = NWARPS_Q8_0_PASCAL;
-
-    mul_mat_q<QK8_0, QR8_0, QI8_0, false, block_q8_0, mmq_x, mmq_y, nwarps, allocate_tiles_q8_0<mmq_y>,
-        load_tiles_q8_0<mmq_y, nwarps, need_check>, VDR_Q8_0_Q8_1_MMQ, vec_dot_q8_0_q8_1_mul_mat>
+    mul_mat_q<QK8_0, QR8_0, QI8_0, false, block_q8_0, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q8_0<arch_config.y>,
+        load_tiles_q8_0<arch_config.y, arch_config.nwarps, need_check>, VDR_Q8_0_Q8_1_MMQ, vec_dot_q8_0_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q8_0_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q2_K_RDNA2  64
-#define  MMQ_Y_Q2_K_RDNA2  128
-#define NWARPS_Q2_K_RDNA2  8
-#define  MMQ_X_Q2_K_RDNA1  128
-#define  MMQ_Y_Q2_K_RDNA1  32
-#define NWARPS_Q2_K_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q2_K_AMPERE 4
-#define  MMQ_Y_Q2_K_AMPERE 32
-#define NWARPS_Q2_K_AMPERE 4
-#else
-#define  MMQ_X_Q2_K_AMPERE 64
-#define  MMQ_Y_Q2_K_AMPERE 128
-#define NWARPS_Q2_K_AMPERE 4
-#endif
-#define  MMQ_X_Q2_K_PASCAL 64
-#define  MMQ_Y_Q2_K_PASCAL 64
-#define NWARPS_Q2_K_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q2_K_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q2_K.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 mul_mat_q2_K(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q2_K_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q2_K_RDNA2;
-    const int nwarps = NWARPS_Q2_K_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q2_K_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q2_K_RDNA1;
-    const int nwarps = NWARPS_Q2_K_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q2_K);
 
-    mul_mat_q<QK_K, QR2_K, QI2_K, false, block_q2_K, mmq_x, mmq_y, nwarps, allocate_tiles_q2_K<mmq_y>,
-        load_tiles_q2_K<mmq_y, nwarps, need_check>, VDR_Q2_K_Q8_1_MMQ, vec_dot_q2_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q2_K_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q2_K_AMPERE;
-    const int nwarps = NWARPS_Q2_K_AMPERE;
-
-    mul_mat_q<QK_K, QR2_K, QI2_K, false, block_q2_K, mmq_x, mmq_y, nwarps, allocate_tiles_q2_K<mmq_y>,
-        load_tiles_q2_K<mmq_y, nwarps, need_check>, VDR_Q2_K_Q8_1_MMQ, vec_dot_q2_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q2_K_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q2_K_PASCAL;
-    const int nwarps = NWARPS_Q2_K_PASCAL;
-
-    mul_mat_q<QK_K, QR2_K, QI2_K, false, block_q2_K, mmq_x, mmq_y, nwarps, allocate_tiles_q2_K<mmq_y>,
-        load_tiles_q2_K<mmq_y, nwarps, need_check>, VDR_Q2_K_Q8_1_MMQ, vec_dot_q2_K_q8_1_mul_mat>
+    mul_mat_q<QK_K, QR2_K, QI2_K, false, block_q2_K, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q2_K<arch_config.y>,
+        load_tiles_q2_K<arch_config.y, arch_config.nwarps, need_check>, VDR_Q2_K_Q8_1_MMQ, vec_dot_q2_K_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q2_K_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q3_K_RDNA2  128
-#define  MMQ_Y_Q3_K_RDNA2  64
-#define NWARPS_Q3_K_RDNA2  8
-#define  MMQ_X_Q3_K_RDNA1  32
-#define  MMQ_Y_Q3_K_RDNA1  128
-#define NWARPS_Q3_K_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q3_K_AMPERE 4
-#define  MMQ_Y_Q3_K_AMPERE 32
-#define NWARPS_Q3_K_AMPERE 4
-#else
-#define  MMQ_X_Q3_K_AMPERE 128
-#define  MMQ_Y_Q3_K_AMPERE 128
-#define NWARPS_Q3_K_AMPERE 4
-#endif
-#define  MMQ_X_Q3_K_PASCAL 64
-#define  MMQ_Y_Q3_K_PASCAL 64
-#define NWARPS_Q3_K_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q3_K_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q3_K.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #elif __CUDA_ARCH__ < CC_VOLTA
-    __launch_bounds__(WARP_SIZE*NWARPS_Q3_K_PASCAL, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q3_K.pascal.nwarps, 2)
 #endif // __CUDA_ARCH__ < CC_VOLTA
     mul_mat_q3_K(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q3_K_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q3_K_RDNA2;
-    const int nwarps = NWARPS_Q3_K_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q3_K_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q3_K_RDNA1;
-    const int nwarps = NWARPS_Q3_K_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q3_K);
 
-    mul_mat_q<QK_K, QR3_K, QI3_K, false, block_q3_K, mmq_x, mmq_y, nwarps, allocate_tiles_q3_K<mmq_y>,
-        load_tiles_q3_K<mmq_y, nwarps, need_check>, VDR_Q3_K_Q8_1_MMQ, vec_dot_q3_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q3_K_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q3_K_AMPERE;
-    const int nwarps = NWARPS_Q3_K_AMPERE;
-
-    mul_mat_q<QK_K, QR3_K, QI3_K, false, block_q3_K, mmq_x, mmq_y, nwarps, allocate_tiles_q3_K<mmq_y>,
-        load_tiles_q3_K<mmq_y, nwarps, need_check>, VDR_Q3_K_Q8_1_MMQ, vec_dot_q3_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q3_K_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q3_K_PASCAL;
-    const int nwarps = NWARPS_Q3_K_PASCAL;
-
-    mul_mat_q<QK_K, QR3_K, QI3_K, false, block_q3_K, mmq_x, mmq_y, nwarps, allocate_tiles_q3_K<mmq_y>,
-        load_tiles_q3_K<mmq_y, nwarps, need_check>, VDR_Q3_K_Q8_1_MMQ, vec_dot_q3_K_q8_1_mul_mat>
+    mul_mat_q<QK_K, QR3_K, QI3_K, false, block_q3_K, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q3_K<arch_config.y>,
+        load_tiles_q3_K<arch_config.y, arch_config.nwarps, need_check>, VDR_Q3_K_Q8_1_MMQ, vec_dot_q3_K_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q3_K_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q4_K_RDNA2  64
-#define  MMQ_Y_Q4_K_RDNA2  128
-#define NWARPS_Q4_K_RDNA2  8
-#define  MMQ_X_Q4_K_RDNA1  32
-#define  MMQ_Y_Q4_K_RDNA1  64
-#define NWARPS_Q4_K_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q4_K_AMPERE 4
-#define  MMQ_Y_Q4_K_AMPERE 32
-#define NWARPS_Q4_K_AMPERE 4
-#else
-#define  MMQ_X_Q4_K_AMPERE 64
-#define  MMQ_Y_Q4_K_AMPERE 128
-#define NWARPS_Q4_K_AMPERE 4
-#endif
-#define  MMQ_X_Q4_K_PASCAL 64
-#define  MMQ_Y_Q4_K_PASCAL 64
-#define NWARPS_Q4_K_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q4_K_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q4_K.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #elif __CUDA_ARCH__ < CC_VOLTA
-    __launch_bounds__(WARP_SIZE*NWARPS_Q4_K_PASCAL, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q4_K.pascal.nwarps, 2)
 #endif // __CUDA_ARCH__ < CC_VOLTA
     mul_mat_q4_K(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q4_K_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q4_K_RDNA2;
-    const int nwarps = NWARPS_Q4_K_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q4_K_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q4_K_RDNA1;
-    const int nwarps = NWARPS_Q4_K_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q4_K);
 
-    mul_mat_q<QK_K, QR4_K, QI4_K, true, block_q4_K, mmq_x, mmq_y, nwarps, allocate_tiles_q4_K<mmq_y>,
-        load_tiles_q4_K<mmq_y, nwarps, need_check>, VDR_Q4_K_Q8_1_MMQ, vec_dot_q4_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q4_K_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q4_K_AMPERE;
-    const int nwarps = NWARPS_Q4_K_AMPERE;
-
-    mul_mat_q<QK_K, QR4_K, QI4_K, true, block_q4_K, mmq_x, mmq_y, nwarps, allocate_tiles_q4_K<mmq_y>,
-        load_tiles_q4_K<mmq_y, nwarps, need_check>, VDR_Q4_K_Q8_1_MMQ, vec_dot_q4_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q4_K_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q4_K_PASCAL;
-    const int nwarps = NWARPS_Q4_K_PASCAL;
-
-    mul_mat_q<QK_K, QR4_K, QI4_K, true, block_q4_K, mmq_x, mmq_y, nwarps, allocate_tiles_q4_K<mmq_y>,
-        load_tiles_q4_K<mmq_y, nwarps, need_check>, VDR_Q4_K_Q8_1_MMQ, vec_dot_q4_K_q8_1_mul_mat>
+    mul_mat_q<QK_K, QR4_K, QI4_K, true, block_q4_K, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q4_K<arch_config.y>,
+        load_tiles_q4_K<arch_config.y, arch_config.nwarps, need_check>, VDR_Q4_K_Q8_1_MMQ, vec_dot_q4_K_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q4_K_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q5_K_RDNA2  64
-#define  MMQ_Y_Q5_K_RDNA2  128
-#define NWARPS_Q5_K_RDNA2  8
-#define  MMQ_X_Q5_K_RDNA1  32
-#define  MMQ_Y_Q5_K_RDNA1  64
-#define NWARPS_Q5_K_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q5_K_AMPERE 4
-#define  MMQ_Y_Q5_K_AMPERE 32
-#define NWARPS_Q5_K_AMPERE 4
-#else
-#define  MMQ_X_Q5_K_AMPERE 64
-#define  MMQ_Y_Q5_K_AMPERE 128
-#define NWARPS_Q5_K_AMPERE 4
-#endif
-#define  MMQ_X_Q5_K_PASCAL 64
-#define  MMQ_Y_Q5_K_PASCAL 64
-#define NWARPS_Q5_K_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q5_K_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q5_K.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #endif // defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 mul_mat_q5_K(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q5_K_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q5_K_RDNA2;
-    const int nwarps = NWARPS_Q5_K_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q5_K_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q5_K_RDNA1;
-    const int nwarps = NWARPS_Q5_K_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q5_K);
 
-    mul_mat_q<QK_K, QR5_K, QI5_K, true, block_q5_K, mmq_x, mmq_y, nwarps, allocate_tiles_q5_K<mmq_y>,
-        load_tiles_q5_K<mmq_y, nwarps, need_check>, VDR_Q5_K_Q8_1_MMQ, vec_dot_q5_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q5_K_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q5_K_AMPERE;
-    const int nwarps = NWARPS_Q5_K_AMPERE;
-
-    mul_mat_q<QK_K, QR5_K, QI5_K, true, block_q5_K, mmq_x, mmq_y, nwarps, allocate_tiles_q5_K<mmq_y>,
-        load_tiles_q5_K<mmq_y, nwarps, need_check>, VDR_Q5_K_Q8_1_MMQ, vec_dot_q5_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q5_K_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q5_K_PASCAL;
-    const int nwarps = NWARPS_Q5_K_PASCAL;
-
-    mul_mat_q<QK_K, QR5_K, QI5_K, true, block_q5_K, mmq_x, mmq_y, nwarps, allocate_tiles_q5_K<mmq_y>,
-        load_tiles_q5_K<mmq_y, nwarps, need_check>, VDR_Q5_K_Q8_1_MMQ, vec_dot_q5_K_q8_1_mul_mat>
+    mul_mat_q<QK_K, QR5_K, QI5_K, true, block_q5_K, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q5_K<arch_config.y>,
+        load_tiles_q5_K<arch_config.y, arch_config.nwarps, need_check>, VDR_Q5_K_Q8_1_MMQ, vec_dot_q5_K_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q5_K_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-#define  MMQ_X_Q6_K_RDNA2  64
-#define  MMQ_Y_Q6_K_RDNA2  128
-#define NWARPS_Q6_K_RDNA2  8
-#define  MMQ_X_Q6_K_RDNA1  32
-#define  MMQ_Y_Q6_K_RDNA1  64
-#define NWARPS_Q6_K_RDNA1  8
-#if defined(CUDA_USE_TENSOR_CORES)
-#define  MMQ_X_Q6_K_AMPERE 4
-#define  MMQ_Y_Q6_K_AMPERE 32
-#define NWARPS_Q6_K_AMPERE 4
-#else
-#define  MMQ_X_Q6_K_AMPERE 64
-#define  MMQ_Y_Q6_K_AMPERE 64
-#define NWARPS_Q6_K_AMPERE 4
-#endif
-#define  MMQ_X_Q6_K_PASCAL 64
-#define  MMQ_Y_Q6_K_PASCAL 64
-#define NWARPS_Q6_K_PASCAL 8
-
 template <bool need_check> static __global__ void
 #if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
 #if defined(RDNA3) || defined(RDNA2)
-    __launch_bounds__(WARP_SIZE*NWARPS_Q6_K_RDNA2, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q6_K.rdna2.nwarps, 2)
 #endif // defined(RDNA3) || defined(RDNA2)
 #elif __CUDA_ARCH__ < CC_VOLTA
-    __launch_bounds__(WARP_SIZE*NWARPS_Q6_K_PASCAL, 2)
+    __launch_bounds__(WARP_SIZE*MMQ_CONFIG_Q4_K.pascal.nwarps, 2)
 #endif // __CUDA_ARCH__ < CC_VOLTA
     mul_mat_q6_K(
     const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst,
     const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst) {
 
-#if defined(GGML_USE_HIPBLAS) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2)
-    const int mmq_x  =  MMQ_X_Q6_K_RDNA2;
-    const int mmq_y  =  MMQ_Y_Q6_K_RDNA2;
-    const int nwarps = NWARPS_Q6_K_RDNA2;
-#else
-    const int mmq_x  =  MMQ_X_Q6_K_RDNA1;
-    const int mmq_y  =  MMQ_Y_Q6_K_RDNA1;
-    const int nwarps = NWARPS_Q6_K_RDNA1;
-#endif // defined(RDNA3) || defined(RDNA2)
+#if __CUDA_ARCH__ >= MIN_CC_DP4A
+    constexpr mmq_arch_config_t arch_config = get_arch_config_device(MMQ_CONFIG_Q6_K);
 
-    mul_mat_q<QK_K, QR6_K, QI6_K, false, block_q6_K, mmq_x, mmq_y, nwarps, allocate_tiles_q6_K<mmq_y>,
-        load_tiles_q6_K<mmq_y, nwarps, need_check>, VDR_Q6_K_Q8_1_MMQ, vec_dot_q6_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= CC_VOLTA
-    const int mmq_x  =  MMQ_X_Q6_K_AMPERE;
-    const int mmq_y  =  MMQ_Y_Q6_K_AMPERE;
-    const int nwarps = NWARPS_Q6_K_AMPERE;
-
-    mul_mat_q<QK_K, QR6_K, QI6_K, false, block_q6_K, mmq_x, mmq_y, nwarps, allocate_tiles_q6_K<mmq_y>,
-        load_tiles_q6_K<mmq_y, nwarps, need_check>, VDR_Q6_K_Q8_1_MMQ, vec_dot_q6_K_q8_1_mul_mat>
-        (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-
-#elif __CUDA_ARCH__ >= MIN_CC_DP4A
-    const int mmq_x  =  MMQ_X_Q6_K_PASCAL;
-    const int mmq_y  =  MMQ_Y_Q6_K_PASCAL;
-    const int nwarps = NWARPS_Q6_K_PASCAL;
-
-    mul_mat_q<QK_K, QR6_K, QI6_K, false, block_q6_K, mmq_x, mmq_y, nwarps, allocate_tiles_q6_K<mmq_y>,
-        load_tiles_q6_K<mmq_y, nwarps, need_check>, VDR_Q6_K_Q8_1_MMQ, vec_dot_q6_K_q8_1_mul_mat>
+    mul_mat_q<QK_K, QR6_K, QI6_K, false, block_q6_K, arch_config.x, arch_config.y, arch_config.nwarps, allocate_tiles_q6_K<arch_config.y>,
+        load_tiles_q6_K<arch_config.y, arch_config.nwarps, need_check>, VDR_Q6_K_Q8_1_MMQ, vec_dot_q6_K_q8_1_mul_mat>
         (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
 #else
+    GGML_UNUSED(get_arch_config_device);
     GGML_UNUSED(vec_dot_q6_K_q8_1_mul_mat);
     NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= CC_VOLTA
+#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
 }
 
-static void ggml_mul_mat_q4_0_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q4_0_RDNA2;
-        mmq_y  =  MMQ_Y_Q4_0_RDNA2;
-        nwarps = NWARPS_Q4_0_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q4_0_RDNA1;
-        mmq_y  =  MMQ_Y_Q4_0_RDNA1;
-        nwarps = NWARPS_Q4_0_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q4_0_AMPERE;
-        mmq_y  =  MMQ_Y_Q4_0_AMPERE;
-        nwarps = NWARPS_Q4_0_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q4_0_PASCAL;
-        mmq_y  =  MMQ_Y_Q4_0_PASCAL;
-        nwarps = NWARPS_Q4_0_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q4_0<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q4_0<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q4_1_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q4_1_RDNA2;
-        mmq_y  =  MMQ_Y_Q4_1_RDNA2;
-        nwarps = NWARPS_Q4_1_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q4_1_RDNA1;
-        mmq_y  =  MMQ_Y_Q4_1_RDNA1;
-        nwarps = NWARPS_Q4_1_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q4_1_AMPERE;
-        mmq_y  =  MMQ_Y_Q4_1_AMPERE;
-        nwarps = NWARPS_Q4_1_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q4_1_PASCAL;
-        mmq_y  =  MMQ_Y_Q4_1_PASCAL;
-        nwarps = NWARPS_Q4_1_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q4_1<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q4_1<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q5_0_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q5_0_RDNA2;
-        mmq_y  =  MMQ_Y_Q5_0_RDNA2;
-        nwarps = NWARPS_Q5_0_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q5_0_RDNA1;
-        mmq_y  =  MMQ_Y_Q5_0_RDNA1;
-        nwarps = NWARPS_Q5_0_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q5_0_AMPERE;
-        mmq_y  =  MMQ_Y_Q5_0_AMPERE;
-        nwarps = NWARPS_Q5_0_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q5_0_PASCAL;
-        mmq_y  =  MMQ_Y_Q5_0_PASCAL;
-        nwarps = NWARPS_Q5_0_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q5_0<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q5_0<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q5_1_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q5_1_RDNA2;
-        mmq_y  =  MMQ_Y_Q5_1_RDNA2;
-        nwarps = NWARPS_Q5_1_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q5_1_RDNA1;
-        mmq_y  =  MMQ_Y_Q5_1_RDNA1;
-        nwarps = NWARPS_Q5_1_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q5_1_AMPERE;
-        mmq_y  =  MMQ_Y_Q5_1_AMPERE;
-        nwarps = NWARPS_Q5_1_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q5_1_PASCAL;
-        mmq_y  =  MMQ_Y_Q5_1_PASCAL;
-        nwarps = NWARPS_Q5_1_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q5_1<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q5_1<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q8_0_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q8_0_RDNA2;
-        mmq_y  =  MMQ_Y_Q8_0_RDNA2;
-        nwarps = NWARPS_Q8_0_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q8_0_RDNA1;
-        mmq_y  =  MMQ_Y_Q8_0_RDNA1;
-        nwarps = NWARPS_Q8_0_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q8_0_AMPERE;
-        mmq_y  =  MMQ_Y_Q8_0_AMPERE;
-        nwarps = NWARPS_Q8_0_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q8_0_PASCAL;
-        mmq_y  =  MMQ_Y_Q8_0_PASCAL;
-        nwarps = NWARPS_Q8_0_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q8_0<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q8_0<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q2_K_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q2_K_RDNA2;
-        mmq_y  =  MMQ_Y_Q2_K_RDNA2;
-        nwarps = NWARPS_Q2_K_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q2_K_RDNA1;
-        mmq_y  =  MMQ_Y_Q2_K_RDNA1;
-        nwarps = NWARPS_Q2_K_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q2_K_AMPERE;
-        mmq_y  =  MMQ_Y_Q2_K_AMPERE;
-        nwarps = NWARPS_Q2_K_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q2_K_PASCAL;
-        mmq_y  =  MMQ_Y_Q2_K_PASCAL;
-        nwarps = NWARPS_Q2_K_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q2_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q2_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q3_K_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-#if QK_K == 256
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q3_K_RDNA2;
-        mmq_y  =  MMQ_Y_Q3_K_RDNA2;
-        nwarps = NWARPS_Q3_K_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q3_K_RDNA1;
-        mmq_y  =  MMQ_Y_Q3_K_RDNA1;
-        nwarps = NWARPS_Q3_K_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q3_K_AMPERE;
-        mmq_y  =  MMQ_Y_Q3_K_AMPERE;
-        nwarps = NWARPS_Q3_K_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q3_K_PASCAL;
-        mmq_y  =  MMQ_Y_Q3_K_PASCAL;
-        nwarps = NWARPS_Q3_K_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q3_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q3_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-#endif
-}
-
-static void ggml_mul_mat_q4_K_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q4_K_RDNA2;
-        mmq_y  =  MMQ_Y_Q4_K_RDNA2;
-        nwarps = NWARPS_Q4_K_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q4_K_RDNA1;
-        mmq_y  =  MMQ_Y_Q4_K_RDNA1;
-        nwarps = NWARPS_Q4_K_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q4_K_AMPERE;
-        mmq_y  =  MMQ_Y_Q4_K_AMPERE;
-        nwarps = NWARPS_Q4_K_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q4_K_PASCAL;
-        mmq_y  =  MMQ_Y_Q4_K_PASCAL;
-        nwarps = NWARPS_Q4_K_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q4_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q4_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q5_K_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q5_K_RDNA2;
-        mmq_y  =  MMQ_Y_Q5_K_RDNA2;
-        nwarps = NWARPS_Q5_K_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q5_K_RDNA1;
-        mmq_y  =  MMQ_Y_Q5_K_RDNA1;
-        nwarps = NWARPS_Q5_K_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q5_K_AMPERE;
-        mmq_y  =  MMQ_Y_Q5_K_AMPERE;
-        nwarps = NWARPS_Q5_K_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q5_K_PASCAL;
-        mmq_y  =  MMQ_Y_Q5_K_PASCAL;
-        nwarps = NWARPS_Q5_K_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q5_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q5_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
-
-static void ggml_mul_mat_q6_K_q8_1_cuda(
-    const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x,
-    const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) {
-
-    int id = ggml_cuda_get_device();
-    const int compute_capability = ggml_cuda_info().devices[id].cc;
-
-    int mmq_x, mmq_y, nwarps;
-    if (compute_capability >= CC_RDNA2) {
-        mmq_x  =  MMQ_X_Q6_K_RDNA2;
-        mmq_y  =  MMQ_Y_Q6_K_RDNA2;
-        nwarps = NWARPS_Q6_K_RDNA2;
-    } else if (compute_capability >= CC_OFFSET_AMD) {
-        mmq_x  =  MMQ_X_Q6_K_RDNA1;
-        mmq_y  =  MMQ_Y_Q6_K_RDNA1;
-        nwarps = NWARPS_Q6_K_RDNA1;
-    } else if (compute_capability >= CC_VOLTA) {
-        mmq_x  =  MMQ_X_Q6_K_AMPERE;
-        mmq_y  =  MMQ_Y_Q6_K_AMPERE;
-        nwarps = NWARPS_Q6_K_AMPERE;
-    } else if (compute_capability >= MIN_CC_DP4A) {
-        mmq_x  =  MMQ_X_Q6_K_PASCAL;
-        mmq_y  =  MMQ_Y_Q6_K_PASCAL;
-        nwarps = NWARPS_Q6_K_PASCAL;
-    } else {
-        GGML_ASSERT(false);
-    }
-
-    const int block_num_x = (nrows_x + mmq_y - 1) / mmq_y;
-    const int block_num_y = (ncols_y + mmq_x - 1) / mmq_x;
-    const dim3 block_nums(block_num_x, block_num_y, 1);
-    const dim3 block_dims(WARP_SIZE, nwarps, 1);
-
-    if (nrows_x % mmq_y == 0) {
-        const bool need_check = false;
-        mul_mat_q6_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    } else {
-        const bool need_check = true;
-        mul_mat_q6_K<need_check><<<block_nums, block_dims, 0, stream>>>
-            (vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst);
-    }
-}
+#define MMQ_SWITCH_CASE(type_suffix)                                                                        \
+    case GGML_TYPE_Q##type_suffix: if (row_diff % arch_config.y == 0) {                                     \
+        const bool need_check = false;                                                                      \
+        mul_mat_q##type_suffix<need_check><<<block_nums, block_dims, 0, stream>>>                           \
+            (src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst); \
+    } else {                                                                                                \
+        const bool need_check = true;                                                                       \
+        mul_mat_q##type_suffix<need_check><<<block_nums, block_dims, 0, stream>>>                           \
+            (src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst); \
+    } break;                                                                                                \
 
 void ggml_cuda_op_mul_mat_q(
     ggml_backend_cuda_context & ctx,
@@ -2190,47 +1462,84 @@ void ggml_cuda_op_mul_mat_q(
     const int64_t row_diff = row_high - row_low;
 
     int id = ggml_cuda_get_device();
+    const int compute_capability = ggml_cuda_info().devices[id].cc;
 
     // the main device has a larger memory buffer to hold the results from all GPUs
     // nrows_dst == nrows of the matrix that the kernel writes into
     const int64_t nrows_dst = id == ctx.device ? ne0 : row_diff;
 
+    mmq_config_t mmq_config;
+
     switch (src0->type) {
         case GGML_TYPE_Q4_0:
-            ggml_mul_mat_q4_0_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q4_0;
             break;
         case GGML_TYPE_Q4_1:
-            ggml_mul_mat_q4_1_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q4_1;
             break;
         case GGML_TYPE_Q5_0:
-            ggml_mul_mat_q5_0_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q5_0;
             break;
         case GGML_TYPE_Q5_1:
-            ggml_mul_mat_q5_1_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q5_1;
             break;
         case GGML_TYPE_Q8_0:
-            ggml_mul_mat_q8_0_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q8_0;
             break;
         case GGML_TYPE_Q2_K:
-            ggml_mul_mat_q2_K_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q2_K;
             break;
         case GGML_TYPE_Q3_K:
-            ggml_mul_mat_q3_K_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q3_K;
             break;
         case GGML_TYPE_Q4_K:
-            ggml_mul_mat_q4_K_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q4_K;
             break;
         case GGML_TYPE_Q5_K:
-            ggml_mul_mat_q5_K_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q5_K;
             break;
         case GGML_TYPE_Q6_K:
-            ggml_mul_mat_q6_K_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_ncols, src1_padded_row_size, nrows_dst, stream);
+            mmq_config = MMQ_CONFIG_Q6_K;
             break;
         default:
             GGML_ASSERT(false);
             break;
     }
 
+    mmq_arch_config_t arch_config;
+    if (compute_capability >= CC_RDNA2) {
+        arch_config = mmq_config.rdna2;
+    } else if (compute_capability >= CC_OFFSET_AMD) {
+        arch_config = mmq_config.rdna1;
+    } else if (compute_capability >= CC_VOLTA) {
+        arch_config = mmq_config.ampere;
+    } else if (compute_capability >= MIN_CC_DP4A) {
+        arch_config = mmq_config.pascal;
+    } else {
+        GGML_ASSERT(false);
+    }
+
+    const int block_num_x = (row_diff   + arch_config.y - 1) / arch_config.y;
+    const int block_num_y = (src1_ncols + arch_config.x - 1) / arch_config.x;
+    const dim3 block_nums(block_num_x, block_num_y, 1);
+    const dim3 block_dims(WARP_SIZE, arch_config.nwarps, 1);
+
+    switch (src0->type) {
+        MMQ_SWITCH_CASE(4_0)
+        MMQ_SWITCH_CASE(4_1)
+        MMQ_SWITCH_CASE(5_0)
+        MMQ_SWITCH_CASE(5_1)
+        MMQ_SWITCH_CASE(8_0)
+        MMQ_SWITCH_CASE(2_K)
+        MMQ_SWITCH_CASE(3_K)
+        MMQ_SWITCH_CASE(4_K)
+        MMQ_SWITCH_CASE(5_K)
+        MMQ_SWITCH_CASE(6_K)
+        default:
+            GGML_ASSERT(false);
+            break;
+    }
+
     GGML_UNUSED(src1);
     GGML_UNUSED(dst);
     GGML_UNUSED(src1_ddf_i);
diff --git a/ggml-cuda/rope.cu b/ggml-cuda/rope.cu
index 4b0d2e5ad..50f2cf415 100644
--- a/ggml-cuda/rope.cu
+++ b/ggml-cuda/rope.cu
@@ -58,10 +58,10 @@ static __global__ void rope(
     dst[i + 1] = x0*sin_theta + x1*cos_theta;
 }
 
-template<typename T, bool has_pos>
+template<typename T, bool has_pos, bool has_freq_facs>
 static __global__ void rope_neox(
     const T * x, T * dst, int ncols, int n_dims, const int32_t * pos, float freq_scale, int p_delta_rows,
-    float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, float inv_ndims
+    float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, float inv_ndims, const float * freq_factors
 ) {
     const int col = 2*(blockDim.y*blockIdx.y + threadIdx.y);
 
@@ -88,7 +88,9 @@ static __global__ void rope_neox(
     float cur_rot = inv_ndims * ic - ib;
 
     const int p = has_pos ? pos[i2] : 0;
-    const float theta_base = p*freq_scale*powf(theta_scale, col/2.0f);
+    const float freq_factor = has_freq_facs ? freq_factors[ic/2] : 1.0f;
+
+    const float theta_base = p*freq_scale*powf(theta_scale, col/2.0f)/freq_factor;
 
     float cos_theta, sin_theta;
     rope_yarn(theta_base, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor, &cos_theta, &sin_theta);
@@ -164,7 +166,7 @@ static void rope_cuda(
 template<typename T>
 static void rope_neox_cuda(
     const T * x, T * dst, int ncols, int n_dims, int nrows, const int32_t * pos, float freq_scale, int p_delta_rows,
-    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, cudaStream_t stream
+    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, const float * freq_factors, cudaStream_t stream
 ) {
     GGML_ASSERT(ncols % 2 == 0);
     const dim3 block_dims(1, CUDA_ROPE_BLOCK_SIZE, 1);
@@ -175,15 +177,29 @@ static void rope_neox_cuda(
     const float inv_ndims = -1.0f / n_dims;
 
     if (pos == nullptr) {
-        rope_neox<T, false><<<block_nums, block_dims, 0, stream>>>(
-            x, dst, ncols, n_dims, pos, freq_scale, p_delta_rows, ext_factor, attn_factor, corr_dims,
-            theta_scale, inv_ndims
-        );
+        if (freq_factors == nullptr) {
+            rope_neox<T, false, false><<<block_nums, block_dims, 0, stream>>>(
+                x, dst, ncols, n_dims, pos, freq_scale, p_delta_rows, ext_factor, attn_factor, corr_dims,
+                theta_scale, inv_ndims, freq_factors
+                );
+        } else {
+            rope_neox<T, false, true><<<block_nums, block_dims, 0, stream>>>(
+                x, dst, ncols, n_dims, pos, freq_scale, p_delta_rows, ext_factor, attn_factor, corr_dims,
+                theta_scale, inv_ndims, freq_factors
+                );
+        }
     } else {
-        rope_neox<T, true><<<block_nums, block_dims, 0, stream>>>(
-            x, dst, ncols, n_dims, pos, freq_scale, p_delta_rows, ext_factor, attn_factor, corr_dims,
-            theta_scale, inv_ndims
-        );
+        if (freq_factors == nullptr) {
+            rope_neox<T, true, false><<<block_nums, block_dims, 0, stream>>>(
+                x, dst, ncols, n_dims, pos, freq_scale, p_delta_rows, ext_factor, attn_factor, corr_dims,
+                theta_scale, inv_ndims, freq_factors
+                );
+        } else {
+            rope_neox<T, true, true><<<block_nums, block_dims, 0, stream>>>(
+                x, dst, ncols, n_dims, pos, freq_scale, p_delta_rows, ext_factor, attn_factor, corr_dims,
+                theta_scale, inv_ndims, freq_factors
+                );
+        }
     }
 }
 
@@ -214,24 +230,27 @@ static void rope_cuda_f32(
 
 static void rope_neox_cuda_f16(
     const half * x, half * dst, int ncols, int n_dims, int nrows, const int32_t * pos, float freq_scale, int p_delta_rows,
-    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, cudaStream_t stream) {
+    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, const float * freq_factors, cudaStream_t stream) {
 
-    rope_neox_cuda<half>(x, dst, ncols, n_dims, nrows, pos, freq_scale, p_delta_rows, freq_base, ext_factor, attn_factor, corr_dims, stream);
+    rope_neox_cuda<half>(x, dst, ncols, n_dims, nrows, pos, freq_scale, p_delta_rows, freq_base, ext_factor, attn_factor, corr_dims, freq_factors, stream);
 }
 
 static void rope_neox_cuda_f32(
     const float * x, float * dst, int ncols, int n_dims, int nrows, const int32_t * pos, float freq_scale, int p_delta_rows,
-    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, cudaStream_t stream
+    float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, const float * freq_factors, cudaStream_t stream
 ) {
 
-    rope_neox_cuda<float>(x, dst, ncols, n_dims, nrows, pos, freq_scale, p_delta_rows, freq_base, ext_factor, attn_factor, corr_dims, stream);
+    rope_neox_cuda<float>(x, dst, ncols, n_dims, nrows, pos, freq_scale, p_delta_rows, freq_base, ext_factor, attn_factor, corr_dims, freq_factors, stream);
 }
 
 void ggml_cuda_op_rope(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
     const ggml_tensor * src0 = dst->src[0];
     const ggml_tensor * src1 = dst->src[1];
+    const ggml_tensor * src2 = dst->src[2];
+
     const float * src0_d = (const float *)src0->data;
     const float * src1_d = (const float *)src1->data;
+
     float * dst_d = (float *)dst->data;
     cudaStream_t stream = ctx.stream();
 
@@ -241,7 +260,6 @@ void ggml_cuda_op_rope(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
 
     const int64_t ne00 = src0->ne[0];
     const int64_t ne01 = src0->ne[1];
-    const int64_t ne2 = dst->ne[2];
     const int64_t nrows = ggml_nrows(src0);
 
     //const int n_past      = ((int32_t *) dst->op_params)[0];
@@ -259,16 +277,22 @@ void ggml_cuda_op_rope(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
     memcpy(&beta_fast,   (int32_t *) dst->op_params +  9, sizeof(float));
     memcpy(&beta_slow,   (int32_t *) dst->op_params + 10, sizeof(float));
 
+    const float * freq_factors = nullptr;
     const int32_t * pos = nullptr;
-    if ((mode & 1) == 0) {
-        GGML_ASSERT(src1->type == GGML_TYPE_I32);
-        GGML_ASSERT(src1->ne[0] == ne2);
-        pos = (const int32_t *) src1_d;
-    }
 
     const bool is_neox = mode & 2;
     const bool is_glm  = mode & 4;
 
+    pos = (const int32_t *) src1_d;
+
+    if (is_neox) {
+        if (src2 != nullptr) {
+            freq_factors = (const float *) src2->data;
+        }
+    } else {
+        GGML_ASSERT(src2 == nullptr && "TODO: freq_factors not implemented for !is_neox");
+    }
+
     rope_corr_dims corr_dims;
     ggml_rope_yarn_corr_dims(n_dims, n_orig_ctx, freq_base, beta_fast, beta_slow, corr_dims.v);
 
@@ -280,12 +304,12 @@ void ggml_cuda_op_rope(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
         if (src0->type == GGML_TYPE_F32) {
             rope_neox_cuda_f32(
                 (const float *)src0_d, (float *)dst_d, ne00, n_dims, nrows, pos, freq_scale, ne01, freq_base, ext_factor,
-                attn_factor, corr_dims, stream
+                attn_factor, corr_dims, freq_factors, stream
             );
         } else if (src0->type == GGML_TYPE_F16) {
             rope_neox_cuda_f16(
                 (const half *)src0_d, (half *)dst_d, ne00, n_dims, nrows, pos, freq_scale, ne01, freq_base, ext_factor,
-                attn_factor, corr_dims, stream
+                attn_factor, corr_dims, freq_factors, stream
             );
         } else {
             GGML_ASSERT(false);
diff --git a/ggml-cuda/softmax.cu b/ggml-cuda/softmax.cu
index ca85285a3..ce64f2f2c 100644
--- a/ggml-cuda/softmax.cu
+++ b/ggml-cuda/softmax.cu
@@ -1,3 +1,4 @@
+#include "common.cuh"
 #include "softmax.cuh"
 
 template <typename T>
@@ -23,17 +24,7 @@ static __global__ void soft_max_f32(const float * x, const T * mask, float * dst
     const int warp_id = threadIdx.x / WARP_SIZE;
     const int lane_id = threadIdx.x % WARP_SIZE;
 
-    float slope = 1.0f;
-
-    // ALiBi
-    if (max_bias > 0.0f) {
-        const int h = rowx/nrows_y; // head index
-
-        const float base = h < n_head_log2 ? m0 : m1;
-        const int   exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
-
-        slope = powf(base, exph);
-    }
+    const float slope = get_alibi_slope(max_bias, rowx/nrows_y, n_head_log2, m0, m1);
 
     extern __shared__ float data_soft_max_f32[];
     float * buf_iw = data_soft_max_f32; // shared memory buffer for inter-warp communication
diff --git a/ggml-cuda/vecdotq.cuh b/ggml-cuda/vecdotq.cuh
index 86b87fa93..5ebdddcc7 100644
--- a/ggml-cuda/vecdotq.cuh
+++ b/ggml-cuda/vecdotq.cuh
@@ -712,7 +712,6 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1(
 static __device__ __forceinline__ float vec_dot_q4_K_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 
-#ifndef GGML_QKK_64
     const block_q4_K * bq4_K = (const block_q4_K *) vbq;
 
     int    v[2];
@@ -754,58 +753,11 @@ static __device__ __forceinline__ float vec_dot_q4_K_q8_1(
     }
 
     return vec_dot_q4_K_q8_1_impl_vmmq(v, u, sc, m, bq4_K->dm, d8);
-
-#else
-
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-    const block_q4_K * bq4_K = (const block_q4_K *) vbq;
-
-    float sumf_d = 0.0f;
-    float sumf_m = 0.0f;
-
-    uint16_t aux16[2];
-    const uint8_t * s = (const uint8_t *)aux16;
-
-    const uint16_t * a = (const uint16_t *)bq4_K->scales;
-    aux16[0] = a[0] & 0x0f0f;
-    aux16[1] = (a[0] >> 4) & 0x0f0f;
-
-    const float dall = bq4_K->dm[0];
-    const float dmin = bq4_K->dm[1];
-
-    const float d8_1 = __low2float(bq8_1[0].ds);
-    const float d8_2 = __low2float(bq8_1[1].ds);
-
-    const int ui1 = *((const int *)bq8_1[0].qs + (iqs/2));
-    const int ui2 = *((const int *)bq8_1[0].qs + (iqs/2) + 4);
-    const int ui3 = *((const int *)bq8_1[1].qs + (iqs/2));
-    const int ui4 = *((const int *)bq8_1[1].qs + (iqs/2) + 4);
-
-    const int * q4 = (const int *)bq4_K->qs + (iqs/2);
-    const int v1 = q4[0];
-    const int v2 = q4[4];
-
-    const int dot1 = __dp4a(ui2, v2 & 0x0f0f0f0f, __dp4a(ui1, v1 & 0x0f0f0f0f, 0));
-    const int dot2 = __dp4a(ui4, (v2 >> 4) & 0x0f0f0f0f, __dp4a(ui3, (v1 >> 4) & 0x0f0f0f0f, 0));
-    const int dot3 = __dp4a(0x01010101, ui2, __dp4a(0x01010101, ui1, 0));
-    const int dot4 = __dp4a(0x01010101, ui4, __dp4a(0x01010101, ui3, 0));
-
-    sumf_d += d8_1 * (dot1 * s[0]) + d8_2 * (dot2 * s[1]);
-    sumf_m += d8_1 * (dot3 * s[2]) + d8_2 * (dot4 * s[3]);
-
-    return dall * sumf_d - dmin * sumf_m;
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
-
-#endif
 }
 
 static __device__ __forceinline__ float vec_dot_q5_K_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 
-#ifndef GGML_QKK_64
     const block_q5_K * bq5_K = (const block_q5_K *) vbq;
 
     int   vl[2];
@@ -847,48 +799,6 @@ static __device__ __forceinline__ float vec_dot_q5_K_q8_1(
     }
 
     return vec_dot_q5_K_q8_1_impl_vmmq(vl, vh, u, sc, m, bq5_K->dm, d8);
-
-#else
-
-#if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-    const block_q5_K * bq5_K = (const block_q5_K *) vbq;
-
-    const int8_t * s = bq5_K->scales;
-
-    const float d = bq5_K->d;
-
-    const float d8_1 = __low2half(bq8_1[0].ds);
-    const float d8_2 = __low2half(bq8_1[1].ds);
-
-    const int ui1 = *((const int *)bq8_1[0].qs + (iqs/2));
-    const int ui2 = *((const int *)bq8_1[0].qs + (iqs/2) + 4);
-    const int ui3 = *((const int *)bq8_1[1].qs + (iqs/2));
-    const int ui4 = *((const int *)bq8_1[1].qs + (iqs/2) + 4);
-
-    const int * ql = (const int *)bq5_K->qs + (iqs/2);
-    const int vl1 = ql[0];
-    const int vl2 = ql[4];
-
-    const int step = 4 * (iqs/2); // 0, 4, 8, 12
-    const int im = step/8; // = 0 for iqs = 0, 2, = 1 for iqs = 4, 6
-    const int in = step%8; // 0, 4, 0, 4
-    const int vh = (*((const int *)(bq5_K->qh + in))) >> im;
-
-    const int v1 = (((vh << 4) & 0x10101010) ^ 0x10101010) | ((vl1 >> 0) & 0x0f0f0f0f);
-    const int v2 = (((vh << 2) & 0x10101010) ^ 0x10101010) | ((vl2 >> 0) & 0x0f0f0f0f);
-    const int v3 = (((vh >> 0) & 0x10101010) ^ 0x10101010) | ((vl1 >> 4) & 0x0f0f0f0f);
-    const int v4 = (((vh >> 2) & 0x10101010) ^ 0x10101010) | ((vl2 >> 4) & 0x0f0f0f0f);
-
-    const float sumf_d = d8_1 * (__dp4a(ui1, v1, 0) * s[0] + __dp4a(ui2, v2, 0) * s[1])
-                       + d8_2 * (__dp4a(ui3, v3, 0) * s[2] + __dp4a(ui4, v4, 0) * s[3]);
-
-    return d * sumf_d;
-
-#else
-    NO_DEVICE_CODE;
-#endif // __CUDA_ARCH__ >= MIN_CC_DP4A
-
-#endif
 }
 
 static __device__ __forceinline__ float vec_dot_q6_K_q8_1(
@@ -919,7 +829,6 @@ static __device__ __forceinline__ float vec_dot_q6_K_q8_1(
 
 static __device__ __forceinline__ float vec_dot_iq2_xxs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
-#if QK_K == 256
     const block_iq2_xxs * bq2 = (const block_iq2_xxs *) vbq;
 
 #if QR2_XXS == 8
@@ -960,15 +869,11 @@ static __device__ __forceinline__ float vec_dot_iq2_xxs_q8_1(
     }
     return d * (sumi1 + sumi2);
 #endif
-#else
-    NO_DEVICE_CODE;
-#endif
 }
 
 static __device__ __forceinline__ float vec_dot_iq2_xs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-#if QK_K == 256
     const block_iq2_xs * bq2 = (const block_iq2_xs *) vbq;
 
     const int ib32 = iqs;
@@ -1002,17 +907,12 @@ static __device__ __forceinline__ float vec_dot_iq2_xs_q8_1(
     GGML_UNUSED(ksigns64);
     NO_DEVICE_CODE;
 #endif
-#else
-    GGML_UNUSED(ksigns64);
-    NO_DEVICE_CODE;
-#endif
 }
 
 // TODO
 static __device__ __forceinline__ float vec_dot_iq2_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-#if QK_K == 256
     const block_iq2_s * bq2 = (const block_iq2_s *) vbq;
 
     const int ib32 = iqs;
@@ -1048,16 +948,11 @@ static __device__ __forceinline__ float vec_dot_iq2_s_q8_1(
     GGML_UNUSED(ksigns64);
     NO_DEVICE_CODE;
 #endif
-#else
-    GGML_UNUSED(ksigns64);
-    NO_DEVICE_CODE;
-#endif
 }
 
 static __device__ __forceinline__ float vec_dot_iq3_xxs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-#if QK_K == 256
     const block_iq3_xxs * bq2 = (const block_iq3_xxs *) vbq;
 
     const int ib32 = iqs;
@@ -1082,16 +977,12 @@ static __device__ __forceinline__ float vec_dot_iq3_xxs_q8_1(
 #else
     NO_DEVICE_CODE;
 #endif
-#else
-    NO_DEVICE_CODE;
-#endif
 }
 
 // TODO: don't use lookup table for signs
 static __device__ __forceinline__ float vec_dot_iq3_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-#if QK_K == 256
     const block_iq3_s * bq2 = (const block_iq3_s *) vbq;
 
     const int ib32 = iqs;
@@ -1114,14 +1005,10 @@ static __device__ __forceinline__ float vec_dot_iq3_s_q8_1(
 #else
     NO_DEVICE_CODE;
 #endif
-#else
-    NO_DEVICE_CODE;
-#endif
 }
 
 static __device__ __forceinline__ float vec_dot_iq1_s_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
-#if QK_K == 256
     const block_iq1_s * bq1 = (const block_iq1_s *) vbq;
 
     const int ib32 = iqs;
@@ -1149,14 +1036,10 @@ static __device__ __forceinline__ float vec_dot_iq1_s_q8_1(
     const float d = d1q * __low2float (bq8_1[ib32].ds);
     const float m = d1q * __high2float(bq8_1[ib32].ds);
     return d * sumi + m * delta;
-#else
-    NO_DEVICE_CODE;
-#endif
 }
 
 static __device__ __forceinline__ float vec_dot_iq1_m_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
-#if QK_K == 256
     const block_iq1_m * bq1 = (const block_iq1_m *) vbq;
 
     const int ib32 = iqs;
@@ -1192,9 +1075,6 @@ static __device__ __forceinline__ float vec_dot_iq1_m_q8_1(
     scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
     const float d = (float)scale.f16 * __low2float (bq8_1[ib32].ds);
     return d * ((sumi[0] + sumf[0]) * (2*((sc[ib32/2] >> 6*(ib32%2)) & 0x7) + 1) + (sumi[1] + sumf[1]) * (2*((sc[ib32/2] >> (6*(ib32%2)+3)) & 0x7) + 1));
-#else
-    NO_DEVICE_CODE;
-#endif
 }
 
 #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
@@ -1250,9 +1130,7 @@ static __device__ __forceinline__ float vec_dot_iq4_nl_q8_1(
 static __device__ __forceinline__ float vec_dot_iq4_xs_q8_1(
     const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & iqs) {
 
-#if QK_K == 256
 #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics
-
     const block_iq4_xs * bq4 = (const block_iq4_xs *) vbq;
     const uint8_t * values = (const uint8_t *)kvalues_iq4nl;
 
@@ -1270,10 +1148,6 @@ static __device__ __forceinline__ float vec_dot_iq4_xs_q8_1(
         sumi2 = __dp4a(v2, q8[j+4], sumi2);
     }
     return d * (sumi1 + sumi2);
-
-#else
-    NO_DEVICE_CODE;
-#endif
 #else
     return vec_dot_iq4_xs_q8_1(vbq, bq8_1, iqs);
 #endif
diff --git a/ggml-impl.h b/ggml-impl.h
index 59684fa81..362d40f4d 100644
--- a/ggml-impl.h
+++ b/ggml-impl.h
@@ -17,6 +17,18 @@
 #define MIN(a, b) ((a) < (b) ? (a) : (b))
 #define MAX(a, b) ((a) > (b) ? (a) : (b))
 
+#if defined(_WIN32)
+
+#define m512bh(p) p
+#define m512i(p) p
+
+#else
+
+#define m512bh(p) (__m512bh)(p)
+#define m512i(p) (__m512i)(p)
+
+#endif
+
 /**
  * Converts brain16 to float32.
  *
@@ -443,6 +455,34 @@ static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
 #include <riscv_vector.h>
 #endif
 
+#if defined(__loongarch64)
+#if defined(__loongarch_asx)
+#include <lasxintrin.h>
+#endif
+#if defined(__loongarch_sx)
+#include <lsxintrin.h>
+#endif
+#endif
+
+#if defined(__loongarch_asx)
+
+typedef union {
+    int32_t i;
+    float f;
+} ft_union;
+
+/* float type data load instructions */
+static __m128 __lsx_vreplfr2vr_s(float val) {
+    ft_union fi_tmpval = {.f = val};
+    return (__m128)__lsx_vreplgr2vr_w(fi_tmpval.i);
+}
+
+static __m256 __lasx_xvreplfr2vr_s(float val) {
+    ft_union fi_tmpval = {.f = val};
+    return (__m256)__lasx_xvreplgr2vr_w(fi_tmpval.i);
+}
+#endif
+
 #ifdef __F16C__
 
 #ifdef _MSC_VER
diff --git a/ggml-kompute.cpp b/ggml-kompute.cpp
index 3f033d58b..6c6058b2a 100644
--- a/ggml-kompute.cpp
+++ b/ggml-kompute.cpp
@@ -1677,6 +1677,10 @@ static void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml
                     } break;
                 case GGML_OP_ROPE:
                     {
+#pragma message("TODO: implement phi3 frequency factors support")
+#pragma message("      https://github.com/ggerganov/llama.cpp/pull/7225")
+                        GGML_ASSERT(dst->src[2] == nullptr && "phi3 frequency factors not implemented yet");
+
                         GGML_ASSERT(ne10 == ne02);
                         GGML_ASSERT(src0t == dstt);
                         // const int n_past = ((int32_t *) dst->op_params)[0];
diff --git a/ggml-metal.m b/ggml-metal.m
index b0b16dbf7..c9e570dbf 100644
--- a/ggml-metal.m
+++ b/ggml-metal.m
@@ -381,10 +381,6 @@ static struct ggml_metal_context * ggml_metal_init(int n_cb) {
                 // dictionary of preprocessor macros
                 NSMutableDictionary * prep = [NSMutableDictionary dictionary];
 
-#ifdef GGML_QKK_64
-                prep[@"GGML_QKK_64"] = @(1);
-#endif
-
                 MTLCompileOptions* options = [MTLCompileOptions new];
                 options.preprocessorMacros = prep;
 
@@ -927,22 +923,32 @@ static enum ggml_status ggml_metal_graph_compute(
             const int64_t  ne10 = src1 ? src1->ne[0] : 0;
             const int64_t  ne11 = src1 ? src1->ne[1] : 0;
             const int64_t  ne12 = src1 ? src1->ne[2] : 0;
-            const int64_t  ne13 = src1 ? src1->ne[3] : 0; UNUSED(ne13);
+            const int64_t  ne13 = src1 ? src1->ne[3] : 0;
 
             const uint64_t nb10 = src1 ? src1->nb[0] : 0;
             const uint64_t nb11 = src1 ? src1->nb[1] : 0;
             const uint64_t nb12 = src1 ? src1->nb[2] : 0;
-            const uint64_t nb13 = src1 ? src1->nb[3] : 0; UNUSED(nb13);
+            const uint64_t nb13 = src1 ? src1->nb[3] : 0;
 
-            const int64_t  ne0  = dst ? dst->ne[0] : 0;
-            const int64_t  ne1  = dst ? dst->ne[1] : 0;
-            const int64_t  ne2  = dst ? dst->ne[2] : 0;
-            const int64_t  ne3  = dst ? dst->ne[3] : 0;
+            const int64_t  ne20 = src2 ? src2->ne[0] : 0;
+            const int64_t  ne21 = src2 ? src2->ne[1] : 0;
+            const int64_t  ne22 = src2 ? src2->ne[2] : 0; GGML_UNUSED(ne22);
+            const int64_t  ne23 = src2 ? src2->ne[3] : 0; GGML_UNUSED(ne23);
 
-            const uint64_t nb0  = dst ? dst->nb[0] : 0;
-            const uint64_t nb1  = dst ? dst->nb[1] : 0;
-            const uint64_t nb2  = dst ? dst->nb[2] : 0;
-            const uint64_t nb3  = dst ? dst->nb[3] : 0;
+            const uint64_t nb20 = src2 ? src2->nb[0] : 0; GGML_UNUSED(nb20);
+            const uint64_t nb21 = src2 ? src2->nb[1] : 0;
+            const uint64_t nb22 = src2 ? src2->nb[2] : 0;
+            const uint64_t nb23 = src2 ? src2->nb[3] : 0;
+
+            const int64_t  ne0  =  dst ?  dst->ne[0] : 0;
+            const int64_t  ne1  =  dst ?  dst->ne[1] : 0;
+            const int64_t  ne2  =  dst ?  dst->ne[2] : 0;
+            const int64_t  ne3  =  dst ?  dst->ne[3] : 0;
+
+            const uint64_t nb0  =  dst ?  dst->nb[0] : 0;
+            const uint64_t nb1  =  dst ?  dst->nb[1] : 0;
+            const uint64_t nb2  =  dst ?  dst->nb[2] : 0;
+            const uint64_t nb3  =  dst ?  dst->nb[3] : 0;
 
             const enum ggml_type src0t = src0 ? src0->type : GGML_TYPE_COUNT;
             const enum ggml_type src1t = src1 ? src1->type : GGML_TYPE_COUNT;
@@ -1763,11 +1769,7 @@ static enum ggml_status ggml_metal_graph_compute(
                                 [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
                             }
                             else if (src0t == GGML_TYPE_Q3_K) {
-#ifdef GGML_QKK_64
-                                [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 1)/2, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
-#else
                                 [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
-#endif
                             }
                             else if (src0t == GGML_TYPE_Q5_K) {
                                 [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
@@ -1785,16 +1787,6 @@ static enum ggml_status ggml_metal_graph_compute(
                         const int n_as = src0->ne[2];
 
                         // src2 = ids
-                        const int64_t  ne20 = src2->ne[0];
-                        const int64_t  ne21 = src2->ne[1];
-                        const int64_t  ne22 = src2->ne[2]; GGML_UNUSED(ne22);
-                        const int64_t  ne23 = src2->ne[3]; GGML_UNUSED(ne23);
-
-                        const uint64_t nb20 = src2->nb[0]; GGML_UNUSED(nb20);
-                        const uint64_t nb21 = src2->nb[1];
-                        const uint64_t nb22 = src2->nb[2]; GGML_UNUSED(nb22);
-                        const uint64_t nb23 = src2->nb[3]; GGML_UNUSED(nb23);
-
                         const enum ggml_type src2t = src2->type; GGML_UNUSED(src2t);
 
                         GGML_ASSERT(src2t == GGML_TYPE_I32);
@@ -2018,12 +2010,7 @@ static enum ggml_status ggml_metal_graph_compute(
                                     {
                                         nth0 = 4;
                                         nth1 = 16;
-                                    #if QK_K == 64
-                                        pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_NL_F32].pipeline;
-                                    #else
                                         pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_IQ4_XS_F32].pipeline;
-                                    #endif
-
                                     } break;
                                 default:
                                     {
@@ -2088,11 +2075,7 @@ static enum ggml_status ggml_metal_graph_compute(
                                 [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, _ne1, tgz) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
                             }
                             else if (src0t == GGML_TYPE_Q3_K) {
-#ifdef GGML_QKK_64
-                                [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 1)/2, _ne1, tgz) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
-#else
                                 [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, _ne1, tgz) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
-#endif
                             }
                             else if (src0t == GGML_TYPE_Q5_K) {
                                 [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3)/4, _ne1, tgz) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
@@ -2244,7 +2227,13 @@ static enum ggml_status ggml_metal_graph_compute(
                         // skip 3, n_ctx, used in GLM RoPE, unimplemented in metal
                         const int n_orig_ctx = ((int32_t *) dst->op_params)[4];
 
-                        float freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow;
+                        float freq_base;
+                        float freq_scale;
+                        float ext_factor;
+                        float attn_factor;
+                        float beta_fast;
+                        float beta_slow;
+
                         memcpy(&freq_base,   (int32_t *) dst->op_params +  5, sizeof(float));
                         memcpy(&freq_scale,  (int32_t *) dst->op_params +  6, sizeof(float));
                         memcpy(&ext_factor,  (int32_t *) dst->op_params +  7, sizeof(float));
@@ -2252,6 +2241,15 @@ static enum ggml_status ggml_metal_graph_compute(
                         memcpy(&beta_fast,   (int32_t *) dst->op_params +  9, sizeof(float));
                         memcpy(&beta_slow,   (int32_t *) dst->op_params + 10, sizeof(float));
 
+                        const bool is_neox = mode & 2;
+                        const bool is_glm  = mode & 4;
+
+                        GGML_ASSERT(!is_glm && "GLM RoPE not implemented in Metal");
+
+                        if (!is_neox) {
+                            GGML_ASSERT(id_src2 == nil && "TODO: freq_factors not implemented for !is_neox");
+                        }
+
                         id<MTLComputePipelineState> pipeline = nil;
 
                         switch (src0->type) {
@@ -2263,33 +2261,38 @@ static enum ggml_status ggml_metal_graph_compute(
                         [encoder setComputePipelineState:pipeline];
                         [encoder setBuffer:id_src0     offset:offs_src0        atIndex:0];
                         [encoder setBuffer:id_src1     offset:offs_src1        atIndex:1];
-                        [encoder setBuffer:id_dst      offset:offs_dst         atIndex:2];
-                        [encoder setBytes:&ne00        length:sizeof( int64_t) atIndex:3];
-                        [encoder setBytes:&ne01        length:sizeof( int64_t) atIndex:4];
-                        [encoder setBytes:&ne02        length:sizeof( int64_t) atIndex:5];
-                        [encoder setBytes:&ne03        length:sizeof( int64_t) atIndex:6];
-                        [encoder setBytes:&nb00        length:sizeof(uint64_t) atIndex:7];
-                        [encoder setBytes:&nb01        length:sizeof(uint64_t) atIndex:8];
-                        [encoder setBytes:&nb02        length:sizeof(uint64_t) atIndex:9];
-                        [encoder setBytes:&nb03        length:sizeof(uint64_t) atIndex:10];
-                        [encoder setBytes:&ne0         length:sizeof( int64_t) atIndex:11];
-                        [encoder setBytes:&ne1         length:sizeof( int64_t) atIndex:12];
-                        [encoder setBytes:&ne2         length:sizeof( int64_t) atIndex:13];
-                        [encoder setBytes:&ne3         length:sizeof( int64_t) atIndex:14];
-                        [encoder setBytes:&nb0         length:sizeof(uint64_t) atIndex:15];
-                        [encoder setBytes:&nb1         length:sizeof(uint64_t) atIndex:16];
-                        [encoder setBytes:&nb2         length:sizeof(uint64_t) atIndex:17];
-                        [encoder setBytes:&nb3         length:sizeof(uint64_t) atIndex:18];
-                        [encoder setBytes:&n_past      length:sizeof(     int) atIndex:19];
-                        [encoder setBytes:&n_dims      length:sizeof(     int) atIndex:20];
-                        [encoder setBytes:&mode        length:sizeof(     int) atIndex:21];
-                        [encoder setBytes:&n_orig_ctx  length:sizeof(     int) atIndex:22];
-                        [encoder setBytes:&freq_base   length:sizeof(   float) atIndex:23];
-                        [encoder setBytes:&freq_scale  length:sizeof(   float) atIndex:24];
-                        [encoder setBytes:&ext_factor  length:sizeof(   float) atIndex:25];
-                        [encoder setBytes:&attn_factor length:sizeof(   float) atIndex:26];
-                        [encoder setBytes:&beta_fast   length:sizeof(   float) atIndex:27];
-                        [encoder setBytes:&beta_slow   length:sizeof(   float) atIndex:28];
+                        if (id_src2 != nil) {
+                            [encoder setBuffer:id_src2 offset:offs_src2        atIndex:2];
+                        } else {
+                            [encoder setBuffer:id_src0 offset:offs_src0        atIndex:2];
+                        }
+                        [encoder setBuffer:id_dst      offset:offs_dst         atIndex:3];
+                        [encoder setBytes:&ne00        length:sizeof( int64_t) atIndex:4];
+                        [encoder setBytes:&ne01        length:sizeof( int64_t) atIndex:5];
+                        [encoder setBytes:&ne02        length:sizeof( int64_t) atIndex:6];
+                        [encoder setBytes:&ne03        length:sizeof( int64_t) atIndex:7];
+                        [encoder setBytes:&nb00        length:sizeof(uint64_t) atIndex:8];
+                        [encoder setBytes:&nb01        length:sizeof(uint64_t) atIndex:9];
+                        [encoder setBytes:&nb02        length:sizeof(uint64_t) atIndex:10];
+                        [encoder setBytes:&nb03        length:sizeof(uint64_t) atIndex:11];
+                        [encoder setBytes:&ne0         length:sizeof( int64_t) atIndex:12];
+                        [encoder setBytes:&ne1         length:sizeof( int64_t) atIndex:13];
+                        [encoder setBytes:&ne2         length:sizeof( int64_t) atIndex:14];
+                        [encoder setBytes:&ne3         length:sizeof( int64_t) atIndex:15];
+                        [encoder setBytes:&nb0         length:sizeof(uint64_t) atIndex:16];
+                        [encoder setBytes:&nb1         length:sizeof(uint64_t) atIndex:17];
+                        [encoder setBytes:&nb2         length:sizeof(uint64_t) atIndex:18];
+                        [encoder setBytes:&nb3         length:sizeof(uint64_t) atIndex:19];
+                        [encoder setBytes:&n_past      length:sizeof(     int) atIndex:20];
+                        [encoder setBytes:&n_dims      length:sizeof(     int) atIndex:21];
+                        [encoder setBytes:&mode        length:sizeof(     int) atIndex:22];
+                        [encoder setBytes:&n_orig_ctx  length:sizeof(     int) atIndex:23];
+                        [encoder setBytes:&freq_base   length:sizeof(   float) atIndex:24];
+                        [encoder setBytes:&freq_scale  length:sizeof(   float) atIndex:25];
+                        [encoder setBytes:&ext_factor  length:sizeof(   float) atIndex:26];
+                        [encoder setBytes:&attn_factor length:sizeof(   float) atIndex:27];
+                        [encoder setBytes:&beta_fast   length:sizeof(   float) atIndex:28];
+                        [encoder setBytes:&beta_slow   length:sizeof(   float) atIndex:29];
 
                         [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
                     } break;
@@ -2535,11 +2538,6 @@ static enum ggml_status ggml_metal_graph_compute(
                         GGML_ASSERT(!src3 || src3->ne[1] >= GGML_PAD(src0->ne[1], 8) &&
                                 "the Flash-Attention Metal kernel requires the mask to be padded to 8 and at least n_queries big");
 
-                        const uint64_t nb20 = src2 ? src2->nb[0] : 0; GGML_UNUSED(nb20);
-                        const uint64_t nb21 = src2 ? src2->nb[1] : 0;
-                        const uint64_t nb22 = src2 ? src2->nb[2] : 0;
-                        const uint64_t nb23 = src2 ? src2->nb[3] : 0;
-
                         const int64_t  ne30 = src3 ? src3->ne[0] : 0; GGML_UNUSED(ne30);
                       //const int64_t  ne31 = src3 ? src3->ne[1] : 0;
                         const int64_t  ne32 = src3 ? src3->ne[2] : 0; GGML_UNUSED(ne32);
diff --git a/ggml-metal.metal b/ggml-metal.metal
index 386e9195f..8ff70d7a7 100644
--- a/ggml-metal.metal
+++ b/ggml-metal.metal
@@ -1640,6 +1640,7 @@ static void rope_yarn_corr_dims(
 typedef void (rope_t)(
         device const    void * src0,
         device const int32_t * src1,
+        device const   float * src2,
         device         float * dst,
         constant     int64_t & ne00,
         constant     int64_t & ne01,
@@ -1675,6 +1676,7 @@ template<typename T>
 kernel void kernel_rope(
         device const    void * src0,
         device const int32_t * src1,
+        device const   float * src2,
         device         float * dst,
         constant     int64_t & ne00,
         constant     int64_t & ne01,
@@ -1744,8 +1746,10 @@ kernel void kernel_rope(
 
                 // simplified from `(ib * n_dims + ic) * inv_ndims`
                 const float cur_rot = inv_ndims*ic - ib;
+                const float freq_factor = src2 != src0 ? src2[ic/2] : 1.0f;
+
+                const float theta = theta_0 * pow(freq_base, cur_rot) / freq_factor;
 
-                const float theta = theta_0 * pow(freq_base, cur_rot);
                 float cos_theta, sin_theta;
                 rope_yarn(theta, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor, &cos_theta, &sin_theta);
 
@@ -2204,11 +2208,7 @@ kernel void kernel_flash_attn_ext_f16(
         // pointer to the mask
         device const half * mp = (device const half *) (mask + iq1*nb31);
 
-        // prepare diagonal scale matrix
-        simdgroup_float8x8 mscale(scale);
-
-        // prepare diagonal slope matrix
-        simdgroup_float8x8 mslope(1.0f);
+        float slope = 1.0f;
 
         // ALiBi
         if (max_bias > 0.0f) {
@@ -2217,7 +2217,7 @@ kernel void kernel_flash_attn_ext_f16(
             const float base = h < n_head_log2 ? m0 : m1;
             const int   exph = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
 
-            mslope = simdgroup_float8x8(pow(base, exph));
+            slope = pow(base, exph);
         }
 
         // loop over the KV cache
@@ -2242,18 +2242,20 @@ kernel void kernel_flash_attn_ext_f16(
                         simdgroup_multiply_accumulate(mqk, mq[i], mk, mqk);
                     }
 
+                    simdgroup_store(mqk, ss + 8*cc, TF, 0, false);
+
+                    const short tx = tiisg%4;
+                    const short ty = tiisg/4;
+
                     if (mask != q) {
                         // mqk = mqk*scale + mask*slope
-                        simdgroup_half8x8 mm;
-                        simdgroup_load(mm, mp + ic + 8*cc, nb31/sizeof(half), 0, false);
-                        simdgroup_multiply(mm, mslope, mm);
-                        simdgroup_multiply_accumulate(mqk, mqk, mscale, mm);
+                        ss[8*cc + ty*TF + 2*tx + 0] = scale*ss[8*cc + ty*TF + 2*tx + 0] + slope*mp[ic + 8*cc + ty*nb31/sizeof(half) + 2*tx + 0];
+                        ss[8*cc + ty*TF + 2*tx + 1] = scale*ss[8*cc + ty*TF + 2*tx + 1] + slope*mp[ic + 8*cc + ty*nb31/sizeof(half) + 2*tx + 1];
                     } else {
                         // mqk = mqk*scale
-                        simdgroup_multiply(mqk, mscale, mqk);
+                        ss[8*cc + ty*TF + 2*tx + 0] *= scale;
+                        ss[8*cc + ty*TF + 2*tx + 1] *= scale;
                     }
-
-                    simdgroup_store(mqk, ss + 8*cc, TF, 0, false);
                 }
             }
 
@@ -2816,8 +2818,7 @@ kernel void kernel_cpy_f32_f16(
     for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
         device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
 
-        // TODO: is there a better way to handle -INFINITY?
-        dst_data[i00] = src[0] == -INFINITY ? -MAXHALF : src[0];
+        dst_data[i00] = src[0];
     }
 }
 
@@ -3385,7 +3386,6 @@ void kernel_mul_mv_q2_K_f32_impl(
 
     const int step = sizeof(block_q2_K) * nb;
 
-#if QK_K == 256
     const int ix = tiisg/8;  // 0...3
     const int it = tiisg%8;  // 0...7
     const int iq = it/4;     // 0 or 1
@@ -3437,57 +3437,6 @@ void kernel_mul_mv_q2_K_f32_impl(
 
         y4 += 4 * QK_K;
     }
-#else
-    const int ix = tiisg/2;  // 0...15
-    const int it = tiisg%2;  // 0...1
-
-    device const float * y4 = y + ix * QK_K + 8 * it;
-
-    for (int ib = ix; ib < nb; ib += 16) {
-
-        float4 sumy = {0.f, 0.f, 0.f, 0.f};
-        for (int i = 0; i < 8; ++i) {
-            yl[i+ 0] = y4[i+ 0]; sumy[0] += yl[i+ 0];
-            yl[i+ 8] = y4[i+16]; sumy[1] += yl[i+ 8];
-            yl[i+16] = y4[i+32]; sumy[2] += yl[i+16];
-            yl[i+24] = y4[i+48]; sumy[3] += yl[i+24];
-        }
-
-        device const uint8_t  * sc = (device const uint8_t  *)x[ib].scales;
-        device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 4 * it;
-        device const half     * dh = &x[ib].d;
-
-        for (int row = 0; row < N_DST; row++) {
-
-            float4 acc1 = {0.f, 0.f, 0.f, 0.f};
-            float4 acc2 = {0.f, 0.f, 0.f, 0.f};
-            for (int i = 0; i < 8; i += 2) {
-                acc1[0] += yl[i+ 0] * (qs[i/2] & 0x0003);
-                acc2[0] += yl[i+ 1] * (qs[i/2] & 0x0300);
-                acc1[1] += yl[i+ 8] * (qs[i/2] & 0x000c);
-                acc2[1] += yl[i+ 9] * (qs[i/2] & 0x0c00);
-                acc1[2] += yl[i+16] * (qs[i/2] & 0x0030);
-                acc2[2] += yl[i+17] * (qs[i/2] & 0x3000);
-                acc1[3] += yl[i+24] * (qs[i/2] & 0x00c0);
-                acc2[3] += yl[i+25] * (qs[i/2] & 0xc000);
-            }
-
-            float dall = dh[0];
-            float dmin = dh[1];
-            sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc2[0]) * (sc[0] & 0xF) * 1.f/ 1.f +
-                                 (acc1[1] + 1.f/256.f * acc2[1]) * (sc[1] & 0xF) * 1.f/ 4.f +
-                                 (acc1[2] + 1.f/256.f * acc2[2]) * (sc[2] & 0xF) * 1.f/16.f +
-                                 (acc1[3] + 1.f/256.f * acc2[3]) * (sc[3] & 0xF) * 1.f/64.f) -
-                         dmin * (sumy[0] * (sc[0] >> 4) + sumy[1] * (sc[1] >> 4) + sumy[2] * (sc[2] >> 4) + sumy[3] * (sc[3] >> 4));
-
-            qs += step/2;
-            sc += step;
-            dh += step/2;
-        }
-
-        y4 += 16 * QK_K;
-    }
-#endif
 
     for (int row = 0; row < N_DST; ++row) {
         all_sum = simd_sum(sumf[row]);
@@ -3525,7 +3474,6 @@ kernel void kernel_mul_mv_q2_K_f32(
     kernel_mul_mv_q2_K_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg);
 }
 
-#if QK_K == 256
 void kernel_mul_mv_q3_K_f32_impl(
         device const  void * src0,
         device const float * src1,
@@ -3684,84 +3632,6 @@ void kernel_mul_mv_q3_K_f32_impl(
         }
     }
 }
-#else
-void kernel_mul_mv_q3_K_f32_impl(
-        device const  void * src0,
-        device const float * src1,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant   int64_t & ne10,
-        constant   int64_t & ne12,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   uint    & r2,
-        constant   uint    & r3,
-        threadgroup int8_t * shared_values [[threadgroup(0)]],
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint  tiisg[[thread_index_in_simdgroup]],
-        uint  sgitg[[simdgroup_index_in_threadgroup]]) {
-
-    const int nb = ne00/QK_K;
-
-    const int64_t r0 = tgpig.x;
-    const int64_t r1 = tgpig.y;
-    const int64_t im = tgpig.z;
-
-    const int row = 2 * r0 + sgitg;
-
-    const uint i12 = im%ne12;
-    const uint i13 = im/ne12;
-
-    const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02);
-
-    device const block_q3_K * x = (device const block_q3_K *) src0 + row*nb + offset0;
-    device const float     * yy = (device const float      *) src1 + r1*ne10 + im*ne00*ne1;
-
-    const int ix = tiisg/4;
-    const int il = 4 * (tiisg%4);// 0, 4, 8, 12
-    const int iq = il/8;         // 0, 0, 1, 1
-    const int in = il%8;         // 0, 4, 0, 4
-
-    float2 sum = {0.f, 0.f};
-
-    for (int i = ix; i < nb; i += 8) {
-
-        const float d_all = (float)(x[i].d);
-
-        device const uint16_t * q = (device const uint16_t *)(x[i].qs + il);
-        device const uint16_t * h = (device const uint16_t *)(x[i].hmask + in);
-        device const uint16_t * s = (device const uint16_t *)(x[i].scales);
-        device const float    * y = yy + i * QK_K + il;
-
-        const float d1 = d_all * ((int32_t)(s[0] & 0x000F) - 8);
-        const float d2 = d_all * ((int32_t)(s[0] & 0x00F0) - 128) * 1.f/64.f;
-        const float d3 = d_all * ((int32_t)(s[0] & 0x0F00) - 2048) * 1.f/4096.f;
-        const float d4 = d_all * ((int32_t)(s[0] & 0xF000) - 32768) * 1.f/262144.f;
-
-        for (int l = 0; l < 4; l += 2) {
-            const uint16_t hm = h[l/2] >> iq;
-            sum[0] += y[l+ 0] * d1 * ((int32_t)(q[l/2] & 0x0003) - ((hm & 0x0001) ? 0 :  4))
-                    + y[l+16] * d2 * ((int32_t)(q[l/2] & 0x000c) - ((hm & 0x0004) ? 0 : 16))
-                    + y[l+32] * d3 * ((int32_t)(q[l/2] & 0x0030) - ((hm & 0x0010) ? 0 : 64))
-                    + y[l+48] * d4 * ((int32_t)(q[l/2] & 0x00c0) - ((hm & 0x0040) ? 0 : 256));
-            sum[1] += y[l+ 1] * d1 * ((int32_t)(q[l/2] & 0x0300) - ((hm & 0x0100) ? 0 : 1024))
-                    + y[l+17] * d2 * ((int32_t)(q[l/2] & 0x0c00) - ((hm & 0x0400) ? 0 : 4096))
-                    + y[l+33] * d3 * ((int32_t)(q[l/2] & 0x3000) - ((hm & 0x1000) ? 0 : 16384))
-                    + y[l+49] * d4 * ((int32_t)(q[l/2] & 0xc000) - ((hm & 0x4000) ? 0 : 65536));
-        }
-
-    }
-    const float sumf = sum[0] + sum[1] * 1.f/256.f;
-
-    const float tot = simd_sum(sumf);
-    if (tiisg == 0) {
-        dst[r1*ne0 + im*ne0*ne1 + row] = tot;
-    }
-
-}
-#endif
 
 [[host_name("kernel_mul_mv_q3_K_f32")]]
 kernel void kernel_mul_mv_q3_K_f32(
@@ -3791,7 +3661,6 @@ kernel void kernel_mul_mv_q3_K_f32(
     kernel_mul_mv_q3_K_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg);
 }
 
-#if QK_K == 256
 void kernel_mul_mv_q4_K_f32_impl(
         device const  void * src0,
         device const float * src1,
@@ -3905,103 +3774,6 @@ void kernel_mul_mv_q4_K_f32_impl(
         }
     }
 }
-#else
-void kernel_mul_mv_q4_K_f32_impl(
-        device const  void * src0,
-        device const float * src1,
-        device       float * dst,
-        constant   int64_t & ne00,
-        constant   int64_t & ne01,
-        constant   int64_t & ne02,
-        constant   int64_t & ne10,
-        constant   int64_t & ne12,
-        constant   int64_t & ne0,
-        constant   int64_t & ne1,
-        constant   uint    & r2,
-        constant   uint    & r3,
-        threadgroup int8_t * shared_values [[threadgroup(0)]],
-        uint3 tgpig[[threadgroup_position_in_grid]],
-        uint  tiisg[[thread_index_in_simdgroup]],
-        uint  sgitg[[simdgroup_index_in_threadgroup]]) {
-
-    const int ix = tiisg/4;  // 0...7
-    const int it = tiisg%4;  // 0...3
-
-    const int nb = ne00/QK_K;
-    const int r0 = tgpig.x;
-    const int r1 = tgpig.y;
-    const int im = tgpig.z;
-    const int first_row = r0 * N_DST;
-    const int ib_row = first_row * nb;
-
-    const uint i12 = im%ne12;
-    const uint i13 = im/ne12;
-
-    const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02);
-
-    device const block_q4_K * x = (device const block_q4_K *) src0 + ib_row + offset0;
-    device const float      * y = (device const float      *) src1 + r1*ne10 + im*ne00*ne1;
-
-    float yl[8];
-    float yh[8];
-    float sumf[N_DST]={0.f}, all_sum;
-
-    const int step = sizeof(block_q4_K) * nb / 2;
-
-    device const float * y4 = y + ix * QK_K + 8 * it;
-
-    uint16_t sc16[4];
-
-    for (int ib = ix; ib < nb; ib += 8) {
-
-        float2 sumy = {0.f, 0.f};
-        for (int i = 0; i < 8; ++i) {
-            yl[i] = y4[i+ 0]; sumy[0] += yl[i];
-            yh[i] = y4[i+32]; sumy[1] += yh[i];
-        }
-
-        device const uint16_t * sc = (device const uint16_t *)x[ib].scales;
-        device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 4 * it;
-        device const half     * dh = x[ib].d;
-
-        for (int row = 0; row < N_DST; row++) {
-
-            sc16[0] = sc[0] & 0x000f;
-            sc16[1] = sc[0] & 0x0f00;
-            sc16[2] = sc[0] & 0x00f0;
-            sc16[3] = sc[0] & 0xf000;
-
-            float2 acc1 = {0.f, 0.f};
-            float2 acc2 = {0.f, 0.f};
-            for (int i = 0; i < 8; i += 2) {
-                acc1[0] += yl[i+0] * (qs[i/2] & 0x000F);
-                acc1[1] += yl[i+1] * (qs[i/2] & 0x0F00);
-                acc2[0] += yh[i+0] * (qs[i/2] & 0x00F0);
-                acc2[1] += yh[i+1] * (qs[i/2] & 0xF000);
-            }
-
-            float dall = dh[0];
-            float dmin = dh[1];
-            sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc1[1]) * sc16[0] +
-                                 (acc2[0] + 1.f/256.f * acc2[1]) * sc16[1] * 1.f/4096.f) -
-                         dmin * 1.f/16.f * (sumy[0] * sc16[2] + sumy[1] * sc16[3] * 1.f/256.f);
-
-            qs += step;
-            sc += step;
-            dh += step;
-        }
-
-        y4 += 8 * QK_K;
-    }
-
-    for (int row = 0; row < N_DST; ++row) {
-        all_sum = simd_sum(sumf[row]);
-        if (tiisg == 0) {
-            dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum;
-        }
-    }
-}
-#endif
 
 [[host_name("kernel_mul_mv_q4_K_f32")]]
 kernel void kernel_mul_mv_q4_K_f32(
@@ -4069,8 +3841,6 @@ void kernel_mul_mv_q5_K_f32_impl(
 
     const int step = sizeof(block_q5_K) * nb;
 
-#if QK_K == 256
-#
     float yl[16], yh[16];
 
     const uint16_t kmask1 = 0x3f3f;
@@ -4153,54 +3923,6 @@ void kernel_mul_mv_q5_K_f32_impl(
         y1 += 4 * QK_K;
 
     }
-#else
-    float yl[8], yh[8];
-
-    const int il = 4 * (tiisg/8);  // 0, 4, 8, 12
-    const int ix = tiisg%8;
-    const int iq = il/8;         // 0, 0, 1, 1
-    const int in = il%8;         // 0, 4, 0, 4
-
-    device const float * y = yy + ix*QK_K + il;
-
-    for (int i = ix; i < nb; i += 8) {
-
-        for (int l = 0; l < 4; ++l) {
-            yl[l+0] = y[l+ 0];
-            yl[l+4] = y[l+16];
-            yh[l+0] = y[l+32];
-            yh[l+4] = y[l+48];
-        }
-
-        device const half * dh = &x[i].d;
-        device const uint8_t * q = x[i].qs + il;
-        device const uint8_t * h = x[i].qh + in;
-        device const int8_t  * s = x[i].scales;
-
-        for (int row = 0; row < 2; ++row) {
-
-            const float d = dh[0];
-
-            float2 acc = {0.f, 0.f};
-            for (int l = 0; l < 4; ++l) {
-                const uint8_t hl = h[l] >> iq;
-                acc[0] += yl[l+0] * s[0] * ((int16_t)(q[l+ 0] & 0x0F) - (hl & 0x01 ? 0 : 16))
-                        + yl[l+4] * s[1] * ((int16_t)(q[l+16] & 0x0F) - (hl & 0x04 ? 0 : 16));
-                acc[1] += yh[l+0] * s[2] * ((int16_t)(q[l+ 0] & 0xF0) - (hl & 0x10 ? 0 : 256))
-                        + yh[l+4] * s[3] * ((int16_t)(q[l+16] & 0xF0) - (hl & 0x40 ? 0 : 256));
-            }
-            sumf[row] += d * (acc[0] + 1.f/16.f * acc[1]);
-
-            q += step;
-            h += step;
-            s += step;
-            dh += step/2;
-
-        }
-
-        y += 8 * QK_K;
-    }
-#endif
 
     for (int row = 0; row < 2; ++row) {
         const float tot = simd_sum(sumf[row]);
@@ -4279,7 +4001,6 @@ void kernel_mul_mv_q6_K_f32_impl(
 
     float sumf = 0;
 
-#if QK_K == 256
     const int tid  = tiisg/2;
     const int ix   = tiisg%2;
     const int ip   = tid/8;         // 0 or 1
@@ -4315,30 +4036,6 @@ void kernel_mul_mv_q6_K_f32_impl(
 
     }
 
-#else
-    const int ix  = tiisg/4;
-    const int il  = 4*(tiisg%4);
-
-    for (int i = ix; i < nb; i += 8) {
-        device const float * y = yy + i * QK_K + il;
-        device const uint8_t * ql = x[i].ql + il;
-        device const uint8_t * qh = x[i].qh + il;
-        device const int8_t  * s  = x[i].scales;
-
-        const float d = x[i].d;
-
-        float4 sums = {0.f, 0.f, 0.f, 0.f};
-        for (int l = 0; l < 4; ++l) {
-            sums[0] += y[l+ 0] * ((int8_t)((ql[l+ 0] & 0xF) | ((qh[l] & kmask1) << 4)) - 32);
-            sums[1] += y[l+16] * ((int8_t)((ql[l+16] & 0xF) | ((qh[l] & kmask2) << 2)) - 32);
-            sums[2] += y[l+32] * ((int8_t)((ql[l+ 0] >>  4) | ((qh[l] & kmask3) >> 0)) - 32);
-            sums[3] += y[l+48] * ((int8_t)((ql[l+16] >>  4) | ((qh[l] & kmask4) >> 2)) - 32);
-        }
-        sumf += d * (sums[0] * s[0] + sums[1] * s[1] + sums[2] * s[2] + sums[3] * s[3]);
-    }
-
-#endif
-
     const float tot = simd_sum(sumf);
     if (tiisg == 0) {
         dst[r1*ne0 + im*ne0*ne1 + row] = tot;
@@ -5172,9 +4869,7 @@ void kernel_mul_mv_iq1_m_f32_impl(
 
     device const float * y4 = y + 32 * ix;
 
-#if QK_K != 64
     iq1m_scale_t scale;
-#endif
 
     for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
 
@@ -5195,10 +4890,7 @@ void kernel_mul_mv_iq1_m_f32_impl(
         device const uint16_t * sc = (device const uint16_t *)xr->scales;
 
         for (int row = 0; row < N_DST; row++) {
-
-#if QK_K != 64
             scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
-#endif
 
             constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
             constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((qh[0] << 4) & 0x700)));
@@ -5214,14 +4906,9 @@ void kernel_mul_mv_iq1_m_f32_impl(
             }
             const float delta1 = sumy[0] * (qh[0] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA) + sumy[1] * (qh[0] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
             const float delta2 = sumy[2] * (qh[1] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA) + sumy[3] * (qh[1] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
-#if QK_K == 64
-            const float d = (float) *((device const half *)(sc - 1));
-            sumf[row] += d * ((sum[0] + delta1) * (2*((sc[0] >> (8*(ib%2)+0)) & 0xf) + 1) +
-                              (sum[1] + delta2) * (2*((sc[0] >> (8*(ib%2)+4)) & 0xf) + 1));
-#else
+
             sumf[row] += (float)scale.f16 * ((sum[0] + delta1) * (2*((sc[ib/2] >> (6*(ib%2)+0)) & 7) + 1) +
                                              (sum[1] + delta2) * (2*((sc[ib/2] >> (6*(ib%2)+3)) & 7) + 1));
-#endif
 
             sc += nb*sizeof(block_iq1_m)/2;
             qs += nb*sizeof(block_iq1_m);
@@ -5333,7 +5020,6 @@ void kernel_mul_mv_iq4_nl_f32_impl(
     }
 }
 
-#if QK_K != 64
 void kernel_mul_mv_iq4_xs_f32_impl(
         device const  void * src0,
         device const float * src1,
@@ -5428,7 +5114,6 @@ void kernel_mul_mv_iq4_xs_f32_impl(
         }
     }
 }
-#endif
 
 [[host_name("kernel_mul_mv_iq1_s_f32")]]
 kernel void kernel_mul_mv_iq1_s_f32(
@@ -5541,11 +5226,7 @@ kernel void kernel_mul_mv_iq4_xs_f32(
         uint tiisg[[thread_index_in_simdgroup]],
         uint sgitg[[simdgroup_index_in_threadgroup]]) {
 
-#if QK_K == 64
-    kernel_mul_mv_iq4_nl_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg);
-#else
     kernel_mul_mv_iq4_xs_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg);
-#endif
 }
 
 //============================= templates and their specializations =============================
@@ -5671,10 +5352,9 @@ void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg
     float dl, ml;
     uint8_t sc = xb->scales[il];
 
-#if QK_K == 256
     q = q + 32*(il/8) + 16*(il&1);
     il = (il/2)%4;
-#endif
+
     half  coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
     uchar mask = il>1 ? (il>2 ? 192    : 48)     : (il>0 ? 12    : 3);
     dl = d * (sc & 0xF) * coef, ml = min * (sc >> 4);
@@ -5690,7 +5370,6 @@ void dequantize_q3_K(device const block_q3_K *xb, short il, thread type4x4 & reg
     device const uint8_t * h = (device const uint8_t *)xb->hmask;
     device const int8_t * scales = (device const int8_t *)xb->scales;
 
-#if QK_K == 256
     q = q + 32 * (il/8) + 16 * (il&1);
     h = h + 16 * (il&1);
     uint8_t m = 1 << (il/2);
@@ -5711,17 +5390,6 @@ void dequantize_q3_K(device const block_q3_K *xb, short il, thread type4x4 & reg
     for (int i = 0; i < 16; ++i) {
         reg[i/4][i%4] = dl * (q[i] & mask) - (h[i] & m ? 0 : ml);
     }
-#else
-    float    kcoef = il&1 ? 1.f/16.f : 1.f;
-    uint16_t kmask = il&1 ? 0xF0     : 0x0F;
-    float    dl = d_all * ((scales[il/2] & kmask) * kcoef - 8);
-    float    coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
-    uint8_t  mask = il>1 ? (il>2 ? 192    : 48)     : (il>0 ? 12    : 3);
-    uint8_t  m = 1<<(il*2);
-    for (int i = 0; i < 16; ++i) {
-        reg[i/4][i%4] = coef * dl * ((q[i] & mask) - ((h[i%8] & (m * (1 + i/8))) ? 0 : 4.f/coef));
-    }
-#endif
 }
 
 static inline uchar2 get_scale_min_k4_just2(int j, int k, device const uchar * q) {
@@ -5733,7 +5401,6 @@ template <typename type4x4>
 void dequantize_q4_K(device const block_q4_K *xb, short il, thread type4x4 & reg) {
     device const uchar * q = xb->qs;
 
-#if QK_K == 256
     short is = (il/4) * 2;
     q = q + (il/4) * 32 + 16 * (il&1);
     il = il & 3;
@@ -5742,16 +5409,7 @@ void dequantize_q4_K(device const block_q4_K *xb, short il, thread type4x4 & reg
     const float min = xb->dmin;
     const float dl = d * sc[0];
     const float ml = min * sc[1];
-#else
-    (void) get_scale_min_k4_just2;
 
-    q = q + 16 * (il&1);
-    device const uint8_t * s = xb->scales;
-    device const half2 * dh = (device const half2 *)xb->d;
-    const float2 d = (float2)dh[0];
-    const float dl = il<2 ? d[0] * (s[0]&0xF) : d[0] * (s[1]&0xF)/16.h;
-    const float ml = il<2 ? d[1] * (s[0]>>4)  : d[1] * (s[1]>>4);
-#endif
     const ushort mask = il<2 ? 0x0F : 0xF0;
     for (int i = 0; i < 16; ++i) {
         reg[i/4][i%4] = dl * (q[i] & mask) - ml;
@@ -5763,7 +5421,6 @@ void dequantize_q5_K(device const block_q5_K *xb, short il, thread type4x4 & reg
     device const uint8_t * q  = xb->qs;
     device const uint8_t * qh = xb->qh;
 
-#if QK_K == 256
     short is = (il/4) * 2;
     q  = q + 32 * (il/4) + 16 * (il&1);
     qh = qh + 16 * (il&1);
@@ -5780,17 +5437,6 @@ void dequantize_q5_K(device const block_q5_K *xb, short il, thread type4x4 & reg
     for (int i = 0; i < 16; ++i) {
         reg[i/4][i%4] = dl * ((q[i] & mask) + (qh[i] & ul ? qh_val : 0)) - ml;
     }
-#else
-    q = q + 16 * (il&1);
-    device const int8_t * s = xb->scales;
-    const float dl = xb->d * s[il];
-    uint8_t m = 1<<(il*2);
-    const float  coef = il<2 ? 1.f  : 1.f/16.f;
-    const ushort mask = il<2 ? 0x0F : 0xF0;
-    for (int i = 0; i < 16; ++i) {
-        reg[i/4][i%4] = coef * dl * ((q[i] & mask) - (qh[i%8] & (m*(1+i/8)) ? 0.f : 16.f/coef));
-    }
-#endif
 }
 
 template <typename type4x4>
@@ -5800,15 +5446,11 @@ void dequantize_q6_K(device const block_q6_K *xb, short il, thread type4x4 & reg
     device const uint8_t * qh = (device const uint8_t *)xb->qh;
     device const int8_t * scales = (device const int8_t *)xb->scales;
 
-#if QK_K == 256
     ql = ql + 64*(il/8) + 32*((il/2)&1) + 16*(il&1);
     qh = qh + 32*(il/8) + 16*(il&1);
     float sc = scales[(il%2) + 2 * ((il/2))];
     il = (il/2) & 3;
-#else
-    ql = ql + 16 * (il&1);
-    float sc = scales[il];
-#endif
+
     const uint16_t  kmask1 = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
     const uint16_t  kmask2 = il>1 ? 0xF0              : 0x0F;
     const float       coef = il>1 ? 1.f/16.f          : 1.f;
@@ -5965,20 +5607,15 @@ void dequantize_iq1_m(device const block_iq1_m * xb, short il, thread type4x4 &
     const int ib32 = il/2;
     il = il%2;
     device const uint16_t * sc = (device const uint16_t *)xb->scales;
-#if QK_K == 64
-    const float d = xb->d;
-#else
+
     iq1m_scale_t scale;
     scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
     const float d = scale.f16;
-#endif
+
     device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
     device const uint8_t * qh = xb->qh + 2*ib32 + il;
-#if QK_K == 64
-    const float dl  = d * (2*((sc[ib32/2] >> (8*(ib32%2)+4*il)) & 0xf) + 1);
-#else
+
     const float dl  = d * (2*((sc[ib32/2] >> (6*(ib32%2)+3*il)) & 7) + 1);
-#endif
     const float ml1 = dl * (qh[0] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
     const float ml2 = dl * (qh[0] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
     constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
@@ -6008,9 +5645,6 @@ void dequantize_iq4_nl(device const block_iq4_nl * xb, short il, thread type4x4
 
 template <typename type4x4>
 void dequantize_iq4_xs(device const block_iq4_xs * xb, short il, thread type4x4 & reg) {
-#if QK_K == 64
-    dequantize_iq4_nl(xb, il, reg);
-#else
     // il is 0...15 for QK_K = 256 => index of block of 32 is il/2
     const int ib32 = il/2;
     il = il%2;
@@ -6027,7 +5661,6 @@ void dequantize_iq4_xs(device const block_iq4_xs * xb, short il, thread type4x4
         reg[i][2] = d * kvalues_iq4nl_f[q8[2]];
         reg[i][3] = d * kvalues_iq4nl_f[q8[3]];
     }
-#endif
 }
 
 template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread float4x4 &)>
@@ -6532,11 +6165,7 @@ kernel void kernel_mul_mm_id(
         sgitg);
 }
 
-#if QK_K == 256
 #define QK_NL 16
-#else
-#define QK_NL 4
-#endif
 
 //
 // get rows
@@ -6576,11 +6205,7 @@ template [[host_name("kernel_get_rows_iq2_s")]]   kernel get_rows_t kernel_get_r
 template [[host_name("kernel_get_rows_iq1_s")]]   kernel get_rows_t kernel_get_rows<block_iq1_s,   QK_NL, dequantize_iq1_s>;
 template [[host_name("kernel_get_rows_iq1_m")]]   kernel get_rows_t kernel_get_rows<block_iq1_m,   QK_NL, dequantize_iq1_m>;
 template [[host_name("kernel_get_rows_iq4_nl")]]  kernel get_rows_t kernel_get_rows<block_iq4_nl,  2,     dequantize_iq4_nl>;
-#if QK_K == 64
-template [[host_name("kernel_get_rows_iq4_xs")]]  kernel get_rows_t kernel_get_rows<block_iq4_xs,  2,     dequantize_iq4_xs>;
-#else
 template [[host_name("kernel_get_rows_iq4_xs")]]  kernel get_rows_t kernel_get_rows<block_iq4_xs,  QK_NL, dequantize_iq4_xs>;
-#endif
 
 //
 // matrix-matrix multiplication
@@ -6608,11 +6233,7 @@ template [[host_name("kernel_mul_mm_iq2_s_f32")]]   kernel mat_mm_t kernel_mul_m
 template [[host_name("kernel_mul_mm_iq1_s_f32")]]   kernel mat_mm_t kernel_mul_mm<block_iq1_s,   QK_NL, dequantize_iq1_s>;
 template [[host_name("kernel_mul_mm_iq1_m_f32")]]   kernel mat_mm_t kernel_mul_mm<block_iq1_m,   QK_NL, dequantize_iq1_m>;
 template [[host_name("kernel_mul_mm_iq4_nl_f32")]]  kernel mat_mm_t kernel_mul_mm<block_iq4_nl,  2,     dequantize_iq4_nl>;
-#if QK_K == 64
-template [[host_name("kernel_mul_mm_iq4_xs_f32")]]  kernel mat_mm_t kernel_mul_mm<block_iq4_nl,  2,     dequantize_iq4_xs>;
-#else
 template [[host_name("kernel_mul_mm_iq4_xs_f32")]]  kernel mat_mm_t kernel_mul_mm<block_iq4_xs,  QK_NL, dequantize_iq4_xs>;
-#endif
 
 //
 // indirect matrix-matrix multiplication
@@ -6640,11 +6261,7 @@ template [[host_name("kernel_mul_mm_id_iq2_s_f32")]]   kernel mat_mm_id_t kernel
 template [[host_name("kernel_mul_mm_id_iq1_s_f32")]]   kernel mat_mm_id_t kernel_mul_mm_id<block_iq1_s,   QK_NL, dequantize_iq1_s>;
 template [[host_name("kernel_mul_mm_id_iq1_m_f32")]]   kernel mat_mm_id_t kernel_mul_mm_id<block_iq1_m,   QK_NL, dequantize_iq1_m>;
 template [[host_name("kernel_mul_mm_id_iq4_nl_f32")]]  kernel mat_mm_id_t kernel_mul_mm_id<block_iq4_nl,  2,     dequantize_iq4_nl>;
-#if QK_K == 64
-template [[host_name("kernel_mul_mm_id_iq4_xs_f32")]]  kernel mat_mm_id_t kernel_mul_mm_id<block_iq4_xs,  2,     dequantize_iq4_xs>;
-#else
 template [[host_name("kernel_mul_mm_id_iq4_xs_f32")]]  kernel mat_mm_id_t kernel_mul_mm_id<block_iq4_xs,  QK_NL, dequantize_iq4_xs>;
-#endif
 
 //
 // matrix-vector multiplication
@@ -6853,7 +6470,5 @@ template [[host_name("kernel_mul_mv_id_iq3_xxs_f32")]] kernel kernel_mul_mv_id_t
 template [[host_name("kernel_mul_mv_id_iq3_s_f32")]]   kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq3_s_f32_impl>>;
 template [[host_name("kernel_mul_mv_id_iq2_s_f32")]]   kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq2_s_f32_impl>>;
 template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]]  kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq4_nl_f32_impl>>;
-#if QK_K != 64
 template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]]  kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq4_xs_f32_impl>>;
-#endif
 
diff --git a/ggml-mpi.c b/ggml-mpi.c
deleted file mode 100644
index ae176d707..000000000
--- a/ggml-mpi.c
+++ /dev/null
@@ -1,216 +0,0 @@
-#include "ggml-mpi.h"
-
-#include "ggml.h"
-
-#include <mpi.h>
-
-#include <stdio.h>
-#include <stdlib.h>
-
-#define MIN(a, b) ((a) < (b) ? (a) : (b))
-
-#define UNUSED GGML_UNUSED
-
-struct ggml_mpi_context {
-    int rank;
-    int size;
-};
-
-void ggml_mpi_backend_init(void) {
-    MPI_Init(NULL, NULL);
-}
-
-void ggml_mpi_backend_free(void) {
-    MPI_Finalize();
-}
-
-struct ggml_mpi_context * ggml_mpi_init(void) {
-    struct ggml_mpi_context * ctx = calloc(1, sizeof(struct ggml_mpi_context));
-
-    MPI_Comm_rank(MPI_COMM_WORLD, &ctx->rank);
-    MPI_Comm_size(MPI_COMM_WORLD, &ctx->size);
-
-    return ctx;
-}
-
-void ggml_mpi_free(struct ggml_mpi_context * ctx) {
-    free(ctx);
-}
-
-int ggml_mpi_rank(struct ggml_mpi_context * ctx) {
-    return ctx->rank;
-}
-
-void ggml_mpi_eval_init(
-        struct ggml_mpi_context * ctx_mpi,
-                            int * n_tokens,
-                            int * n_past,
-                            int * n_threads) {
-    UNUSED(ctx_mpi);
-
-    // synchronize the worker node parameters with the root node
-    MPI_Barrier(MPI_COMM_WORLD);
-
-    MPI_Bcast(n_tokens,  1, MPI_INT, 0, MPI_COMM_WORLD);
-    MPI_Bcast(n_past,    1, MPI_INT, 0, MPI_COMM_WORLD);
-    MPI_Bcast(n_threads, 1, MPI_INT, 0, MPI_COMM_WORLD);
-}
-
-static int ggml_graph_get_node_idx(struct ggml_cgraph * gf, const char * name) {
-    struct ggml_tensor * t = ggml_graph_get_tensor(gf, name);
-    if (t == NULL) {
-        fprintf(stderr, "%s: tensor %s not found\n", __func__, name);
-        return -1;
-    }
-
-    for (int i = 0; i < gf->n_nodes; i++) {
-        if (gf->nodes[i] == t) {
-            return i;
-        }
-    }
-
-    fprintf(stderr, "%s: tensor %s not found in graph (should not happen)\n", __func__, name);
-    return -1;
-}
-
-static void ggml_mpi_tensor_send(struct ggml_tensor * t, int mpi_rank_dst) {
-    MPI_Datatype mpi_type;
-
-    switch (t->type) {
-        case GGML_TYPE_I32: mpi_type = MPI_INT32_T; break;
-        case GGML_TYPE_F32: mpi_type = MPI_FLOAT;   break;
-        default: GGML_ASSERT(false && "not implemented");
-    }
-
-    const int retval = MPI_Send(t->data, ggml_nelements(t), mpi_type, mpi_rank_dst, 0, MPI_COMM_WORLD);
-    GGML_ASSERT(retval == MPI_SUCCESS);
-}
-
-static void ggml_mpi_tensor_recv(struct ggml_tensor * t, int mpi_rank_src) {
-    MPI_Datatype mpi_type;
-
-    switch (t->type) {
-        case GGML_TYPE_I32: mpi_type = MPI_INT32_T; break;
-        case GGML_TYPE_F32: mpi_type = MPI_FLOAT;   break;
-        default: GGML_ASSERT(false && "not implemented");
-    }
-
-    MPI_Status status; UNUSED(status);
-
-    const int retval = MPI_Recv(t->data, ggml_nelements(t), mpi_type, mpi_rank_src, MPI_ANY_TAG, MPI_COMM_WORLD, &status);
-    GGML_ASSERT(retval == MPI_SUCCESS);
-}
-
-// TODO: there are many improvements that can be done to this implementation
-void ggml_mpi_graph_compute_pre(
-        struct ggml_mpi_context * ctx_mpi,
-             struct ggml_cgraph * gf,
-                            int   n_layers) {
-    const int mpi_rank = ctx_mpi->rank;
-    const int mpi_size = ctx_mpi->size;
-
-    struct ggml_tensor * inp_tokens = ggml_graph_get_tensor(gf, "inp_tokens");
-    if (inp_tokens == NULL) {
-        fprintf(stderr, "%s: tensor 'inp_tokens' not found\n", __func__);
-        return;
-    }
-
-    struct ggml_tensor * inp0 = ggml_graph_get_tensor(gf, "layer_inp_0");
-    if (inp0 == NULL) {
-        fprintf(stderr, "%s: tensor 'inp0' not found\n", __func__);
-        return;
-    }
-
-    GGML_ASSERT(inp0 == gf->nodes[0]);
-
-    // distribute the compute graph into slices across the MPI nodes
-    //
-    // the main node (0) processes the last layers + the remainder of the compute graph
-    // and is responsible to pass the input tokens to the first node (1)
-    //
-    // node 1:   [(  0) * n_per_node, (  1) * n_per_node)
-    // node 2:   [(  1) * n_per_node, (  2) * n_per_node)
-    // ...
-    // node n-1: [(n-2) * n_per_node, (n-1) * n_per_node)
-    // node 0:   [(n-1) * n_per_node,            n_nodes)
-    //
-    if (mpi_rank > 0) {
-        if (mpi_rank == 1) {
-            // the first node (1) receives the input tokens from the main node (0)
-            ggml_mpi_tensor_recv(inp_tokens, 0);
-        } else {
-            // recv input data for each node into the "inp0" tensor (i.e. the first node in the compute graph)
-            ggml_mpi_tensor_recv(inp0, mpi_rank - 1);
-        }
-    } else if (mpi_size > 1) {
-        // node 0 sends the input tokens to node 1
-        ggml_mpi_tensor_send(inp_tokens, 1);
-
-        // recv the output data from the last node
-        ggml_mpi_tensor_recv(inp0, mpi_size - 1);
-    }
-
-    {
-        const int n_per_node = (n_layers + (mpi_size - 1)) / mpi_size;
-
-        const int mpi_idx = mpi_rank > 0 ? mpi_rank - 1 : mpi_size - 1;
-
-        const int il0 =               (mpi_idx + 0) * n_per_node;
-        const int il1 = MIN(n_layers, (mpi_idx + 1) * n_per_node);
-
-        char name_l0[GGML_MAX_NAME];
-        char name_l1[GGML_MAX_NAME];
-
-        snprintf(name_l0, sizeof(name_l0), "layer_inp_%d", il0);
-        snprintf(name_l1, sizeof(name_l1), "layer_inp_%d", il1);
-
-        const int idx_l0 =                ggml_graph_get_node_idx(gf, name_l0);
-        const int idx_l1 = mpi_rank > 0 ? ggml_graph_get_node_idx(gf, name_l1) + 1 : gf->n_nodes;
-
-        if (idx_l0 < 0 || idx_l1 < 0) {
-            fprintf(stderr, "%s: layer input nodes not found\n", __func__);
-            return;
-        }
-
-        // attach the input data to all nodes that need it
-        // TODO: not great - should be able to do this without modifying the compute graph (see next TODO below)
-        for (int i = idx_l0; i < idx_l1; i++) {
-            if (gf->nodes[i]->src[0] == gf->nodes[idx_l0]) {
-                gf->nodes[i]->src[0] =  inp0;
-            }
-            if (gf->nodes[i]->src[1] == gf->nodes[idx_l0]) {
-                gf->nodes[i]->src[1] =  inp0;
-            }
-        }
-
-        // TODO: instead of rearranging the nodes, we should be able to execute a subset of the compute graph
-        for (int i = 1; i < idx_l1 - idx_l0; i++) {
-            gf->nodes[i] = gf->nodes[idx_l0 + i];
-            gf->grads[i] = gf->grads[idx_l0 + i];
-        }
-
-        // the first node performs the "get_rows" operation, the rest of the nodes get the data from the previous node
-        if (mpi_idx != 0) {
-            gf->nodes[0]->op = GGML_OP_NONE;
-        }
-
-        gf->n_nodes = idx_l1 - idx_l0;
-
-        //fprintf(stderr, "%s: node %d: processing %d nodes [%d, %d)\n", __func__, mpi_rank, gf->n_nodes, il0, il1);
-    }
-}
-
-void ggml_mpi_graph_compute_post(
-        struct ggml_mpi_context * ctx_mpi,
-             struct ggml_cgraph * gf,
-                            int   n_layers) {
-    UNUSED(n_layers);
-
-    const int mpi_rank = ctx_mpi->rank;
-    const int mpi_size = ctx_mpi->size;
-
-    // send the output data to the next node
-    if (mpi_rank > 0) {
-        ggml_mpi_tensor_send(gf->nodes[gf->n_nodes - 1], (mpi_rank + 1) % mpi_size);
-    }
-}
diff --git a/ggml-mpi.h b/ggml-mpi.h
deleted file mode 100644
index eda119d44..000000000
--- a/ggml-mpi.h
+++ /dev/null
@@ -1,39 +0,0 @@
-#pragma once
-
-struct ggml_context;
-struct ggml_tensor;
-struct ggml_cgraph;
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-struct ggml_mpi_context;
-
-void ggml_mpi_backend_init(void);
-void ggml_mpi_backend_free(void);
-
-struct ggml_mpi_context * ggml_mpi_init(void);
-void ggml_mpi_free(struct ggml_mpi_context * ctx);
-
-int ggml_mpi_rank(struct ggml_mpi_context * ctx);
-
-void ggml_mpi_eval_init(
-        struct ggml_mpi_context * ctx_mpi,
-                            int * n_tokens,
-                            int * n_past,
-                            int * n_threads);
-
-void ggml_mpi_graph_compute_pre(
-        struct ggml_mpi_context * ctx_mpi,
-             struct ggml_cgraph * gf,
-                            int   n_layers);
-
-void ggml_mpi_graph_compute_post(
-        struct ggml_mpi_context * ctx_mpi,
-             struct ggml_cgraph * gf,
-                            int   n_layers);
-
-#ifdef __cplusplus
-}
-#endif
diff --git a/ggml-opencl.cpp b/ggml-opencl.cpp
index 880a14958..e28566a7b 100644
--- a/ggml-opencl.cpp
+++ b/ggml-opencl.cpp
@@ -1835,7 +1835,10 @@ static void ggml_cl_mul_mat_q_f32(const ggml_tensor * src0, const ggml_tensor *
                     CL_CHECK(clEnqueueNDRangeKernel(queue, *to_fp32_cl, 1, &offset, &global, local > 0 ? &local : NULL, events.size(), !events.empty() ? events.data() : NULL, NULL));
                 }
 
-                for (int64_t i12 = i02 * r2, e12 = i12 + r2; i12 < e12; i12++) {
+                int64_t i12 = i02 * r2;
+                int64_t e12 = i12 + r2;
+                events.reserve(e12 - i12);
+                for (; i12 < e12; i12++) {
                     if (mul_mat_vec) { // specialized dequantize_mul_mat_vec kernel
                         // copy src1 to device
                         events.emplace_back();
diff --git a/ggml-quants.c b/ggml-quants.c
index 9b291d522..bb01ce93c 100644
--- a/ggml-quants.c
+++ b/ggml-quants.c
@@ -14,6 +14,12 @@
 #include <stdlib.h> // for qsort
 #include <stdio.h>  // for GGML_ASSERT
 
+#define GROUP_MAX_EPS 1e-15f
+#define GROUP_MAX_EPS_IQ3_XXS 1e-8f
+#define GROUP_MAX_EPS_IQ2_S 1e-8f
+#define GROUP_MAX_EPS_IQ1_M 1e-7f
+#define GROUP_MAX_EPS_IQ1_S 1e-12f
+
 #if defined(_MSC_VER)
 // disable "possible loss of data" to avoid warnings for hundreds of casts
 // we should just be careful :)
@@ -256,6 +262,403 @@ static const uint64_t table_b2b_0[1 << 8] = { B8(00, 10) }; // ( b) << 4
 static const uint64_t table_b2b_1[1 << 8] = { B8(10, 00) }; // (!b) << 4
 #endif
 
+#if defined(__loongarch_asx)
+
+#ifdef __clang__
+#define VREGS_PREFIX "$vr"
+#define XREGS_PREFIX "$xr"
+#else // GCC
+#define VREGS_PREFIX "$f"
+#define XREGS_PREFIX "$f"
+#endif
+#define __ALL_REGS "0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31"
+// Convert __m128i to __m256i
+static inline __m256i ____m256i(__m128i in) {
+    __m256i out = __lasx_xvldi(0);
+    __asm__ volatile (
+        ".irp i," __ALL_REGS                "\n\t"
+        " .ifc %[out], " XREGS_PREFIX"\\i    \n\t"
+        "  .irp j," __ALL_REGS              "\n\t"
+        "   .ifc %[in], " VREGS_PREFIX "\\j  \n\t"
+        "    xvpermi.q $xr\\i, $xr\\j, 0x20  \n\t"
+        "   .endif                           \n\t"
+        "  .endr                             \n\t"
+        " .endif                             \n\t"
+        ".endr                               \n\t"
+        : [out] "+f" (out) : [in] "f" (in)
+    );
+    return out;
+}
+// Convert two __m128i to __m256i
+static inline __m256i lasx_set_q(__m128i inhi, __m128i inlo) {
+    __m256i out;
+    __asm__ volatile (
+        ".irp i," __ALL_REGS                "\n\t"
+        " .ifc %[hi], " VREGS_PREFIX "\\i    \n\t"
+        "  .irp j," __ALL_REGS              "\n\t"
+        "   .ifc %[lo], " VREGS_PREFIX "\\j  \n\t"
+        "    xvpermi.q $xr\\i, $xr\\j, 0x20  \n\t"
+        "   .endif                           \n\t"
+        "  .endr                             \n\t"
+        " .endif                             \n\t"
+        ".endr                               \n\t"
+        ".ifnc %[out], %[hi]                 \n\t"
+        ".irp i," __ALL_REGS                "\n\t"
+        " .ifc %[out], " XREGS_PREFIX "\\i   \n\t"
+        "  .irp j," __ALL_REGS              "\n\t"
+        "   .ifc %[hi], " VREGS_PREFIX "\\j  \n\t"
+        "    xvori.b $xr\\i, $xr\\j, 0       \n\t"
+        "   .endif                           \n\t"
+        "  .endr                             \n\t"
+        " .endif                             \n\t"
+        ".endr                               \n\t"
+        ".endif                              \n\t"
+        : [out] "=f" (out), [hi] "+f" (inhi)
+        : [lo] "f" (inlo)
+    );
+    return out;
+}
+// Convert __m256i low part to __m128i
+static inline __m128i lasx_extracti128_lo(__m256i in) {
+    __m128i out;
+    __asm__ volatile (
+        ".ifnc %[out], %[in]                 \n\t"
+        ".irp i," __ALL_REGS                "\n\t"
+        " .ifc %[out], " VREGS_PREFIX "\\i   \n\t"
+        "  .irp j," __ALL_REGS              "\n\t"
+        "   .ifc %[in], " XREGS_PREFIX "\\j  \n\t"
+        "    vori.b $vr\\i, $vr\\j, 0        \n\t"
+        "   .endif                           \n\t"
+        "  .endr                             \n\t"
+        " .endif                             \n\t"
+        ".endr                               \n\t"
+        ".endif                              \n\t"
+        : [out] "=f" (out) : [in] "f" (in)
+    );
+    return out;
+}
+// Convert __m256i high part to __m128i
+static inline __m128i lasx_extracti128_hi(__m256i in) {
+    __m128i out;
+    __asm__ volatile (
+        ".irp i," __ALL_REGS                "\n\t"
+        " .ifc %[out], " VREGS_PREFIX "\\i   \n\t"
+        "  .irp j," __ALL_REGS              "\n\t"
+        "   .ifc %[in], " XREGS_PREFIX "\\j  \n\t"
+        "    xvpermi.q $xr\\i, $xr\\j, 0x11  \n\t"
+        "   .endif                           \n\t"
+        "  .endr                             \n\t"
+        " .endif                             \n\t"
+        ".endr                               \n\t"
+        : [out] "=f" (out) : [in] "f" (in)
+    );
+    return out;
+}
+
+static __m256i lasx_set_w(int e7, int e6, int e5, int e4, int e3, int e2, int e1, int e0) {
+    v8i32 __ret = {e0, e1, e2, e3, e4, e5, e6, e7};
+    return (__m256i)__ret;
+}
+
+static __m128i lsx_set_w(int32_t a, int32_t b, int32_t c, int32_t d) {
+    v4i32 __ret = {d, c, b, a};
+    return (__m128i)__ret;
+}
+
+static __m256i lasx_set_d(int64_t a, int64_t b, int64_t c, int64_t d) {
+    v4i64 __ret = {d, c, b, a};
+    return (__m256i)__ret;
+}
+
+static __m256i lasx_insertf128( __m128i x, __m128i y) {
+    return lasx_set_q(x, y);
+}
+
+static __m128i lsx_shuffle_b(__m128i a, __m128i b) {
+    __m128i mask_f, zero, tmp0, tmp2, mask;
+    int f = 0x8f;
+    mask_f = __lsx_vreplgr2vr_b(f);
+    zero = __lsx_vldi(0);
+    tmp0 = __lsx_vand_v(b, mask_f); // get mask with low 4 bit and sign bits
+    tmp0 = __lsx_vori_b(tmp0, 0x10); // make each mask or  with 0x10 prepare for positive
+    mask = __lsx_vsle_b(zero, tmp0); // if mask >= 0, set mask
+    tmp2 = __lsx_vand_v(tmp0, mask); // maskout the in2 < ones
+    return __lsx_vshuf_b(a, zero, tmp2);
+}
+
+static __m256i lasx_shuffle_b(__m256i a, __m256i b) {
+    __m256i mask_f, zero, tmp0, tmp2, mask;
+    int f = 0x8f;
+    mask_f = __lasx_xvreplgr2vr_b(f);
+    zero = __lasx_xvldi(0);
+    tmp0 = __lasx_xvand_v(b, mask_f); // get mask with low 4 bit and sign bits
+    tmp0 = __lasx_xvori_b(tmp0, 0x10); // make each mask or  with 0x10 prepare for positive
+    mask = __lasx_xvsle_b(zero, tmp0); // if mask >= 0, set mask
+    tmp2 = __lasx_xvand_v(tmp0, mask); // maskout the in2 < ones
+    return __lasx_xvshuf_b(a, zero, tmp2);
+}
+
+static __m256i lasx_extu8_16(__m128i a) {
+    __m128i zero = __lsx_vldi(0);
+    __m128i vlo = __lsx_vilvl_b(zero, a);
+    __m128i vhi = __lsx_vilvh_b(zero, a);
+    return lasx_set_q(vhi, vlo);
+}
+
+static __m256i lasx_ext8_16(__m128i a) {
+     __m128i sign = __lsx_vslti_b(a, 0);
+     __m128i vlo = __lsx_vilvl_b(sign, a);
+     __m128i vhi = __lsx_vilvh_b(sign, a);
+     return lasx_set_q(vhi, vlo);
+}
+
+static __m256i lasx_ext16_32(__m128i a) {
+    __m256i tmp1;
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 0), 0);
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 1), 1);
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 2), 2);
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 3), 3);
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 4), 4);
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 5), 5);
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 6), 6);
+    tmp1 = __lasx_xvinsgr2vr_w(tmp1, __lsx_vpickve2gr_h(a, 7), 7);
+    return tmp1;
+}
+
+static __m128i lasx_extracti128( __m256i a, int pos) {
+    __m128i ret;
+    if( pos == 0)
+    {
+       ret = lasx_extracti128_lo(a);
+    } else {
+       ret = lasx_extracti128_hi(a);
+    }
+    return ret;
+}
+
+static __m128 lasx_extractf128( __m256 a, int pos) {
+    __m128 ret;
+    if( pos == 0)
+    {
+       ret = (__m128)lasx_extracti128_lo((__m256i)a);
+    } else {
+       ret = (__m128)lasx_extracti128_hi((__m256i)a);
+    }
+    return ret;
+}
+
+static __m128i lsx_hadd_h(__m128i a, __m128i b) {
+    __m128i tmp1 = __lsx_vpickev_h(b, a);
+    __m128i tmp2 = __lsx_vpickod_h(b, a);
+    return __lsx_vadd_h(tmp1, tmp2);
+}
+
+static __m128i lsx_hadd_w(__m128i a, __m128i b) {
+    __m128i tmp1 = __lsx_vpickev_w(b, a);
+    __m128i tmp2 = __lsx_vpickod_w(b, a);
+    return __lsx_vadd_w(tmp1, tmp2);
+}
+
+static __m128 lsx_hadd_s(__m128 a, __m128 b) {
+    __m128 tmp1 = (__m128)__lsx_vpickev_w((__m128i)b, (__m128i)a);
+    __m128 tmp2 = (__m128)__lsx_vpickod_w((__m128i)b, (__m128i)a);
+
+    return __lsx_vfadd_s(tmp1, tmp2);
+}
+
+static __m256i lasx_maddubs_h(__m256i a, __m256i b) {
+    __m256i tmp1, tmp2;
+    tmp1 = __lasx_xvmulwev_h_b(a, b);
+    tmp2 = __lasx_xvmulwod_h_b(a, b);
+    return __lasx_xvsadd_h(tmp1, tmp2);
+}
+
+static __m256i lasx_madd_h(__m256i a, __m256i b) {
+    __m256i tmp1, tmp2;
+    tmp1 = __lasx_xvmulwev_w_h(a, b);
+    tmp2 = __lasx_xvmulwod_w_h(a, b);
+    return __lasx_xvadd_w(tmp1, tmp2);
+}
+
+static __m256i lasx_packs_w(__m256i a, __m256i b) {
+    __m256i tmp, tmp1;
+    tmp = __lasx_xvsat_w(a, 15);
+    tmp1 = __lasx_xvsat_w(b, 15);
+    return __lasx_xvpickev_h(tmp1, tmp);
+}
+
+static __m256i lasx_packs_h(__m256i a, __m256i b) {
+    __m256i tmp, tmp1;
+    tmp = __lasx_xvsat_h(a, 7);
+    tmp1 = __lasx_xvsat_h(b, 7);
+    return __lasx_xvpickev_b(tmp1, tmp);
+}
+
+static __m128i lsx_packs_w(__m128i a, __m128i b) {
+    __m128i tmp, tmp1;
+    tmp = __lsx_vsat_w(a, 15);
+    tmp1 = __lsx_vsat_w(b, 15);
+    return __lsx_vpickev_h(tmp1, tmp);
+}
+
+static __m128i lsx_packs_h(__m128i a, __m128i b) {
+    __m128i tmp, tmp1;
+    tmp = __lsx_vsat_h(a, 7);
+    tmp1 = __lsx_vsat_h(b, 7);
+    return __lsx_vpickev_b(tmp1, tmp);
+}
+
+static __m128i lsx_packus_h(__m128i a, __m128i b) {
+    __m128i tmp, tmp1;
+    tmp = __lsx_vsat_hu(a, 7);
+    tmp1 = __lsx_vsat_hu(b, 7);
+    return __lsx_vpickev_b(tmp1, tmp);
+}
+
+
+static __m128i lsx_maddubs_h(__m128i a, __m128i b) {
+    __m128i tmp1, tmp2;
+    tmp1 = __lsx_vmulwev_h_b(a, b);
+    tmp2 = __lsx_vmulwod_h_b(a, b);
+    return __lsx_vsadd_h(tmp1, tmp2);
+}
+
+static __m128i lsx_madd_h(__m128i a, __m128i b) {
+    __m128i tmp1, tmp2;
+    tmp1 = __lsx_vmulwev_w_h(a, b);
+    tmp2 = __lsx_vmulwod_w_h(a, b);
+    return __lsx_vadd_w(tmp1, tmp2);
+}
+
+// multiply int8_t, add results pairwise twice
+static inline __m128i mul_sum_i8_pairs(const __m128i x, const __m128i y) {
+    // Get absolute values of x vectors
+    const __m128i ax = __lsx_vsigncov_b(x, x);
+    // Sign the values of the y vectors
+    const __m128i sy = __lsx_vsigncov_b(x, y);
+    // Perform multiplication and create 16-bit values
+    const __m128i dot = lsx_maddubs_h(ax, sy);
+    const __m128i ones = __lsx_vreplgr2vr_h(1);
+    return lsx_madd_h(ones, dot);
+}
+
+// horizontally add 8 floats
+static inline float hsum_float_8(const __m256 x) {
+    __m128 res = lasx_extractf128(x, 1);
+    ft_union tmp;
+    res = __lsx_vfadd_s(res, lasx_extractf128(x, 0));
+    res = __lsx_vfadd_s(res, (__m128)__lsx_vpickod_d((__m128i)res, (__m128i)res));
+    res = __lsx_vfadd_s(res, (__m128)__lsx_vinsgr2vr_w(__lsx_vldi(0), __lsx_vpickve2gr_w(res, 1), 0));
+    tmp.i = __lsx_vpickve2gr_w(res, 0);
+    return tmp.f;
+}
+
+// horizontally add 8 int32_t
+static inline int hsum_i32_8(const __m256i a) {
+
+    __m256i tmp1 = __lasx_xvpermi_q(a, a, 0x11);
+    __m256i tmp2 = __lasx_xvpermi_q(a, a, 0x00);
+
+    __m128i  tmp1_128 = lasx_extracti128_lo(tmp1);
+    __m128i  tmp2_128 = lasx_extracti128_lo(tmp2);
+
+    __m128i sum128 = __lsx_vadd_w(tmp1_128, tmp2_128);
+
+    __m128i ev = __lsx_vpickev_w(sum128, sum128);
+    __m128i od = __lsx_vpickod_w(sum128, sum128);
+    __m128i sum64 = __lsx_vadd_w(ev, od);
+
+    int sum64_1, sum64_2;
+    sum64_1 = __lsx_vpickve2gr_w(sum64, 0);
+    sum64_2 = __lsx_vpickve2gr_w(sum64, 1);
+
+    return  sum64_1 + sum64_2;
+}
+
+// horizontally add 4 int32_t
+static inline int hsum_i32_4(const __m128i a) {
+    __m128i ev = __lsx_vpickev_w(a, a);
+    __m128i od = __lsx_vpickod_w(a, a);
+    __m128i sum64 = __lsx_vadd_w(ev, od);
+
+    int sum64_1, sum64_2;
+    sum64_1 = __lsx_vpickve2gr_w(sum64, 0);
+    sum64_2 = __lsx_vpickve2gr_w(sum64, 1);
+
+    return  sum64_1 + sum64_2;
+}
+
+// spread 32 bits to 32 bytes { 0x00, 0xFF }
+static inline __m256i bytes_from_bits_32(const uint8_t * x) {
+
+    uint32_t x32;
+    memcpy(&x32, x, sizeof(uint32_t));
+    const __m256i shuf_mask = lasx_set_d(
+            0x0303030303030303, 0x0202020202020202,
+            0x0101010101010101, 0x0000000000000000);
+
+    __m256i bytes = lasx_shuffle_b(__lasx_xvreplgr2vr_w(x32), shuf_mask);
+    const __m256i bit_mask = __lasx_xvreplgr2vr_d(0x7fbfdfeff7fbfdfe);
+    bytes = __lasx_xvor_v(bytes, bit_mask);
+    return __lasx_xvseq_b(bytes, __lasx_xvreplgr2vr_d(-1));
+}
+
+// Unpack 32 4-bit fields into 32 bytes
+// The output vector contains 32 bytes, each one in [ 0 .. 15 ] interval
+static inline __m256i bytes_from_nibbles_32(const uint8_t * rsi) {
+    const __m128i lo = __lsx_vld((const __m128i *)rsi, 0);
+    __m128i hi = __lsx_vsrli_h(lo, 4);
+    return __lasx_xvandi_b(lasx_insertf128(hi, lo), 0xf);
+}
+
+// add int16_t pairwise and return as float vector
+static inline __m256 sum_i16_pairs_float(const __m256i x) {
+    __m256i v = __lasx_xvpackod_h(x, x);
+    __m256i summed_pairs = __lasx_xvaddwev_w_h(x, v);
+    return __lasx_xvffint_s_w(summed_pairs);
+}
+
+static inline __m256 mul_sum_us8_pairs_float(const __m256i ax, const __m256i sy) {
+    // Perform multiplication and create 16-bit values
+    const __m256i dot = lasx_maddubs_h(ax, sy);
+    return sum_i16_pairs_float(dot);
+}
+
+// multiply int8_t, add results pairwise twice and return as float vector
+static inline __m256 mul_sum_i8_pairs_float(const __m256i x, const __m256i y) {
+
+    // Get absolute values of x vectors
+    const __m256i ax = __lasx_xvsigncov_b(x, x);
+    // Sign the values of the y vectors
+    const __m256i sy = __lasx_xvsigncov_b(x, y);
+
+    return mul_sum_us8_pairs_float(ax, sy);
+}
+
+static inline __m128i packNibbles( __m256i bytes ) {
+    // Move bits within 16-bit lanes from 0000_abcd_0000_efgh into 0000_0000_abcd_efgh
+    const __m256i lowByte = __lasx_xvreplgr2vr_h(0xFF);
+     __m256i high = __lasx_xvandn_v(lowByte, bytes);
+    __m256i low = __lasx_xvand_v(lowByte, bytes);
+    high = __lasx_xvsrli_h(high, 4);
+    bytes = __lasx_xvor_v(low, high);
+    // Compress uint16_t lanes into bytes
+    __m128i *r0 = (__m128i *)&bytes;
+    __m256i tmp_h128 = __lasx_xvpermi_q(bytes, bytes, 0x11);
+    __m128i *r1 = (__m128i *)&tmp_h128;
+
+    __m128i zero = __lsx_vldi(0);
+    __m128i tmp, tmp2, tmp3;
+
+    tmp = __lsx_vmax_h(zero, *r0);
+    tmp2 = __lsx_vsat_hu(tmp, 7);
+
+    tmp = __lsx_vmax_h(zero, *r1);
+    tmp3 = __lsx_vsat_hu(tmp, 7);
+    return  __lsx_vpickev_b(tmp3, tmp2);
+}
+#endif  //__loongarch_asx
+
 // reference implementation for deterministic creation of model files
 void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict y, int64_t k) {
     static const int qk = QK4_0;
@@ -643,6 +1046,7 @@ void quantize_row_q8_0(const float * restrict x, void * restrict vy, int64_t k)
         // store result
         __riscv_vse8_v_i8m1(y[i].qs , vs, vl);
     }
+
 #elif defined(__POWER9_VECTOR__)
     for (int i = 0; i < nb; i++) {
         vector float srcv [8];
@@ -674,6 +1078,69 @@ void quantize_row_q8_0(const float * restrict x, void * restrict vy, int64_t k)
         }
         vec_xst(vec_pack(vec_pack(vi[0], vi[1]), vec_pack(vi[2], vi[3])),  0, &y[i].qs[0]);
         vec_xst(vec_pack(vec_pack(vi[4], vi[5]), vec_pack(vi[6], vi[7])), 16, &y[i].qs[0]);
+
+#elif defined(__loongarch_asx)
+    for (int i = 0; i < nb; i++) {
+        ft_union fi;
+        __m256 v0 = (__m256)__lasx_xvld( x , 0);
+        __m256 v1 = (__m256)__lasx_xvld( x , 32);
+        __m256 v2 = (__m256)__lasx_xvld( x , 64);
+        __m256 v3 = (__m256)__lasx_xvld( x , 96);
+        x += 32;
+
+        // Compute max(abs(e)) for the block
+        const __m256 sign_bit = __lasx_xvreplfr2vr_s( -0.0f );
+        __m256 max_abs = (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v0 );
+        max_abs = __lasx_xvfmax_s( max_abs, (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v1 ) );
+        max_abs = __lasx_xvfmax_s( max_abs, (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v2 ) );
+        max_abs = __lasx_xvfmax_s( max_abs, (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v3 ) );
+
+        __m128 max4 = __lsx_vfmax_s( lasx_extractf128( max_abs, 1 ), lasx_extractf128( max_abs , 0) );
+        max4 = __lsx_vfmax_s( max4, (__m128)__lsx_vpickod_d((__m128i) max4, (__m128i)max4 ) );
+        __m128 tmp = max4;
+        max4 = __lsx_vfmax_s( max4, (__m128)__lsx_vinsgr2vr_w(tmp, __lsx_vpickve2gr_w( max4, 1 ), 0 ));
+        fi.i = __lsx_vpickve2gr_w( (__m128i)max4, 0 );
+        const float max_scalar = fi.f;
+
+        // Quantize these floats
+        const float d = max_scalar / 127.f;
+        y[i].d = GGML_FP32_TO_FP16(d);
+        const float id = ( max_scalar != 0.0f ) ? 127.f / max_scalar : 0.0f;
+        const __m256 mul = (__m256)__lasx_xvreplfr2vr_s( id );
+
+        // Apply the multiplier
+        v0 = __lasx_xvfmul_s( v0, mul );
+        v1 = __lasx_xvfmul_s( v1, mul );
+        v2 = __lasx_xvfmul_s( v2, mul );
+        v3 = __lasx_xvfmul_s( v3, mul );
+
+        // Round to nearest integer
+        __m256i i0 = __lasx_xvftintrne_w_s( v0 );
+        __m256i i1 = __lasx_xvftintrne_w_s( v1 );
+        __m256i i2 = __lasx_xvftintrne_w_s( v2 );
+        __m256i i3 = __lasx_xvftintrne_w_s( v3 );
+
+        __m128i ni0 = lasx_extracti128( i0, 0 );
+        __m128i ni1 = lasx_extracti128( i0, 1);
+        __m128i ni2 = lasx_extracti128( i1, 0);
+        __m128i ni3 = lasx_extracti128( i1, 1);
+        __m128i ni4 = lasx_extracti128( i2, 0);
+        __m128i ni5 = lasx_extracti128( i2, 1);
+        __m128i ni6 = lasx_extracti128( i3, 0);
+        __m128i ni7 = lasx_extracti128( i3, 1);
+
+        // Convert int32 to int16
+        ni0 = lsx_packs_w( ni0, ni1 );
+        ni2 = lsx_packs_w( ni2, ni3 );
+        ni4 = lsx_packs_w( ni4, ni5 );
+        ni6 = lsx_packs_w( ni6, ni7 );
+        // Convert int16 to int8
+        ni0 = lsx_packs_h( ni0, ni2 );
+        ni4 = lsx_packs_h( ni4, ni6 );
+
+        __lsx_vst(ni0, (__m128i *)(y[i].qs +  0), 0);
+        __lsx_vst(ni4, (__m128i *)(y[i].qs + 16), 0);
+
     }
 #else
     GGML_UNUSED(nb);
@@ -822,12 +1289,12 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
         __m128 max4 = _mm_max_ps( _mm256_extractf128_ps( maxAbs, 1 ), _mm256_castps256_ps128( maxAbs ) );
         max4 = _mm_max_ps( max4, _mm_movehl_ps( max4, max4 ) );
         max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4 ) );
-        const float maxScalar = _mm_cvtss_f32( max4 );
+        const float max_scalar = _mm_cvtss_f32( max4 );
 
         // Quantize these floats
-        const float d = maxScalar / 127.f;
+        const float d = max_scalar / 127.f;
         y[i].d = GGML_FP32_TO_FP16(d);
-        const float id = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f;
+        const float id = ( max_scalar != 0.0f ) ? 127.f / max_scalar : 0.0f;
         const __m256 mul = _mm256_set1_ps( id );
 
         // Apply the multiplier
@@ -930,6 +1397,7 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
         int sum = __riscv_vmv_x_s_i16m1_i16(vwrs);
         y[i].s = GGML_FP32_TO_FP16(sum*d);
     }
+
 #elif defined(__POWER9_VECTOR__)
     for (int i = 0; i < nb; i++) {
         vector float srcv [8];
@@ -969,6 +1437,73 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
         accv = vec_add(accv, vec_sld(accv, accv, 4));
         accv = vec_add(accv, vec_sld(accv, accv, 8));
         y[i].s = GGML_FP32_TO_FP16(d * vec_extract(accv, 0));
+
+#elif defined(__loongarch_asx)
+    for (int i = 0; i < nb; i++) {
+        ft_union ft;
+        __m256 v0 = (__m256)__lasx_xvld( x , 0 );
+        __m256 v1 = (__m256)__lasx_xvld( x , 32 );
+        __m256 v2 = (__m256)__lasx_xvld( x , 64 );
+        __m256 v3 = (__m256)__lasx_xvld( x , 96 );
+        x += 32;
+
+        // Compute max(abs(e)) for the block
+        const __m256 sign_bit = __lasx_xvreplfr2vr_s( -0.0f );
+        __m256 max_abs = (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v0 );
+        max_abs = __lasx_xvfmax_s( max_abs, (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v1 ) );
+        max_abs = __lasx_xvfmax_s( max_abs, (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v2 ) );
+        max_abs = __lasx_xvfmax_s( max_abs, (__m256)__lasx_xvandn_v( (__m256i)sign_bit, (__m256i)v3 ) );
+
+        __m128 max4 = __lsx_vfmax_s( lasx_extractf128( max_abs, 1 ), lasx_extractf128( max_abs, 0) );
+        max4 = __lsx_vfmax_s( max4, (__m128)__lsx_vpickod_d((__m128i) max4, (__m128i)max4 ) );
+        __m128 tmp = max4;
+        max4 = __lsx_vfmax_s( max4, (__m128)__lsx_vextrins_w((__m128i)tmp, (__m128i)max4, 0x10 ));
+        ft.i = __lsx_vpickve2gr_w( (__m128i)max4, 0 );
+        const float max_scalar = ft.f;
+
+        // Quantize these floats
+        const float d = max_scalar / 127.f;
+        y[i].d = GGML_FP32_TO_FP16(d);
+        const float id = ( max_scalar != 0.0f ) ? 127.f / max_scalar : 0.0f;
+        const __m256 mul = __lasx_xvreplfr2vr_s( id );
+
+        // Apply the multiplier
+        v0 = __lasx_xvfmul_s( v0, mul );
+        v1 = __lasx_xvfmul_s( v1, mul );
+        v2 = __lasx_xvfmul_s( v2, mul );
+        v3 = __lasx_xvfmul_s( v3, mul );
+
+        // Round to nearest integer
+        __m256i i0 = __lasx_xvftintrne_w_s( v0 );
+        __m256i i1 = __lasx_xvftintrne_w_s( v1 );
+        __m256i i2 = __lasx_xvftintrne_w_s( v2 );
+        __m256i i3 = __lasx_xvftintrne_w_s( v3 );
+
+        __m128i ni0 = lasx_extracti128(i0, 0);
+        __m128i ni1 = lasx_extracti128( i0, 1);
+        __m128i ni2 = lasx_extracti128( i1, 0);
+        __m128i ni3 = lasx_extracti128( i1, 1);
+        __m128i ni4 = lasx_extracti128( i2, 0 );
+        __m128i ni5 = lasx_extracti128( i2, 1);
+        __m128i ni6 = lasx_extracti128( i3, 0);
+        __m128i ni7 = lasx_extracti128( i3, 1);
+
+        // Compute the sum of the quants and set y[i].s
+        const __m128i s0 = __lsx_vadd_w(__lsx_vadd_w(ni0, ni1), __lsx_vadd_w(ni2, ni3));
+        const __m128i s1 = __lsx_vadd_w(__lsx_vadd_w(ni4, ni5), __lsx_vadd_w(ni6, ni7));
+        y[i].s = GGML_FP32_TO_FP16(d * hsum_i32_4(__lsx_vadd_w(s0, s1)));
+
+        // Convert int32 to int16
+        ni0 = lsx_packs_w( ni0, ni1 );
+        ni2 = lsx_packs_w( ni2, ni3 );
+        ni4 = lsx_packs_w( ni4, ni5 );
+        ni6 = lsx_packs_w( ni6, ni7 );
+        // Convert int16 to int8
+        ni0 = lsx_packs_h( ni0, ni2 );
+        ni4 = lsx_packs_h( ni4, ni6 );
+
+        __lsx_vst(ni0, (__m128i *)(y[i].qs +  0), 0);
+        __lsx_vst(ni4, (__m128i *)(y[i].qs + 16), 0);
     }
 #else
     GGML_UNUSED(nb);
@@ -1109,7 +1644,7 @@ static float make_qx_quants(int n, int nmax, const float * restrict x, int8_t *
         float ax = fabsf(x[i]);
         if (ax > amax) { amax = ax; max = x[i]; }
     }
-    if (amax < 1e-30f) { // all zero
+    if (amax < GROUP_MAX_EPS) { // all zero
         for (int i = 0; i < n; ++i) {
             L[i] = 0;
         }
@@ -1143,7 +1678,7 @@ static float make_qx_quants(int n, int nmax, const float * restrict x, int8_t *
         sumlx += w*x[i]*l;
         suml2 += w*l*l;
     }
-    float scale = sumlx/suml2;
+    float scale = suml2 ? sumlx/suml2 : 0.0f;
     if (return_early) return suml2 > 0 ? 0.5f*(scale + 1/iscale) : 1/iscale;
     float best = scale * sumlx;
     for (int is = -9; is <= 9; ++is) {
@@ -1177,7 +1712,7 @@ static float make_q3_quants(int n, int nmax, const float * restrict x, int8_t *
         float ax = fabsf(x[i]);
         if (ax > amax) { amax = ax; max = x[i]; }
     }
-    if (!amax) { // all zero
+    if (amax < GROUP_MAX_EPS) { // all zero
         for (int i = 0; i < n; ++i) { L[i] = 0; }
         return 0.f;
     }
@@ -1353,7 +1888,6 @@ static float make_qkx2_quants(int n, int nmax, const float * restrict x, const f
     return scale;
 }
 
-#if QK_K == 256
 static inline void get_scale_min_k4(int j, const uint8_t * restrict q, uint8_t * restrict d, uint8_t * restrict m) {
     if (j < 4) {
         *d = q[j] & 63; *m = q[j + 4] & 63;
@@ -1362,7 +1896,6 @@ static inline void get_scale_min_k4(int j, const uint8_t * restrict q, uint8_t *
         *m = (q[j+4] >>  4) | ((q[j-0] >> 6) << 4);
     }
 }
-#endif
 
 //========================- 2-bit (de)-quantization
 
@@ -1426,20 +1959,13 @@ void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict
             }
         }
 
-#if QK_K == 256
         for (int j = 0; j < QK_K; j += 128) {
             for (int l = 0; l < 32; ++l) {
                 y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6);
             }
         }
-#else
-        for (int l = 0; l < 16; ++l) {
-            y[i].qs[l] = L[l] | (L[l + 16] << 2) | (L[l + 32] << 4) | (L[l + 48] << 6);
-        }
-#endif
 
         x += QK_K;
-
     }
 }
 
@@ -1454,7 +1980,6 @@ void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int6
 
         const uint8_t * q = x[i].qs;
 
-#if QK_K == 256
         int is = 0;
         float dl, ml;
         for (int n = 0; n < QK_K; n += 128) {
@@ -1473,19 +1998,6 @@ void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int6
             }
             q += 32;
         }
-#else
-        float dl1 = d * (x[i].scales[0] & 0xF), ml1 = min * (x[i].scales[0] >> 4);
-        float dl2 = d * (x[i].scales[1] & 0xF), ml2 = min * (x[i].scales[1] >> 4);
-        float dl3 = d * (x[i].scales[2] & 0xF), ml3 = min * (x[i].scales[2] >> 4);
-        float dl4 = d * (x[i].scales[3] & 0xF), ml4 = min * (x[i].scales[3] >> 4);
-        for (int l = 0; l < 16; ++l) {
-            y[l+ 0] = dl1 * ((int8_t)((q[l] >> 0) & 3)) - ml1;
-            y[l+16] = dl2 * ((int8_t)((q[l] >> 2) & 3)) - ml2;
-            y[l+32] = dl3 * ((int8_t)((q[l] >> 4) & 3)) - ml3;
-            y[l+48] = dl4 * ((int8_t)((q[l] >> 6) & 3)) - ml4;
-        }
-        y += QK_K;
-#endif
     }
 }
 
@@ -1646,7 +2158,7 @@ static float make_qp_quants(int n, int nmax, const float * restrict x, uint8_t *
             break;
         }
     }
-    return sumlx / suml2;
+    return sumlx/suml2;
 }
 
 static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restrict y, int k, const float * restrict quant_weights) {
@@ -1676,36 +2188,9 @@ static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restri
         }
 
         float dm, mm;
-#if QK_K == 64
-        float max_scale = 0, max_min = 0;
-        for (int j = 0; j < QK_K/16; ++j) {
-            max_scale = MAX(max_scale, scales[j]);
-            max_min   = MAX(max_min,   mins[j]);
-        }
-        dm = max_scale/15;
-        mm = max_min/15;
-        if (max_scale) {
-            float id = 1/dm;
-            for (int j = 0; j < QK_K/16; ++j) {
-                int l = nearest_int(id*scales[j]);
-                Ls[j] = MAX(0, MIN(15, l));
-            }
-        } else {
-            memset(Ls, 0, QK_K/16);
-        }
-        if (max_min) {
-            float id = 1/mm;
-            for (int j = 0; j < QK_K/16; ++j) {
-                int l = nearest_int(id*mins[j]);
-                Lm[j] = MAX(0, MIN(15, l));
-            }
-        } else {
-            memset(Lm, 0, QK_K/16);
-        }
-#else
         dm  = make_qp_quants(QK_K/16, 15, scales, Ls, sw);
         mm  = make_qp_quants(QK_K/16, 15, mins,   Lm, sw);
-#endif
+
         y[i].d    = GGML_FP32_TO_FP16(dm);
         y[i].dmin = GGML_FP32_TO_FP16(mm);
         dm        = GGML_FP16_TO_FP32(y[i].d);
@@ -1728,20 +2213,13 @@ static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restri
             }
         }
 
-#if QK_K == 256
         for (int j = 0; j < QK_K; j += 128) {
             for (int l = 0; l < 32; ++l) {
                 y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6);
             }
         }
-#else
-        for (int l = 0; l < 16; ++l) {
-            y[i].qs[l] = L[l] | (L[l + 16] << 2) | (L[l + 32] << 4) | (L[l + 48] << 6);
-        }
-#endif
 
         x += QK_K;
-
     }
 }
 
@@ -1782,7 +2260,6 @@ void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict
             }
         }
 
-#if QK_K == 256
         memset(y[i].scales, 0, 12);
         if (max_scale) {
             float iscale = -32.f/max_scale;
@@ -1816,36 +2293,6 @@ void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict
                 L[16*j + ii] = l + 4;
             }
         }
-#else
-        if (max_scale) {
-            float iscale = -8.f/max_scale;
-            for (int j = 0; j < QK_K/16; j+=2) {
-                int l1 = nearest_int(iscale*scales[j]);
-                l1 = 8 + MAX(-8, MIN(7, l1));
-                int l2 = nearest_int(iscale*scales[j+1]);
-                l2 = 8 + MAX(-8, MIN(7, l2));
-                y[i].scales[j/2] = l1 | (l2 << 4);
-            }
-            y[i].d = GGML_FP32_TO_FP16(1/iscale);
-        } else {
-            for (int j = 0; j < QK_K/16; j+=2) {
-                y[i].scales[j/2] = 0;
-            }
-            y[i].d = GGML_FP32_TO_FP16(0.f);
-        }
-        for (int j = 0; j < QK_K/16; ++j) {
-            int s = j%2 == 0 ? y[i].scales[j/2] & 0xF : y[i].scales[j/2] >> 4;
-            float d = GGML_FP16_TO_FP32(y[i].d) * (s - 8);
-            if (!d) {
-                continue;
-            }
-            for (int ii = 0; ii < 16; ++ii) {
-                int l = nearest_int(x[16*j + ii]/d);
-                l = MAX(-4, MIN(3, l));
-                L[16*j + ii] = l + 4;
-            }
-        }
-#endif
 
         memset(y[i].hmask, 0, QK_K/8);
         // We put the high-bit for the 1st 8 quants into bit 0, the next 8 into bit 1, etc.
@@ -1860,23 +2307,16 @@ void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict
                 m = 0; hm <<= 1;
             }
         }
-#if QK_K == 256
         for (int j = 0; j < QK_K; j += 128) {
             for (int l = 0; l < 32; ++l) {
                 y[i].qs[j/4 + l] = L[j + l] | (L[j + l + 32] << 2) | (L[j + l + 64] << 4) | (L[j + l + 96] << 6);
             }
         }
-#else
-        for (int l = 0; l < 16; ++l) {
-            y[i].qs[l] = L[l] | (L[l + 16] << 2) | (L[l + 32] << 4) | (L[l + 48] << 6);
-        }
-#endif
 
         x += QK_K;
     }
 }
 
-#if QK_K == 256
 void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
@@ -1926,49 +2366,12 @@ void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int6
 
     }
 }
-#else
-void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int64_t k) {
-    assert(k % QK_K == 0);
-    assert(QK_K == 64);
-    const int nb = k / QK_K;
-
-    for (int i = 0; i < nb; i++) {
-
-        const float d_all = GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8_t * restrict q = x[i].qs;
-        const uint8_t * restrict hm = x[i].hmask;
-
-        const float d1 = d_all * ((x[i].scales[0] & 0xF) - 8);
-        const float d2 = d_all * ((x[i].scales[0] >>  4) - 8);
-        const float d3 = d_all * ((x[i].scales[1] & 0xF) - 8);
-        const float d4 = d_all * ((x[i].scales[1] >>  4) - 8);
-
-        for (int l=0; l<8; ++l) {
-            uint8_t h = hm[l];
-            y[l+ 0] = d1 * ((int8_t)((q[l+0] >> 0) & 3) - ((h & 0x01) ? 0 : 4));
-            y[l+ 8] = d1 * ((int8_t)((q[l+8] >> 0) & 3) - ((h & 0x02) ? 0 : 4));
-            y[l+16] = d2 * ((int8_t)((q[l+0] >> 2) & 3) - ((h & 0x04) ? 0 : 4));
-            y[l+24] = d2 * ((int8_t)((q[l+8] >> 2) & 3) - ((h & 0x08) ? 0 : 4));
-            y[l+32] = d3 * ((int8_t)((q[l+0] >> 4) & 3) - ((h & 0x10) ? 0 : 4));
-            y[l+40] = d3 * ((int8_t)((q[l+8] >> 4) & 3) - ((h & 0x20) ? 0 : 4));
-            y[l+48] = d4 * ((int8_t)((q[l+0] >> 6) & 3) - ((h & 0x40) ? 0 : 4));
-            y[l+56] = d4 * ((int8_t)((q[l+8] >> 6) & 3) - ((h & 0x80) ? 0 : 4));
-        }
-        y += QK_K;
-    }
-}
-#endif
 
 void quantize_row_q3_K(const float * restrict x, void * restrict vy, int64_t k) {
     quantize_row_q3_K_reference(x, vy, k);
 }
 
 static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restrict y, int64_t n_per_row, const float * restrict quant_weights) {
-#if QK_K != 256
-    (void)quant_weights;
-    quantize_row_q3_K_reference(x, y, n_per_row);
-#else
     assert(n_per_row % QK_K == 0);
     const int nb = n_per_row / QK_K;
 
@@ -2050,7 +2453,6 @@ static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restri
 
         x += QK_K;
     }
-#endif
 }
 
 size_t quantize_q3_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
@@ -2082,7 +2484,6 @@ void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict
     float scales[QK_K/32];
 
     for (int i = 0; i < nb; i++) {
-
         float max_scale = 0; // as we are deducting the min, scales are always positive
         float max_min = 0;
         for (int j = 0; j < QK_K/32; ++j) {
@@ -2102,7 +2503,6 @@ void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict
             }
         }
 
-#if QK_K == 256
         float inv_scale = max_scale > 0 ? 63.f/max_scale : 0.f;
         float inv_min   = max_min   > 0 ? 63.f/max_min   : 0.f;
         for (int j = 0; j < QK_K/32; ++j) {
@@ -2134,39 +2534,7 @@ void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict
                 L[32*j + ii] = l;
             }
         }
-#else
-        const float s_factor = 15.f;
-        float inv_scale = max_scale > 0 ? s_factor/max_scale : 0.f;
-        float inv_min   = max_min   > 0 ? s_factor/max_min   : 0.f;
-        int d1 = nearest_int(inv_scale*scales[0]);
-        int m1 = nearest_int(inv_min*mins[0]);
-        int d2 = nearest_int(inv_scale*scales[1]);
-        int m2 = nearest_int(inv_min*mins[1]);
-        y[i].scales[0] = d1 | (m1 << 4);
-        y[i].scales[1] = d2 | (m2 << 4);
-        y[i].d[0] = GGML_FP32_TO_FP16(max_scale/s_factor);
-        y[i].d[1] = GGML_FP32_TO_FP16(max_min/s_factor);
 
-        float sumlx = 0;
-        int   suml2 = 0;
-        for (int j = 0; j < QK_K/32; ++j) {
-            const uint8_t sd = y[i].scales[j] & 0xF;
-            const uint8_t sm = y[i].scales[j] >>  4;
-            const float d = GGML_FP16_TO_FP32(y[i].d[0]) * sd;
-            if (!d) continue;
-            const float m = GGML_FP16_TO_FP32(y[i].d[1]) * sm;
-            for (int ii = 0; ii < 32; ++ii) {
-                int l = nearest_int((x[32*j + ii] + m)/d);
-                l = MAX(0, MIN(15, l));
-                L[32*j + ii] = l;
-                sumlx += (x[32*j + ii] + m)*l*sd;
-                suml2 += l*l*sd*sd;
-            }
-        }
-        if (suml2) {
-            y[i].d[0] = GGML_FP32_TO_FP16(sumlx/suml2);
-        }
-#endif
         uint8_t * q = y[i].qs;
         for (int j = 0; j < QK_K; j += 64) {
             for (int l = 0; l < 32; ++l) q[l] = L[j + l] | (L[j + l + 32] << 4);
@@ -2174,7 +2542,6 @@ void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict
         }
 
         x += QK_K;
-
     }
 }
 
@@ -2183,11 +2550,8 @@ void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int6
     const int nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
-
         const uint8_t * q = x[i].qs;
 
-#if QK_K == 256
-
         const float d   = GGML_FP16_TO_FP32(x[i].d);
         const float min = GGML_FP16_TO_FP32(x[i].dmin);
 
@@ -2202,18 +2566,6 @@ void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int6
             for (int l = 0; l < 32; ++l) *y++ = d2 * (q[l]  >> 4) - m2;
             q += 32; is += 2;
         }
-#else
-        const float dall = GGML_FP16_TO_FP32(x[i].d[0]);
-        const float mall = GGML_FP16_TO_FP32(x[i].d[1]);
-        const float d1 = dall * (x[i].scales[0] & 0xF), m1 = mall * (x[i].scales[0] >> 4);
-        const float d2 = dall * (x[i].scales[1] & 0xF), m2 = mall * (x[i].scales[1] >> 4);
-        for (int l = 0; l < 32; ++l) {
-            y[l+ 0] = d1 * (q[l] & 0xF) - m1;
-            y[l+32] = d2 * (q[l] >>  4) - m2;
-        }
-        y += QK_K;
-#endif
-
     }
 }
 
@@ -2224,10 +2576,6 @@ void quantize_row_q4_K(const float * restrict x, void * restrict vy, int64_t k)
 }
 
 static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restrict y, int64_t n_per_row, const float * quant_weights) {
-#if QK_K != 256
-    (void)quant_weights;
-    quantize_row_q4_K_reference(x, y, n_per_row);
-#else
     assert(n_per_row % QK_K == 0);
     const int64_t nb = n_per_row / QK_K;
 
@@ -2298,7 +2646,6 @@ static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restri
         x += QK_K;
 
     }
-#endif
 }
 
 size_t quantize_q4_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
@@ -2323,21 +2670,13 @@ void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict
     assert(k % QK_K == 0);
     const int64_t nb = k / QK_K;
 
-#if QK_K == 256
     uint8_t L[QK_K];
     float mins[QK_K/32];
     float scales[QK_K/32];
     float weights[32];
     uint8_t Laux[32];
-#else
-    int8_t L[QK_K];
-    float scales[QK_K/16];
-#endif
 
     for (int i = 0; i < nb; i++) {
-
-#if QK_K == 256
-
         float max_scale = 0; // as we are deducting the min, scales are always positive
         float max_min = 0;
         for (int j = 0; j < QK_K/32; ++j) {
@@ -2409,55 +2748,8 @@ void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict
             m1 <<= 2; m2 <<= 2;
             ql += 32;
         }
-#else
-        float max_scale = 0, amax = 0;
-        for (int j = 0; j < QK_K/16; ++j) {
-            scales[j] = make_qx_quants(16, 16, x + 16*j, L + 16*j, 1, NULL);
-            float abs_scale = fabsf(scales[j]);
-            if (abs_scale > amax) {
-                amax = abs_scale;
-                max_scale = scales[j];
-            }
-        }
-
-        float iscale = -128.f/max_scale;
-        for (int j = 0; j < QK_K/16; ++j) {
-            int l = nearest_int(iscale*scales[j]);
-            y[i].scales[j] = MAX(-128, MIN(127, l));
-        }
-        y[i].d = GGML_FP32_TO_FP16(1/iscale);
-
-        for (int j = 0; j < QK_K/16; ++j) {
-            const float d = GGML_FP16_TO_FP32(y[i].d) * y[i].scales[j];
-            if (!d) continue;
-            for (int ii = 0; ii < 16; ++ii) {
-                int l = nearest_int(x[16*j + ii]/d);
-                l = MAX(-16, MIN(15, l));
-                L[16*j + ii] = l + 16;
-            }
-        }
-
-        uint8_t * restrict qh = y[i].qh;
-        uint8_t * restrict ql = y[i].qs;
-        memset(qh, 0, QK_K/8);
-
-        for (int j = 0; j < 32; ++j) {
-            int jm = j%8;
-            int is = j/8;
-            int l1 = L[j];
-            if (l1 > 15) {
-                l1 -= 16; qh[jm] |= (1 << is);
-            }
-            int l2 = L[j + 32];
-            if (l2 > 15) {
-                l2 -= 16; qh[jm] |= (1 << (4 + is));
-            }
-            ql[j] = l1 | (l2 << 4);
-        }
-#endif
 
         x += QK_K;
-
     }
 }
 
@@ -2466,12 +2758,9 @@ void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int6
     const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
-
         const uint8_t * ql = x[i].qs;
         const uint8_t * qh = x[i].qh;
 
-#if QK_K == 256
-
         const float d = GGML_FP16_TO_FP32(x[i].d);
         const float min = GGML_FP16_TO_FP32(x[i].dmin);
 
@@ -2488,21 +2777,6 @@ void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int6
             ql += 32; is += 2;
             u1 <<= 2; u2 <<= 2;
         }
-#else
-        float d = GGML_FP16_TO_FP32(x[i].d);
-        const int8_t * restrict s = x[i].scales;
-        for (int l = 0; l < 8; ++l) {
-            y[l+ 0] = d * s[0] * ((ql[l+ 0] & 0xF) - (qh[l] & 0x01 ? 0 : 16));
-            y[l+ 8] = d * s[0] * ((ql[l+ 8] & 0xF) - (qh[l] & 0x02 ? 0 : 16));
-            y[l+16] = d * s[1] * ((ql[l+16] & 0xF) - (qh[l] & 0x04 ? 0 : 16));
-            y[l+24] = d * s[1] * ((ql[l+24] & 0xF) - (qh[l] & 0x08 ? 0 : 16));
-            y[l+32] = d * s[2] * ((ql[l+ 0] >>  4) - (qh[l] & 0x10 ? 0 : 16));
-            y[l+40] = d * s[2] * ((ql[l+ 8] >>  4) - (qh[l] & 0x20 ? 0 : 16));
-            y[l+48] = d * s[3] * ((ql[l+16] >>  4) - (qh[l] & 0x40 ? 0 : 16));
-            y[l+56] = d * s[3] * ((ql[l+24] >>  4) - (qh[l] & 0x80 ? 0 : 16));
-        }
-        y += QK_K;
-#endif
     }
 }
 
@@ -2513,10 +2787,6 @@ void quantize_row_q5_K(const float * restrict x, void * restrict vy, int64_t k)
 }
 
 static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restrict y, int64_t n_per_row, const float * quant_weights) {
-#if QK_K != 256
-    (void)quant_weights;
-    quantize_row_q5_K_reference(x, y, n_per_row);
-#else
     assert(n_per_row % QK_K == 0);
     const int64_t nb = n_per_row / QK_K;
 
@@ -2607,7 +2877,6 @@ static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restri
         x += QK_K;
 
     }
-#endif
 }
 
 size_t quantize_q5_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
@@ -2653,7 +2922,7 @@ void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict
 
         }
 
-        if (!max_abs_scale) {
+        if (max_abs_scale < GROUP_MAX_EPS) {
             memset(&y[i], 0, sizeof(block_q6_K));
             y[i].d = GGML_FP32_TO_FP16(0.f);
             x += QK_K;
@@ -2680,7 +2949,6 @@ void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict
 
         uint8_t * restrict ql = y[i].ql;
         uint8_t * restrict qh = y[i].qh;
-#if QK_K == 256
         for (int j = 0; j < QK_K; j += 128) {
             for (int l = 0; l < 32; ++l) {
                 const uint8_t q1 = L[j + l +  0] & 0xF;
@@ -2694,19 +2962,8 @@ void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict
             ql += 64;
             qh += 32;
         }
-#else
-        for (int l = 0; l < 32; ++l) {
-            const uint8_t q1 = L[l +  0] & 0xF;
-            const uint8_t q2 = L[l + 32] & 0xF;
-            ql[l] = q1 | (q2 << 4);
-        }
-        for (int l = 0; l < 16; ++l) {
-            qh[l] = (L[l] >> 4) | ((L[l + 16] >> 4) << 2) | ((L[l + 32] >> 4) << 4) | ((L[l + 48] >> 4) << 6);
-        }
-#endif
 
         x += QK_K;
-
     }
 }
 
@@ -2715,14 +2972,12 @@ void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int6
     const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
-
         const float d = GGML_FP16_TO_FP32(x[i].d);
 
         const uint8_t * restrict ql = x[i].ql;
         const uint8_t * restrict qh = x[i].qh;
         const int8_t  * restrict sc = x[i].scales;
 
-#if QK_K == 256
         for (int n = 0; n < QK_K; n += 128) {
             for (int l = 0; l < 32; ++l) {
                 int is = l/16;
@@ -2740,20 +2995,6 @@ void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int6
             qh += 32;
             sc += 8;
         }
-#else
-        for (int l = 0; l < 16; ++l) {
-            const int8_t q1 = (int8_t)((ql[l+ 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
-            const int8_t q2 = (int8_t)((ql[l+16] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
-            const int8_t q3 = (int8_t)((ql[l+ 0]  >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32;
-            const int8_t q4 = (int8_t)((ql[l+16]  >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32;
-            y[l+ 0] = d * sc[0] * q1;
-            y[l+16] = d * sc[1] * q2;
-            y[l+32] = d * sc[2] * q3;
-            y[l+48] = d * sc[3] * q4;
-        }
-        y  += 64;
-#endif
-
     }
 }
 
@@ -2764,10 +3005,6 @@ void quantize_row_q6_K(const float * restrict x, void * restrict vy, int64_t k)
 }
 
 static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restrict y, int64_t n_per_row, const float * quant_weights) {
-#if QK_K != 256
-    (void)quant_weights;
-    quantize_row_q6_K_reference(x, y, n_per_row);
-#else
     assert(n_per_row % QK_K == 0);
     const int64_t nb = n_per_row / QK_K;
 
@@ -2805,7 +3042,7 @@ static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restri
 
         }
 
-        if (!max_abs_scale) {
+        if (max_abs_scale < GROUP_MAX_EPS) {
             memset(&y[i], 0, sizeof(block_q6_K));
             y[i].d = GGML_FP32_TO_FP16(0.f);
             x += QK_K;
@@ -2849,7 +3086,6 @@ static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restri
         x += QK_K;
 
     }
-#endif
 }
 
 size_t quantize_q6_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
@@ -3266,30 +3502,21 @@ void dequantize_row_iq1_m(const block_iq1_m * restrict x, float * restrict y, in
     float delta[4];
     uint16_t idx[4];
 
-#if QK_K != 64
     iq1m_scale_t scale;
-#endif
 
     for (int i = 0; i < nb; i++) {
 
         const uint16_t * sc = (const uint16_t *)x[i].scales;
-#if QK_K == 64
-        const float d = GGML_FP16_TO_FP32(x[i].d);
-#else
         scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
         const float d = GGML_FP16_TO_FP32(scale.f16);
-#endif
+
         const uint8_t * qs = x[i].qs;
         const uint8_t * qh = x[i].qh;
 
         for (int ib = 0; ib < QK_K/32; ++ib) {
-#if QK_K == 64
-            const float dl1 = d * (2*((sc[ib/2] >> (8*(ib%2)+0)) & 0xf) + 1);
-            const float dl2 = d * (2*((sc[ib/2] >> (8*(ib%2)+4)) & 0xf) + 1);
-#else
             const float dl1 = d * (2*((sc[ib/2] >> (6*(ib%2)+0)) & 0x7) + 1);
             const float dl2 = d * (2*((sc[ib/2] >> (6*(ib%2)+3)) & 0x7) + 1);
-#endif
+
             idx[0] = qs[0] | ((qh[0] << 8) & 0x700);
             idx[1] = qs[1] | ((qh[0] << 4) & 0x700);
             idx[2] = qs[2] | ((qh[1] << 8) & 0x700);
@@ -3340,9 +3567,6 @@ void dequantize_row_iq4_nl(const block_iq4_nl * restrict x, float * restrict y,
 
 void dequantize_row_iq4_xs(const block_iq4_xs * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-#if QK_K == 64
-    dequantize_row_iq4_nl((const block_iq4_nl *)x, y, k);
-#else
     const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
@@ -3362,7 +3586,6 @@ void dequantize_row_iq4_xs(const block_iq4_xs * restrict x, float * restrict y,
             qs += 16;
         }
     }
-#endif
 }
 
 //===================================== Q8_K ==============================================
@@ -3464,6 +3687,43 @@ static inline __m128i get_scale_shuffle(int i) {
     };
     return _mm_loadu_si128((const __m128i*)k_shuffle + i);
 }
+#elif defined(__loongarch_asx)
+// shuffles to pick the required scales in dot products
+static inline __m256i get_scale_shuffle_q3k(int i) {
+    static const uint8_t k_shuffle[128] = {
+         0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1,     2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3,
+         4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5,     6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7,
+         8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9,    10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,
+        12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,    14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,
+    };
+    return __lasx_xvld((const __m256i*)k_shuffle + i, 0);
+}
+static inline __m256i get_scale_shuffle_k4(int i) {
+    static const uint8_t k_shuffle[256] = {
+         0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1,
+         2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3,
+         4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5,
+         6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7,
+         8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9,
+        10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,
+        12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13,
+        14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15
+    };
+    return __lasx_xvld((const __m256i*)k_shuffle + i, 0);
+}
+static inline __m128i get_scale_shuffle(int i) {
+    static const uint8_t k_shuffle[128] = {
+         0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
+         2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3,
+         4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5,
+         6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7,
+         8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9,
+        10,10,10,10,10,10,10,10, 11,11,11,11,11,11,11,11,
+        12,12,12,12,12,12,12,12, 13,13,13,13,13,13,13,13,
+        14,14,14,14,14,14,14,14, 15,15,15,15,15,15,15,15
+    };
+    return __lsx_vld((const __m128i*)k_shuffle + i, 0);
+}
 #endif
 
 void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
@@ -3813,6 +4073,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     }
 
     *s = sumf;
+
 #elif defined(__POWER9_VECTOR__)
     const vector signed char lowMask = vec_splats((signed char)0xF);
     const vector unsigned char v4 = vec_splats((unsigned char)0x4);
@@ -3853,6 +4114,149 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+    // Initialize accumulator with zeros
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    // Main loop
+    for (int i = 0; i < nb; ++i) {
+        /* Compute combined scale for the block */
+        const __m256 d = __lasx_xvreplfr2vr_s( GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d) );
+
+        __m256i qx = bytes_from_nibbles_32(x[i].qs);
+
+        // Now we have a vector with bytes in [ 0 .. 15 ] interval. Offset them into [ -8 .. +7 ] interval.
+        const __m256i off = __lasx_xvreplgr2vr_b( 8 );
+        qx = __lasx_xvsub_b( qx, off );
+
+        __m256i qy = __lasx_xvld((const __m256i *)y[i].qs, 0);
+
+        const __m256 q = mul_sum_i8_pairs_float(qx, qy);
+
+        /* Multiply q with scale and accumulate */
+        acc = __lasx_xvfmadd_s( d, q, acc );
+    }
+
+    *s = hsum_float_8(acc);
+#elif defined(__loongarch_sx)
+    // set constants
+    const __m128i low_mask = __lsx_vreplgr2vr_b(0xF);
+    const __m128i off = __lsx_vreplgr2vr_b(8);
+
+    // Initialize accumulator with zeros
+    __m128 acc_0 = __lsx_vldi(0);
+    __m128 acc_1 = __lsx_vldi(0);
+    __m128 acc_2 = __lsx_vldi(0);
+    __m128 acc_3 = __lsx_vldi(0);
+
+    // First round without accumulation
+    {
+        _mm_prefetch(&x[0] + sizeof(block_q4_0), _MM_HINT_T0);
+        _mm_prefetch(&y[0] + sizeof(block_q8_0), _MM_HINT_T0);
+
+        // Compute combined scale for the block 0 and 1
+        const __m128 d_0_1 = __lsx_vreplgr2vr_w( GGML_FP16_TO_FP32(x[0].d) * GGML_FP16_TO_FP32(y[0].d) );
+
+        const __m128i tmp_0_1 = __lsx_vld((const __m128i *)x[0].qs, 0);
+
+        __m128i bx_0 = __lsx_vand_v(low_mask, tmp_0_1);
+        __m128i by_0 = __lsx_vld((const __m128i *)y[0].qs, 0);
+        bx_0 = __lsx_vsub_b(bx_0, off);
+        const __m128i i32_0 = mul_sum_i8_pairs(bx_0, by_0);
+
+        __m128i bx_1 = __lsx_vand_v(low_mask, __lsx_vsrli_d(tmp_0_1, 4));
+        __m128i by_1 = __lsx_vld((const __m128i *)(y[0].qs + 16), 0);
+        bx_1 = __lsx_vsub_b(bx_1, off);
+        const __m128i i32_1 = mul_sum_i8_pairs(bx_1, by_1);
+
+        // Compute combined scale for the block 2 and 3
+        const __m128 d_2_3 = __lsx_vreplgr2vr_w( GGML_FP16_TO_FP32(x[1].d) * GGML_FP16_TO_FP32(y[1].d) );
+
+        const __m128i tmp_2_3 = __lsx_vld((const __m128i *)x[1].qs, 0);
+
+        __m128i bx_2 = __lsx_vand_v(low_mask, tmp_2_3);
+        __m128i by_2 = __lsx_vld((const __m128i *)y[1].qs, 0);
+        bx_2 = __lsx_vsub_b(bx_2, off);
+        const __m128i i32_2 = mul_sum_i8_pairs(bx_2, by_2);
+
+        __m128i bx_3 = __lsx_vand_v(low_mask, __lsx_vsrli_d(tmp_2_3, 4));
+        __m128i by_3 = __lsx_vld((const __m128i *)(y[1].qs + 16), 0);
+        bx_3 = __lsx_vsub_b(bx_3, off);
+        const __m128i i32_3 = mul_sum_i8_pairs(bx_3, by_3);
+
+        // Convert int32_t to float
+        __m128 p0 = __lsx_vffint_s_w(i32_0);
+        __m128 p1 = __lsx_vffint_s_w(i32_1);
+        __m128 p2 = __lsx_vffint_s_w(i32_2);
+        __m128 p3 = __lsx_vffint_s_w(i32_3);
+
+        // Apply the scale
+        acc_0 = __lsx_vfmul_s( d_0_1, p0 );
+        acc_1 = __lsx_vfmul_s( d_0_1, p1 );
+        acc_2 = __lsx_vfmul_s( d_2_3, p2 );
+        acc_3 = __lsx_vfmul_s( d_2_3, p3 );
+    }
+
+    assert(nb % 2 == 0); // TODO: handle odd nb
+
+    // Main loop
+    for (int i = 2; i < nb; i+=2) {
+
+        // Compute combined scale for the block 0 and 1
+        const __m128 d_0_1 = __lsx_vreplgr2vr_w( GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d) );
+
+        const __m128i tmp_0_1 = __lsx_vld((const __m128i *)x[i].qs, 0);
+
+        __m128i bx_0 = __lsx_vand_v(low_mask, tmp_0_1);
+        __m128i by_0 = __lsx_vld((const __m128i *)y[i].qs, 0);
+        bx_0 = __lsx_vsub_b(bx_0, off);
+        const __m128i i32_0 = mul_sum_i8_pairs(bx_0, by_0);
+
+        __m128i bx_1 = __lsx_vand_v(low_mask, __lsx_vsrli_d(tmp_0_1, 4));
+        __m128i by_1 = __lsx_vld((const __m128i *)(y[i].qs + 16), 0);
+        bx_1 = __lsx_vsub_b(bx_1, off);
+        const __m128i i32_1 = mul_sum_i8_pairs(bx_1, by_1);
+
+        //_mm_prefetch(&x[i] + 2 * sizeof(block_q4_0), _MM_HINT_T0);
+        //_mm_prefetch(&y[i] + 2 * sizeof(block_q8_0), _MM_HINT_T0);
+
+        // Compute combined scale for the block 2 and 3
+        const __m128 d_2_3 = __lsx_vreplgr2vr_w( GGML_FP16_TO_FP32(x[i + 1].d) * GGML_FP16_TO_FP32(y[i + 1].d) );
+
+        const __m128i tmp_2_3 = __lsx_vld((const __m128i *)x[i + 1].qs, 0);
+
+        __m128i bx_2 = __lsx_vand_v(low_mask, tmp_2_3);
+        __m128i by_2 = __lsx_vld((const __m128i *)y[i + 1].qs, 0);
+        bx_2 = __lsx_vsub_b(bx_2, off);
+        const __m128i i32_2 = mul_sum_i8_pairs(bx_2, by_2);
+
+        __m128i bx_3 = __lsx_vand_v(low_mask, __lsx_vsrli_d(tmp_2_3, 4));
+        __m128i by_3 = __lsx_vld((const __m128i *)(y[i + 1].qs + 16), 0);
+        bx_3 = __lsx_vsub_b(bx_3, off);
+        const __m128i i32_3 = mul_sum_i8_pairs(bx_3, by_3);
+
+        // Convert int32_t to float
+        __m128 p0 = __lsx_vffint_s_w(i32_0);
+        __m128 p1 = __lsx_vffint_s_w(i32_1);
+        __m128 p2 = __lsx_vffint_s_w(i32_2);
+        __m128 p3 = __lsx_vffint_s_w(i32_3);
+
+        // Apply the scale
+        __m128 p0_d = __lsx_vfmul_s( d_0_1, p0 );
+        __m128 p1_d = __lsx_vfmul_s( d_0_1, p1 );
+        __m128 p2_d = __lsx_vfmul_s( d_2_3, p2 );
+        __m128 p3_d = __lsx_vfmul_s( d_2_3, p3 );
+
+        // Acummulate
+        acc_0 = __lsx_vfadd_s(p0_d, acc_0);
+        acc_1 = __lsx_vfadd_s(p1_d, acc_1);
+        acc_2 = __lsx_vfadd_s(p2_d, acc_2);
+        acc_3 = __lsx_vfadd_s(p3_d, acc_3);
+    }
+
+    *s = hsum_float_4x4(acc_0, acc_1, acc_2, acc_3);
+
 #else
     // scalar
     float sumf = 0.0;
@@ -4072,6 +4476,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * restrict s, size_t bs, const void * r
     }
 
     *s = sumf;
+
 #elif defined(__POWER9_VECTOR__)
     const vector signed char lowMask = vec_splats((signed char)0xF);
     const vector unsigned char v4 = vec_splats((unsigned char)0x4);
@@ -4112,6 +4517,38 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * restrict s, size_t bs, const void * r
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+    // Initialize accumulator with zeros
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    float summs = 0;
+
+    // Main loop
+    for (int i = 0; i < nb; ++i) {
+        const float d0 = GGML_FP16_TO_FP32(x[i].d);
+        const float d1 = GGML_FP16_TO_FP32(y[i].d);
+
+        summs += GGML_FP16_TO_FP32(x[i].m) * GGML_FP16_TO_FP32(y[i].s);
+
+        const __m256 d0v = __lasx_xvreplfr2vr_s( d0 );
+        const __m256 d1v = __lasx_xvreplfr2vr_s( d1 );
+
+        // Compute combined scales
+        const __m256 d0d1 = __lasx_xvfmul_s( d0v, d1v );
+
+        // Load 16 bytes, and unpack 4 bit fields into bytes, making 32 bytes
+        const __m256i qx = bytes_from_nibbles_32(x[i].qs);
+        const __m256i qy = __lasx_xvld( (const __m256i *)y[i].qs, 0);
+
+        const __m256 xy = mul_sum_us8_pairs_float(qx, qy);
+
+        // Accumulate d0*d1*x*y
+        acc = __lasx_xvfmadd_s( d0d1, xy, acc );
+    }
+
+    *s = hsum_float_8(acc) + summs;
+
 #else
     // scalar
     float sumf = 0.0;
@@ -4397,6 +4834,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     }
 
     *s = sumf;
+
 #elif defined(__POWER9_VECTOR__)
     const vector signed char lowMask = vec_splats((signed char)0xF);
     const vector unsigned char v4 = vec_splats((unsigned char)4);
@@ -4440,6 +4878,31 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+    // Initialize accumulator with zeros
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    // Main loop
+    for (int i = 0; i < nb; i++) {
+        /* Compute combined scale for the block */
+        const __m256 d = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d)); //FIXME
+
+        __m256i qx = bytes_from_nibbles_32(x[i].qs);
+        __m256i bxhi = bytes_from_bits_32(x[i].qh);
+        bxhi = __lasx_xvandn_v(bxhi, __lasx_xvreplgr2vr_b((char)0xF0));
+        qx = __lasx_xvor_v(qx, bxhi);
+
+        __m256i qy = __lasx_xvld((const __m256i *)y[i].qs, 0);
+
+        const __m256 q = mul_sum_i8_pairs_float(qx, qy);
+
+        /* Multiply q with scale and accumulate */
+        acc = __lasx_xvfmadd_s(d, q, acc);
+    }
+
+    *s = hsum_float_8(acc);
+
 #else
     // scalar
     float sumf = 0.0;
@@ -4744,6 +5207,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * restrict s, size_t bs, const void * r
     }
 
     *s = sumf;
+
 #elif defined(__POWER9_VECTOR__)
     const vector signed char lowMask = vec_splats((signed char)0xF);
     const vector unsigned char v4 = vec_splats((unsigned char)0x4);
@@ -4791,6 +5255,34 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * restrict s, size_t bs, const void * r
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+    // Initialize accumulator with zeros
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    float summs = 0.0f;
+
+    // Main loop
+    for (int i = 0; i < nb; i++) {
+        const __m256 dx = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[i].d));
+
+        summs += GGML_FP16_TO_FP32(x[i].m) * GGML_FP16_TO_FP32(y[i].s);
+
+        __m256i qx = bytes_from_nibbles_32(x[i].qs);
+        __m256i bxhi = bytes_from_bits_32(x[i].qh);
+        bxhi = __lasx_xvand_v(bxhi, __lasx_xvreplgr2vr_b(0x10));
+        qx = __lasx_xvor_v(qx, bxhi);
+
+        const __m256 dy = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(y[i].d));
+        const __m256i qy = __lasx_xvld((const __m256i *)y[i].qs, 0);
+
+        const __m256 q = mul_sum_us8_pairs_float(qx, qy);
+
+        acc = __lasx_xvfmadd_s(q, __lasx_xvfmul_s(dx, dy), acc);
+    }
+
+    *s = hsum_float_8(acc) + summs;
+
 #else
     // scalar
     float sumf = 0.0;
@@ -4967,6 +5459,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     }
 
     *s = sumf;
+
 #elif defined(__POWER9_VECTOR__)
     vector float vsumf0 = vec_splats(0.0f);
 
@@ -5006,6 +5499,26 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, size_t bs, const void * r
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+    // Initialize accumulator with zeros
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    // Main loop
+    for (int i = 0; i < nb; ++i) {
+        // Compute combined scale for the block
+        const __m256 d = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[i].d) * GGML_FP16_TO_FP32(y[i].d));
+        __m256i qx = __lasx_xvld((const __m256i *)x[i].qs, 0);
+        __m256i qy = __lasx_xvld((const __m256i *)y[i].qs, 0);
+
+        const __m256 q = mul_sum_i8_pairs_float(qx, qy);
+
+        // Multiply q with scale and accumulate
+        acc = __lasx_xvfmadd_s( d, q, acc );
+    }
+
+    *s = hsum_float_8(acc);
+
 #else
     // scalar
     float sumf = 0.0;
@@ -5024,7 +5537,6 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, size_t bs, const void * r
 #endif
 }
 
-#if QK_K == 256
 void ggml_vec_dot_q2_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
     assert(nrc == 1);
     UNUSED(nrc);
@@ -5410,8 +5922,6 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * restrict s, size_t bs, const void * r
         vector signed int vsumi6 = vec_splats((int32_t)0);
         vector signed int vsumi7 = vec_splats((int32_t)0);
 
-        const uint8_t * restrict q2 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
 
         for (int j = 0; j < QK_K/128; ++j) {
             __builtin_prefetch(q2, 0, 1);
@@ -5502,6 +6012,71 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 
     *s = vec_extract(vsumf0, 0);
 
+#elif defined __loongarch_asx
+
+    const __m256i m3 = __lasx_xvreplgr2vr_b(3);
+    const __m128i m4 = __lsx_vreplgr2vr_b(0xF);
+
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    for (int i = 0; i < nb; ++i) {
+
+        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
+        const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
+
+        const uint8_t * restrict q2 = x[i].qs;
+        const int8_t  * restrict q8 = y[i].qs;
+        const __m128i mins_and_scales = __lsx_vld((const __m128i*)x[i].scales, 0);
+        const __m128i scales8 = __lsx_vand_v(mins_and_scales, m4);
+        const __m128i mins8 = __lsx_vand_v(__lsx_vsrli_h(mins_and_scales, 4), m4);
+        const __m256i mins = lasx_ext8_16(mins8);
+        const __m256i prod = lasx_madd_h(mins, __lasx_xvld((const __m256i*)y[i].bsums, 0));
+
+        acc = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(dmin), __lasx_xvffint_s_w(prod), acc);
+
+        const __m256i all_scales = lasx_ext8_16(scales8);
+        const __m128i l_scales = lasx_extracti128(all_scales, 0);
+        const __m128i h_scales = lasx_extracti128(all_scales, 1);
+        const __m256i scales[2] = {lasx_insertf128(l_scales, l_scales), lasx_insertf128(h_scales, h_scales)};
+
+        __m256i sumi = __lasx_xvldi(0);
+
+        for (int j = 0; j < QK_K/128; ++j) {
+
+            const __m256i q2bits = __lasx_xvld((const __m256i*)q2, 0); q2 += 32;
+
+            const __m256i q8_0 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_1 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_3 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+
+            const __m256i q2_0 = __lasx_xvand_v(q2bits, m3);
+            const __m256i q2_1 = __lasx_xvand_v(__lasx_xvsrli_h(q2bits, 2), m3);
+            const __m256i q2_2 = __lasx_xvand_v(__lasx_xvsrli_h(q2bits, 4), m3);
+            const __m256i q2_3 = __lasx_xvand_v(__lasx_xvsrli_h(q2bits, 6), m3);
+
+            __m256i p0 = lasx_maddubs_h(q2_0, q8_0);
+            __m256i p1 = lasx_maddubs_h(q2_1, q8_1);
+            __m256i p2 = lasx_maddubs_h(q2_2, q8_2);
+            __m256i p3 = lasx_maddubs_h(q2_3, q8_3);
+
+            p0 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(0)), p0);
+            p1 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(1)), p1);
+            p2 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(2)), p2);
+            p3 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(3)), p3);
+
+            p0 = __lasx_xvadd_w(p0, p1);
+            p2 = __lasx_xvadd_w(p2, p3);
+
+            sumi = __lasx_xvadd_w(sumi, __lasx_xvadd_w(p0, p2));
+        }
+
+        acc = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(sumi), acc);
+
+    }
+
+    *s = hsum_float_8(acc);
+
 #else
 
     float sumf = 0;
@@ -5545,352 +6120,6 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 #endif
 }
 
-#else
-
-void ggml_vec_dot_q2_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
-    assert(nrc == 1);
-    UNUSED(nrc);
-    UNUSED(bx);
-    UNUSED(by);
-    UNUSED(bs);
-
-    const block_q2_K * restrict x = vx;
-    const block_q8_K * restrict y = vy;
-
-    const int nb = n / QK_K;
-
-#ifdef __ARM_NEON
-    const uint8x16_t m3 = vdupq_n_u8(0x3);
-
-    const int32x4_t vzero = vdupq_n_s32(0);
-
-    ggml_int8x16x4_t q2bytes;
-
-    uint32_t aux32[2];
-    const uint8_t * scales = (const uint8_t *)aux32;
-
-    float sum = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d    =  y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
-
-        const uint8_t * restrict q2 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-        const uint32_t * restrict sc = (const uint32_t *)x[i].scales;
-
-        aux32[0] = sc[0] & 0x0f0f0f0f;
-        aux32[1] = (sc[0] >> 4) & 0x0f0f0f0f;
-
-        sum += dmin * (scales[4] * y[i].bsums[0] + scales[5] * y[i].bsums[1] + scales[6] * y[i].bsums[2] + scales[7] * y[i].bsums[3]);
-
-        int isum1 = 0, isum2 = 0;
-
-        const uint8x16_t q2bits = vld1q_u8(q2);
-
-        const ggml_int8x16x4_t q8bytes = ggml_vld1q_s8_x4(q8);
-
-        q2bytes.val[0] = vreinterpretq_s8_u8(vandq_u8(q2bits, m3));
-        q2bytes.val[1] = vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q2bits, 2), m3));
-        q2bytes.val[2] = vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q2bits, 4), m3));
-        q2bytes.val[3] = vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q2bits, 6), m3));
-
-        isum1 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[0], q8bytes.val[0])) * scales[0];
-        isum2 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[1], q8bytes.val[1])) * scales[1];
-        isum1 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[2], q8bytes.val[2])) * scales[2];
-        isum2 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[3], q8bytes.val[3])) * scales[3];
-
-        sum += d * (isum1 + isum2);
-    }
-
-    *s = sum;
-
-#elif defined __AVX2__
-
-    const __m256i m3 = _mm256_set1_epi8(3);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    uint32_t ud, um;
-    const uint8_t * restrict db = (const uint8_t *)&ud;
-    const uint8_t * restrict mb = (const uint8_t *)&um;
-
-    float summs = 0;
-
-    // TODO: optimize this
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
-
-        const uint8_t * restrict q2 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const uint32_t * restrict sc = (const uint32_t *)x[i].scales;
-        ud = (sc[0] >> 0) & 0x0f0f0f0f;
-        um = (sc[0] >> 4) & 0x0f0f0f0f;
-
-        int32_t smin = mb[0] * y[i].bsums[0] + mb[1] * y[i].bsums[1] + mb[2] * y[i].bsums[2] + mb[3] * y[i].bsums[3];
-        summs += dmin * smin;
-
-        const __m128i q2bits = _mm_loadu_si128((const __m128i*)q2);
-        const __m256i q2_0 = _mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q2bits, 2), q2bits), m3);
-        const __m256i q2_1 = _mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q2bits, 6), _mm_srli_epi16(q2bits, 4)), m3);
-
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        const __m256i p0 = _mm256_maddubs_epi16(q2_0, q8_0);
-        const __m256i p1 = _mm256_maddubs_epi16(q2_1, q8_1);
-
-        const __m256i p_0 = _mm256_cvtepi16_epi32(_mm256_extracti128_si256(p0, 0));
-        const __m256i p_1 = _mm256_cvtepi16_epi32(_mm256_extracti128_si256(p0, 1));
-        const __m256i p_2 = _mm256_cvtepi16_epi32(_mm256_extracti128_si256(p1, 0));
-        const __m256i p_3 = _mm256_cvtepi16_epi32(_mm256_extracti128_si256(p1, 1));
-
-        acc = _mm256_fmadd_ps(_mm256_set1_ps(d * db[0]), _mm256_cvtepi32_ps(p_0), acc);
-        acc = _mm256_fmadd_ps(_mm256_set1_ps(d * db[1]), _mm256_cvtepi32_ps(p_1), acc);
-        acc = _mm256_fmadd_ps(_mm256_set1_ps(d * db[2]), _mm256_cvtepi32_ps(p_2), acc);
-        acc = _mm256_fmadd_ps(_mm256_set1_ps(d * db[3]), _mm256_cvtepi32_ps(p_3), acc);
-    }
-
-    *s = hsum_float_8(acc) + summs;
-
-#elif defined __AVX__
-
-    const __m128i m3 = _mm_set1_epi8(3);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    uint32_t ud, um;
-    const uint8_t * restrict db = (const uint8_t *)&ud;
-    const uint8_t * restrict mb = (const uint8_t *)&um;
-
-    float summs = 0;
-
-    // TODO: optimize this
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
-
-        const uint8_t * restrict q2 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const uint32_t * restrict sc = (const uint32_t *)x[i].scales;
-        ud = (sc[0] >> 0) & 0x0f0f0f0f;
-        um = (sc[0] >> 4) & 0x0f0f0f0f;
-
-        int32_t smin = mb[0] * y[i].bsums[0] + mb[1] * y[i].bsums[1] + mb[2] * y[i].bsums[2] + mb[3] * y[i].bsums[3];
-        summs += dmin * smin;
-
-        const __m128i q2bits = _mm_loadu_si128((const __m128i*)q2);
-        const __m128i q2_0 = _mm_and_si128(q2bits, m3);
-        const __m128i q2_1 = _mm_and_si128(_mm_srli_epi16(q2bits, 2), m3);
-        const __m128i q2_2 = _mm_and_si128(_mm_srli_epi16(q2bits, 4), m3);
-        const __m128i q2_3 = _mm_and_si128(_mm_srli_epi16(q2bits, 6), m3);
-
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        const __m128i p0 = _mm_maddubs_epi16(q2_0, _mm256_extractf128_si256(q8_0, 0));
-        const __m128i p1 = _mm_maddubs_epi16(q2_1, _mm256_extractf128_si256(q8_0, 1));
-        const __m128i p2 = _mm_maddubs_epi16(q2_2, _mm256_extractf128_si256(q8_1, 0));
-        const __m128i p3 = _mm_maddubs_epi16(q2_3, _mm256_extractf128_si256(q8_1, 1));
-
-        const __m256i p_0 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p0, p0)), _mm_cvtepi16_epi32(p0));
-        const __m256i p_1 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p1, p1)), _mm_cvtepi16_epi32(p1));
-        const __m256i p_2 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p2, p2)), _mm_cvtepi16_epi32(p2));
-        const __m256i p_3 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p3, p3)), _mm_cvtepi16_epi32(p3));
-
-        acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[0]), _mm256_cvtepi32_ps(p_0)), acc);
-        acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[1]), _mm256_cvtepi32_ps(p_1)), acc);
-        acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[2]), _mm256_cvtepi32_ps(p_2)), acc);
-        acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[3]), _mm256_cvtepi32_ps(p_3)), acc);
-    }
-
-    *s = hsum_float_8(acc) + summs;
-
-#elif defined __riscv_v_intrinsic
-
-    uint32_t aux32[2];
-    const uint8_t * scales = (const uint8_t *)aux32;
-
-    float sumf = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d    =  y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
-
-        const uint8_t * restrict q2 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-        const uint32_t * restrict sc = (const uint32_t *)x[i].scales;
-
-        aux32[0] = sc[0] & 0x0f0f0f0f;
-        aux32[1] = (sc[0] >> 4) & 0x0f0f0f0f;
-
-        sumf += dmin * (scales[4] * y[i].bsums[0] + scales[5] * y[i].bsums[1] + scales[6] * y[i].bsums[2] + scales[7] * y[i].bsums[3]);
-
-        int isum1 = 0;
-        int isum2 = 0;
-
-        size_t vl = 16;
-
-        vint16m1_t vzero = __riscv_vmv_v_x_i16m1(0, 1);
-
-        // load Q2
-        vuint8mf2_t q2_x = __riscv_vle8_v_u8mf2(q2, vl);
-
-        vint8mf2_t q2_0 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vand_vx_u8mf2(q2_x, 0x03, vl));
-        vint8mf2_t q2_1 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vand_vx_u8mf2(__riscv_vsrl_vx_u8mf2(q2_x, 0x2, vl), 0x03 , vl));
-        vint8mf2_t q2_2 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vand_vx_u8mf2(__riscv_vsrl_vx_u8mf2(q2_x, 0x4, vl), 0x03 , vl));
-        vint8mf2_t q2_3 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vand_vx_u8mf2(__riscv_vsrl_vx_u8mf2(q2_x, 0x6, vl), 0x03 , vl));
-
-        // load Q8, and take product with Q2
-        vint16m1_t p0 = __riscv_vwmul_vv_i16m1(q2_0, __riscv_vle8_v_i8mf2(q8, vl), vl);
-        vint16m1_t p1 = __riscv_vwmul_vv_i16m1(q2_1, __riscv_vle8_v_i8mf2(q8+16, vl), vl);
-        vint16m1_t p2 = __riscv_vwmul_vv_i16m1(q2_2, __riscv_vle8_v_i8mf2(q8+32, vl), vl);
-        vint16m1_t p3 = __riscv_vwmul_vv_i16m1(q2_3, __riscv_vle8_v_i8mf2(q8+48, vl), vl);
-
-        vint16m1_t vs_0 = __riscv_vredsum_vs_i16m1_i16m1(p0, vzero, vl);
-        vint16m1_t vs_1 = __riscv_vredsum_vs_i16m1_i16m1(p1, vzero, vl);
-        vint16m1_t vs_2 = __riscv_vredsum_vs_i16m1_i16m1(p2, vzero, vl);
-        vint16m1_t vs_3 = __riscv_vredsum_vs_i16m1_i16m1(p3, vzero, vl);
-
-        isum1 += __riscv_vmv_x_s_i16m1_i16(vs_0) * scales[0];
-        isum2 += __riscv_vmv_x_s_i16m1_i16(vs_1) * scales[1];
-        isum1 += __riscv_vmv_x_s_i16m1_i16(vs_2) * scales[2];
-        isum2 += __riscv_vmv_x_s_i16m1_i16(vs_3) * scales[3];
-
-        sumf += d * (isum1 + isum2);
-
-    }
-
-    *s = sumf;
-
-#elif defined(__POWER9_VECTOR__)
-    const vector signed char lowMask = vec_splats((signed char)0x3);
-    const vector signed char lowScaleMask = vec_splats((signed char)0xF);
-    const vector unsigned char v2 = vec_splats((unsigned char)0x2);
-    const vector unsigned char v4 = vec_splats((unsigned char)0x4);
-    const vector unsigned char v6 = vec_splats((unsigned char)0x6);
-
-    vector float vsumf0 = vec_splats(0.0f);
-    vector float vsumf1 = vec_splats(0.0f);
-    vector float vsumf2 = vec_splats(0.0f);
-    vector float vsumf3 = vec_splats(0.0f);
-
-#pragma GCC unroll 2
-    for (int i = 0; i < nb; ++i) {
-        __builtin_prefetch(x[i].qs, 0, 1);
-        __builtin_prefetch(y[i].qs, 0, 1);
-
-        vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
-        vector float vyd = vec_splats(y[i].d);
-        vector float vd = vec_mul(vxd, vyd);
-
-        vector float vxmin = vec_splats(GGML_FP16_TO_FP32(x[i].dmin));
-        vector float vdmin = vec_mul(vxmin, vyd);
-
-        vector signed short q8ysums0 = vec_xl_len(y[i].bsums, 8);
-
-        vector signed char q2xmins = (vector signed char)vec_xl_len(x[i].scales, 4);
-        vector signed char vscales = vec_and(q2xmins, lowScaleMask);
-
-        q2xmins = vec_sr(q2xmins, v4);
-        vector signed short q2xmins0 = vec_unpackh((vector signed char)q2xmins);
-
-        vector signed int prod0 = vec_mule(q2xmins0, q8ysums0);
-        vector signed int prod1 = vec_mulo(q2xmins0, q8ysums0);
-
-        vsumf0 = vec_nmsub(vec_ctf(prod0, 0), vdmin, vsumf0);
-        vsumf1 = vec_nmsub(vec_ctf(prod1, 0), vdmin, vsumf1);
-
-        vector signed char qxs0 = (vector signed char)vec_xl( 0, x[i].qs);
-        vector signed char q2x00 = vec_and(qxs0, lowMask);
-        vector signed char q2x01 = vec_and(vec_sr(qxs0, v2), lowMask);
-        vector signed char q2x02 = vec_and(vec_sr(qxs0, v4), lowMask);
-        vector signed char q2x03 = vec_and(vec_sr(qxs0, v6), lowMask);
-
-        vector signed char q8y00 = vec_xl(  0, y[i].qs);
-        vector signed char q8y01 = vec_xl( 16, y[i].qs);
-        vector signed char q8y02 = vec_xl( 32, y[i].qs);
-        vector signed char q8y03 = vec_xl( 48, y[i].qs);
-
-        vector signed short qv0 = vec_add(vec_mule(q2x00, q8y00), vec_mulo(q2x00, q8y00));
-        vector signed short qv1 = vec_add(vec_mule(q2x01, q8y01), vec_mulo(q2x01, q8y01));
-        vector signed short qv2 = vec_add(vec_mule(q2x02, q8y02), vec_mulo(q2x02, q8y02));
-        vector signed short qv3 = vec_add(vec_mule(q2x03, q8y03), vec_mulo(q2x03, q8y03));
-
-        vector signed short vscales_h = vec_unpackh(vscales);
-        vector signed short vs0 = vec_splat(vscales_h, 0);
-        vector signed short vs1 = vec_splat(vscales_h, 1);
-        vector signed short vs2 = vec_splat(vscales_h, 2);
-        vector signed short vs3 = vec_splat(vscales_h, 3);
-
-        vector signed int vsumi0 = vec_add(vec_mule(qv0, vs0), vec_mulo(qv0, vs0));
-        vector signed int vsumi1 = vec_add(vec_mule(qv1, vs1), vec_mulo(qv1, vs1));
-        vector signed int vsumi2 = vec_add(vec_mule(qv2, vs2), vec_mulo(qv2, vs2));
-        vector signed int vsumi3 = vec_add(vec_mule(qv3, vs3), vec_mulo(qv3, vs3));
-
-        vsumf0 = vec_madd(vec_ctf(vsumi0, 0), vd, vsumf0);
-        vsumf1 = vec_madd(vec_ctf(vsumi1, 0), vd, vsumf1);
-        vsumf2 = vec_madd(vec_ctf(vsumi2, 0), vd, vsumf2);
-        vsumf3 = vec_madd(vec_ctf(vsumi3, 0), vd, vsumf3);
-    }
-
-    vsumf0 = vec_add(vsumf0, vsumf2);
-    vsumf1 = vec_add(vsumf1, vsumf3);
-
-    vsumf0 = vec_add(vsumf0, vsumf1);
-
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 4));
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
-
-    *s = vec_extract(vsumf0, 0);
-
-#else
-
-    float sumf = 0;
-
-    int isum[QK_K/16];
-
-    for (int i = 0; i < nb; ++i) {
-
-        const uint8_t * q2 = x[i].qs;
-        const  int8_t * q8 = y[i].qs;
-        const uint8_t * sc = x[i].scales;
-
-        int summs = 0;
-        for (int j = 0; j < QK_K/16; ++j) {
-            summs += y[i].bsums[j] * (sc[j] >> 4);
-        }
-
-        const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
-
-        memset(isum, 0, (QK_K/16)*sizeof(int));
-        for (int l =  0; l < 16; ++l) {
-            isum[0] += q8[l+ 0] * ((q2[l] >> 0) & 3);
-            isum[1] += q8[l+16] * ((q2[l] >> 2) & 3);
-            isum[2] += q8[l+32] * ((q2[l] >> 4) & 3);
-            isum[3] += q8[l+48] * ((q2[l] >> 6) & 3);
-        }
-        for (int l = 0; l < QK_K/16; ++l) {
-            isum[l] *= (sc[l] & 0xF);
-        }
-        sumf += dall * (isum[0] + isum[1] + isum[2] + isum[3]) - dmin * summs;
-    }
-    *s = sumf;
-#endif
-}
-#endif
-
-#if QK_K == 256
 void ggml_vec_dot_q3_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
     assert(n % QK_K == 0);
     assert(nrc == 1);
@@ -6390,6 +6619,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * restrict s, size_t bs, const void * r
         vector signed int vsumi6 = vec_splats((int32_t)0);
         vector signed int vsumi7 = vec_splats((int32_t)0);
 
+
         const uint8_t * restrict q3 = x[i].qs;
         const int8_t  * restrict q8 = y[i].qs;
 
@@ -6501,6 +6731,107 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * restrict s, size_t bs, const void * r
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined __loongarch_asx
+
+    const __m256i m3 = __lasx_xvreplgr2vr_b(3);
+    const __m256i mone = __lasx_xvreplgr2vr_b(1);
+    const __m128i m32 = __lsx_vreplgr2vr_b(32);
+
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    uint32_t aux[3];
+
+    for (int i = 0; i < nb; ++i) {
+
+        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
+        // Set up scales
+        memcpy(aux, x[i].scales, 12);
+        __m128i scales128 = lsx_set_w(
+                ((aux[1] >> 4) & kmask2) | (((aux[2] >> 6) & kmask1) << 4),
+                ((aux[0] >> 4) & kmask2) | (((aux[2] >> 4) & kmask1) << 4),
+                (aux[1] & kmask2) | (((aux[2] >> 2) & kmask1) << 4),
+                (aux[0] & kmask2) | (((aux[2] >> 0) & kmask1) << 4));
+        scales128 = __lsx_vsub_b(scales128, m32);
+        const __m256i all_scales = lasx_ext8_16(scales128);
+        const __m128i l_scales = lasx_extracti128(all_scales, 0);
+        const __m128i h_scales = lasx_extracti128(all_scales, 1);
+        const __m256i scales[2] = {lasx_insertf128(l_scales, l_scales), lasx_insertf128(h_scales, h_scales)};
+
+        // high bit
+        const __m256i hbits = __lasx_xvld((const __m256i*)x[i].hmask, 0);
+
+        // integer accumulator
+        __m256i sumi = __lasx_xvldi(0);
+
+        int bit = 0;
+        int is  = 0;
+
+        const uint8_t * restrict q3 = x[i].qs;
+        const int8_t  * restrict q8 = y[i].qs;
+
+        for (int j = 0; j < QK_K/128; ++j) {
+            // load low 2 bits
+            const __m256i q3bits = __lasx_xvld((const __m256i*)q3, 0); q3 += 32;
+
+            // prepare low and high bits
+            const __m256i q3l_0 = __lasx_xvand_v(q3bits, m3);
+            const __m256i q3h_0 = __lasx_xvslli_h(__lasx_xvsrli_h(__lasx_xvandn_v(hbits, __lasx_xvslli_h(mone, bit)), bit), 2);
+            ++bit;
+
+            const __m256i q3l_1 = __lasx_xvand_v(__lasx_xvsrli_h(q3bits, 2), m3);
+            const __m256i q3h_1 = __lasx_xvslli_h(__lasx_xvsrli_h(__lasx_xvandn_v(hbits, __lasx_xvslli_h(mone, bit)), bit), 2);
+            ++bit;
+
+            const __m256i q3l_2 = __lasx_xvand_v(__lasx_xvsrli_h(q3bits, 4), m3);
+            const __m256i q3h_2 = __lasx_xvslli_h(__lasx_xvsrli_h(__lasx_xvandn_v(hbits, __lasx_xvslli_h(mone, bit)), bit), 2);
+            ++bit;
+
+            const __m256i q3l_3 = __lasx_xvand_v(__lasx_xvsrli_h(q3bits, 6), m3);
+            const __m256i q3h_3 = __lasx_xvslli_h(__lasx_xvsrli_h(__lasx_xvandn_v(hbits, __lasx_xvslli_h(mone, bit)), bit), 2);
+            ++bit;
+
+            // load Q8 quants
+            const __m256i q8_0 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_1 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_3 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+
+            // Dot product: we multiply the 2 low bits and 1 high bit part separately, so we can use lasx_maddubs_h,
+            // and then subtract. The high bit part has the 2 already subtracted (and so, it is zero if the high bit was not set,
+            // and 2 if the high bit was set)
+            __m256i q8s_0 = lasx_maddubs_h(q3h_0, q8_0);
+            __m256i q8s_1 = lasx_maddubs_h(q3h_1, q8_1);
+            __m256i q8s_2 = lasx_maddubs_h(q3h_2, q8_2);
+            __m256i q8s_3 = lasx_maddubs_h(q3h_3, q8_3);
+
+            __m256i p16_0 = lasx_maddubs_h(q3l_0, q8_0);
+            __m256i p16_1 = lasx_maddubs_h(q3l_1, q8_1);
+            __m256i p16_2 = lasx_maddubs_h(q3l_2, q8_2);
+            __m256i p16_3 = lasx_maddubs_h(q3l_3, q8_3);
+
+            p16_0 = __lasx_xvsub_h(p16_0, q8s_0);
+            p16_1 = __lasx_xvsub_h(p16_1, q8s_1);
+            p16_2 = __lasx_xvsub_h(p16_2, q8s_2);
+            p16_3 = __lasx_xvsub_h(p16_3, q8s_3);
+
+            // multiply with scales
+            p16_0 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(is + 0)), p16_0);
+            p16_1 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(is + 1)), p16_1);
+            p16_2 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(is + 2)), p16_2);
+            p16_3 = lasx_madd_h(lasx_shuffle_b(scales[j], get_scale_shuffle_q3k(is + 3)), p16_3);
+
+            // accumulate
+            p16_0 = __lasx_xvadd_w(p16_0, p16_1);
+            p16_2 = __lasx_xvadd_w(p16_2, p16_3);
+            sumi  = __lasx_xvadd_w(sumi, __lasx_xvadd_w(p16_0, p16_2));
+        }
+        // multiply with block scale and accumulate
+        acc = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(sumi), acc);//FIXME
+    }
+
+    *s = hsum_float_8(acc);
+
 #else
     // scalar version
     // This function is written like this so the compiler can manage to vectorize most of it
@@ -6568,445 +6899,6 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 
 }
 
-#else
-
-void ggml_vec_dot_q3_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
-    assert(n % QK_K == 0);
-    assert(nrc == 1);
-    UNUSED(nrc);
-    UNUSED(bx);
-    UNUSED(by);
-    UNUSED(bs);
-
-    const block_q3_K * restrict x = vx;
-    const block_q8_K * restrict y = vy;
-
-    const int nb = n / QK_K;
-
-#ifdef __ARM_NEON
-    const int32x4_t vzero = vdupq_n_s32(0);
-
-    const uint8x16_t m3b = vdupq_n_u8(0x3);
-    const uint8x16_t mh  = vdupq_n_u8(4);
-
-    ggml_int8x16x4_t q3bytes;
-
-    uint16_t aux16[2];
-    int8_t * scales = (int8_t *)aux16;
-
-    float sum = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        ggml_uint8x16x4_t q3h;
-
-        const uint8x8_t  hbits    = vld1_u8(x[i].hmask);
-        const uint8x16_t q3bits   = vld1q_u8(x[i].qs);
-        const ggml_int8x16x4_t q8bytes = ggml_vld1q_s8_x4(y[i].qs);
-
-        const uint16_t a = *(const uint16_t *)x[i].scales;
-        aux16[0] = a & 0x0f0f;
-        aux16[1] = (a >> 4) & 0x0f0f;
-
-        for (int j = 0; j < 4; ++j) scales[j] -= 8;
-
-        int32_t isum = -4*(scales[0] * y[i].bsums[0] + scales[2] * y[i].bsums[1] + scales[1] * y[i].bsums[2] + scales[3] * y[i].bsums[3]);
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8x16_t htmp = vcombine_u8(hbits, vshr_n_u8(hbits, 1));
-        q3h.val[0] = vandq_u8(mh, vshlq_n_u8(htmp, 2));
-        q3h.val[1] = vandq_u8(mh, htmp);
-        q3h.val[2] = vandq_u8(mh, vshrq_n_u8(htmp, 2));
-        q3h.val[3] = vandq_u8(mh, vshrq_n_u8(htmp, 4));
-
-        q3bytes.val[0] = vreinterpretq_s8_u8(vorrq_u8(vandq_u8(q3bits, m3b),                q3h.val[0]));
-        q3bytes.val[1] = vreinterpretq_s8_u8(vorrq_u8(vandq_u8(vshrq_n_u8(q3bits, 2), m3b), q3h.val[1]));
-        q3bytes.val[2] = vreinterpretq_s8_u8(vorrq_u8(vandq_u8(vshrq_n_u8(q3bits, 4), m3b), q3h.val[2]));
-        q3bytes.val[3] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q3bits, 6),                q3h.val[3]));
-
-        isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[0], q8bytes.val[0])) * scales[0];
-        isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[1], q8bytes.val[1])) * scales[2];
-        isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[2], q8bytes.val[2])) * scales[1];
-        isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[3], q8bytes.val[3])) * scales[3];
-
-        sum += d * isum;
-
-    }
-
-    *s = sum;
-
-#elif defined __AVX2__
-
-    const __m256i m3 = _mm256_set1_epi8(3);
-    const __m256i m1 = _mm256_set1_epi8(1);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    uint64_t aux64;
-
-    uint16_t aux16[2];
-    const int8_t * aux8 = (const int8_t *)aux16;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8_t * restrict q3 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const uint16_t a = *(const uint16_t *)x[i].scales;
-        aux16[0] = a & 0x0f0f;
-        aux16[1] = (a >> 4) & 0x0f0f;
-
-        const __m256i scale_0 = MM256_SET_M128I(_mm_set1_epi16(aux8[2] - 8), _mm_set1_epi16(aux8[0] - 8));
-        const __m256i scale_1 = MM256_SET_M128I(_mm_set1_epi16(aux8[3] - 8), _mm_set1_epi16(aux8[1] - 8));
-
-        memcpy(&aux64, x[i].hmask, 8);
-
-        const __m128i haux = _mm_set_epi64x(aux64 >> 1, aux64 >> 0);
-        __m256i q3h_0 = MM256_SET_M128I(_mm_srli_epi16(haux, 2), haux);
-        __m256i q3h_1 = _mm256_srli_epi16(q3h_0, 4);
-        q3h_0 = _mm256_slli_epi16(_mm256_andnot_si256(q3h_0, m1), 2);
-        q3h_1 = _mm256_slli_epi16(_mm256_andnot_si256(q3h_1, m1), 2);
-
-        // load low 2 bits
-        const __m128i q3bits = _mm_loadu_si128((const __m128i*)q3);
-
-        // prepare low and high bits
-        const __m256i q3aux  = MM256_SET_M128I(_mm_srli_epi16(q3bits, 2), q3bits);
-        const __m256i q3l_0 = _mm256_and_si256(q3aux, m3);
-        const __m256i q3l_1 = _mm256_and_si256(_mm256_srli_epi16(q3aux, 4), m3);
-
-        // load Q8 quants
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        // Dot product: we multiply the 2 low bits and 1 high bit part separately, so we can use _mm256_maddubs_epi16,
-        // and then subtract. The high bit part has the 2 already subtracted (and so, it is zero if the high bit was not set,
-        // and 2 if the high bit was set)
-        const __m256i q8s_0 = _mm256_maddubs_epi16(q3h_0, q8_0);
-        const __m256i q8s_1 = _mm256_maddubs_epi16(q3h_1, q8_1);
-
-        __m256i p16_0 = _mm256_maddubs_epi16(q3l_0, q8_0);
-        __m256i p16_1 = _mm256_maddubs_epi16(q3l_1, q8_1);
-
-        p16_0 = _mm256_sub_epi16(p16_0, q8s_0);
-        p16_1 = _mm256_sub_epi16(p16_1, q8s_1);
-
-        // multiply with scales
-        p16_0 = _mm256_madd_epi16(scale_0, p16_0);
-        p16_1 = _mm256_madd_epi16(scale_1, p16_1);
-
-        p16_0 = _mm256_add_epi32(p16_0, p16_1);
-
-        // multiply with block scale and accumulate
-        acc = _mm256_fmadd_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(p16_0), acc);
-
-    }
-
-    *s = hsum_float_8(acc);
-
-#elif defined __AVX__
-
-    const __m128i m3 = _mm_set1_epi8(3);
-    const __m128i m1 = _mm_set1_epi8(1);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    uint64_t aux64;
-
-    uint16_t aux16[2];
-    const int8_t * aux8 = (const int8_t *)aux16;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8_t * restrict q3 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const uint16_t a = *(const uint16_t *)x[i].scales;
-        aux16[0] = a & 0x0f0f;
-        aux16[1] = (a >> 4) & 0x0f0f;
-
-        const __m128i scale_0 = _mm_set1_epi16(aux8[0] - 8);
-        const __m128i scale_1 = _mm_set1_epi16(aux8[2] - 8);
-        const __m128i scale_2 = _mm_set1_epi16(aux8[1] - 8);
-        const __m128i scale_3 = _mm_set1_epi16(aux8[3] - 8);
-
-        memcpy(&aux64, x[i].hmask, 8);
-
-        __m128i q3h_0 = _mm_set_epi64x(aux64 >> 1, aux64 >> 0);
-        __m128i q3h_1 = _mm_srli_epi16(q3h_0, 2);
-        __m128i q3h_2 = _mm_srli_epi16(q3h_0, 4);
-        __m128i q3h_3 = _mm_srli_epi16(q3h_0, 6);
-        q3h_0 = _mm_slli_epi16(_mm_andnot_si128(q3h_0, m1), 2);
-        q3h_1 = _mm_slli_epi16(_mm_andnot_si128(q3h_1, m1), 2);
-        q3h_2 = _mm_slli_epi16(_mm_andnot_si128(q3h_2, m1), 2);
-        q3h_3 = _mm_slli_epi16(_mm_andnot_si128(q3h_3, m1), 2);
-
-        // load low 2 bits
-        const __m128i q3bits = _mm_loadu_si128((const __m128i*)q3);
-
-        // prepare low and high bits
-        const __m128i q3l_0 = _mm_and_si128(q3bits, m3);
-        const __m128i q3l_1 = _mm_and_si128(_mm_srli_epi16(q3bits, 2), m3);
-        const __m128i q3l_2 = _mm_and_si128(_mm_srli_epi16(q3bits, 4), m3);
-        const __m128i q3l_3 = _mm_and_si128(_mm_srli_epi16(q3bits, 6), m3);
-
-        // load Q8 quants
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        // Dot product: we multiply the 2 low bits and 1 high bit part separately, so we can use _mm_maddubs_epi16,
-        // and then subtract. The high bit part has the 2 already subtracted (and so, it is zero if the high bit was not set,
-        // and 2 if the high bit was set)
-        const __m128i q8s_0 = _mm_maddubs_epi16(q3h_0, _mm256_extractf128_si256(q8_0, 0));
-        const __m128i q8s_1 = _mm_maddubs_epi16(q3h_1, _mm256_extractf128_si256(q8_0, 1));
-        const __m128i q8s_2 = _mm_maddubs_epi16(q3h_2, _mm256_extractf128_si256(q8_1, 0));
-        const __m128i q8s_3 = _mm_maddubs_epi16(q3h_3, _mm256_extractf128_si256(q8_1, 1));
-
-        __m128i p16_0 = _mm_maddubs_epi16(q3l_0, _mm256_extractf128_si256(q8_0, 0));
-        __m128i p16_1 = _mm_maddubs_epi16(q3l_1, _mm256_extractf128_si256(q8_0, 1));
-        __m128i p16_2 = _mm_maddubs_epi16(q3l_2, _mm256_extractf128_si256(q8_1, 0));
-        __m128i p16_3 = _mm_maddubs_epi16(q3l_3, _mm256_extractf128_si256(q8_1, 1));
-
-        p16_0 = _mm_sub_epi16(p16_0, q8s_0);
-        p16_1 = _mm_sub_epi16(p16_1, q8s_1);
-        p16_2 = _mm_sub_epi16(p16_2, q8s_2);
-        p16_3 = _mm_sub_epi16(p16_3, q8s_3);
-
-        // multiply with scales
-        p16_0 = _mm_madd_epi16(scale_0, p16_0);
-        p16_1 = _mm_madd_epi16(scale_1, p16_1);
-        p16_2 = _mm_madd_epi16(scale_2, p16_2);
-        p16_3 = _mm_madd_epi16(scale_3, p16_3);
-
-        p16_0 = _mm_add_epi32(p16_0, p16_2);
-        p16_1 = _mm_add_epi32(p16_1, p16_3);
-        __m256i p16 = MM256_SET_M128I(p16_1, p16_0);
-
-        // multiply with block scale and accumulate
-        acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(p16)), acc);
-
-    }
-
-    *s = hsum_float_8(acc);
-
-#elif defined __riscv_v_intrinsic
-
-    uint16_t aux16[2];
-    int8_t * scales = (int8_t *)aux16;
-
-    float sumf = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const uint8_t * restrict q3 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const uint16_t a = *(const uint16_t *)x[i].scales;
-        aux16[0] = a & 0x0f0f;
-        aux16[1] = (a >> 4) & 0x0f0f;
-
-        for (int j = 0; j < 4; ++j) scales[j] -= 8;
-
-        int32_t isum = -4*(scales[0] * y[i].bsums[0] + scales[2] * y[i].bsums[1] + scales[1] * y[i].bsums[2] + scales[3] * y[i].bsums[3]);
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        vint32m1_t vzero = __riscv_vmv_v_x_i32m1(0, 1);
-
-        // load qh
-        vuint8mf4_t qh_x1   = __riscv_vle8_v_u8mf4(x[i].hmask, 8);
-        vuint8mf2_t qh_x2   = __riscv_vlmul_ext_v_u8mf4_u8mf2(__riscv_vsrl_vx_u8mf4(qh_x1, 1, 8));
-
-        size_t vl = 16;
-
-        // extend and combine both qh_x1 and qh_x2
-        vuint8mf2_t qh_x = __riscv_vslideup_vx_u8mf2(__riscv_vlmul_ext_v_u8mf4_u8mf2(qh_x1), qh_x2, vl/2, vl);
-
-        vuint8mf2_t qh_0 = __riscv_vand_vx_u8mf2(__riscv_vsll_vx_u8mf2(qh_x, 0x2, vl), 0x4, vl);
-        vuint8mf2_t qh_1 = __riscv_vand_vx_u8mf2(qh_x, 0x4, vl);
-        vuint8mf2_t qh_2 = __riscv_vand_vx_u8mf2(__riscv_vsrl_vx_u8mf2(qh_x, 0x2, vl), 0x4, vl);
-        vuint8mf2_t qh_3 = __riscv_vand_vx_u8mf2(__riscv_vsrl_vx_u8mf2(qh_x, 0x4, vl), 0x4, vl);
-
-        // load Q3
-        vuint8mf2_t q3_x  = __riscv_vle8_v_u8mf2(q3, vl);
-
-        vuint8mf2_t q3h_0 = __riscv_vor_vv_u8mf2(__riscv_vand_vx_u8mf2(q3_x, 0x3, vl), qh_0, vl);
-        vuint8mf2_t q3h_1 = __riscv_vor_vv_u8mf2(__riscv_vand_vx_u8mf2(__riscv_vsrl_vx_u8mf2(q3_x, 2, vl), 0x3, vl), qh_1, vl);
-        vuint8mf2_t q3h_2 = __riscv_vor_vv_u8mf2(__riscv_vand_vx_u8mf2(__riscv_vsrl_vx_u8mf2(q3_x, 4, vl), 0x3, vl), qh_2, vl);
-        vuint8mf2_t q3h_3 = __riscv_vor_vv_u8mf2(__riscv_vsrl_vx_u8mf2(q3_x, 0x6, vl), qh_3, vl);
-
-        vint8mf2_t q3_0 = __riscv_vreinterpret_v_u8mf2_i8mf2(q3h_0);
-        vint8mf2_t q3_1 = __riscv_vreinterpret_v_u8mf2_i8mf2(q3h_1);
-        vint8mf2_t q3_2 = __riscv_vreinterpret_v_u8mf2_i8mf2(q3h_2);
-        vint8mf2_t q3_3 = __riscv_vreinterpret_v_u8mf2_i8mf2(q3h_3);
-
-        // load Q8 and take product with Q3
-        vint16m1_t p0 = __riscv_vwmul_vv_i16m1(q3_0, __riscv_vle8_v_i8mf2(q8, vl), vl);
-        vint16m1_t p1 = __riscv_vwmul_vv_i16m1(q3_1, __riscv_vle8_v_i8mf2(q8+16, vl), vl);
-        vint16m1_t p2 = __riscv_vwmul_vv_i16m1(q3_2, __riscv_vle8_v_i8mf2(q8+32, vl), vl);
-        vint16m1_t p3 = __riscv_vwmul_vv_i16m1(q3_3, __riscv_vle8_v_i8mf2(q8+48, vl), vl);
-
-        vint32m1_t vs_0 = __riscv_vwredsum_vs_i16m1_i32m1(p0, vzero, vl);
-        vint32m1_t vs_1 = __riscv_vwredsum_vs_i16m1_i32m1(p1, vzero, vl);
-        vint32m1_t vs_2 = __riscv_vwredsum_vs_i16m1_i32m1(p2, vzero, vl);
-        vint32m1_t vs_3 = __riscv_vwredsum_vs_i16m1_i32m1(p3, vzero, vl);
-
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_0) * scales[0];
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_1) * scales[2];
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_2) * scales[1];
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_3) * scales[3];
-
-        sumf += d * isum;
-
-    }
-
-    *s = sumf;
-
-#elif defined(__POWER9_VECTOR__)
-    const vector signed char lowMask = vec_splats((signed char)0x3);
-    const vector signed char v1 = vec_splats((signed char)0x1);
-    const vector unsigned char v2 = vec_splats((unsigned char)0x2);
-    const vector unsigned char v4 = vec_splats((unsigned char)0x4);
-    const vector unsigned char v6 = vec_splats((unsigned char)0x6);
-    const vector signed char off = vec_splats((signed char)0x8);
-
-    vector float vsumf0 = vec_splats(0.0f);
-    vector float vsumf1 = vec_splats(0.0f);
-    vector float vsumf2 = vec_splats(0.0f);
-    vector float vsumf3 = vec_splats(0.0f);
-
-#pragma GCC unroll 2
-    for (int i = 0; i < nb; ++i) {
-        __builtin_prefetch(x[i].qs, 0, 1);
-        __builtin_prefetch(y[i].qs, 0, 1);
-
-        vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
-        vector float vyd = vec_splats(y[i].d);
-        vector float vd = vec_mul(vxd, vyd);
-
-        uint16_t aux16[2];
-        int8_t * scales = (int8_t *)aux16;
-
-        const uint16_t a = *(const uint16_t *)x[i].scales;
-        aux16[0] = a & 0x0f0f;
-        aux16[1] = (a >> 4) & 0x0f0f;
-
-        vector signed char vscales = (vector signed char)vec_xl_len(scales, 8);
-        vector signed char qxhs0 = (vector signed char)vec_xl_len(x[i].hmask, 8);
-        qxhs0 = vec_or(qxhs0, vec_sr(vec_sld(qxhs0, qxhs0, 8), (vector unsigned char)v1));
-
-        vscales = vec_sub(vscales, off);
-
-        vector signed char qxs0 = (vector signed char)vec_xl( 0, x[i].qs);
-        vector signed char qxs00 = vec_and(qxs0, lowMask);
-        vector signed char qxs01 = vec_and(vec_sr(qxs0, v2), lowMask);
-        vector signed char qxs10 = vec_and(vec_sr(qxs0, v4), lowMask);
-        vector signed char qxs11 = vec_and(vec_sr(qxs0, v6), lowMask);
-
-        //the 3rd bit
-        vector signed char qxh00 = vec_sl(vec_andc(v1, qxhs0), v2);
-        vector signed char qxh01 = vec_sl(vec_andc(v1, vec_sr(qxhs0, v2)), v2);
-        vector signed char qxh02 = vec_sl(vec_andc(v1, vec_sr(qxhs0, v4)), v2);
-        vector signed char qxh03 = vec_sl(vec_andc(v1, vec_sr(qxhs0, v6)), v2);
-        qxhs0 = vec_sr(qxhs0, v4);
-
-        vector signed char q3x00 = vec_sub(qxs00, qxh00);
-        vector signed char q3x01 = vec_sub(qxs01, qxh01);
-        vector signed char q3x10 = vec_sub(qxs10, qxh02);
-        vector signed char q3x11 = vec_sub(qxs11, qxh03);
-
-        vector signed char q8y00 = vec_xl(  0, y[i].qs);
-        vector signed char q8y01 = vec_xl( 16, y[i].qs);
-        vector signed char q8y10 = vec_xl( 32, y[i].qs);
-        vector signed char q8y11 = vec_xl( 48, y[i].qs);
-
-        vector signed short vscales_h = vec_unpackh(vscales);
-        vector signed short vs0 = vec_splat(vscales_h, 0);
-        vector signed short vs1 = vec_splat(vscales_h, 1);
-        vector signed short vs2 = vec_splat(vscales_h, 2);
-        vector signed short vs3 = vec_splat(vscales_h, 3);
-
-        vector signed short qv00 = vec_add(vec_mule(q3x00, q8y00), vec_mulo(q3x00, q8y00));
-        vector signed short qv10 = vec_add(vec_mule(q3x10, q8y10), vec_mulo(q3x10, q8y10));
-        vector signed short qv01 = vec_add(vec_mule(q3x01, q8y01), vec_mulo(q3x01, q8y01));
-        vector signed short qv11 = vec_add(vec_mule(q3x11, q8y11), vec_mulo(q3x11, q8y11));
-
-        vector signed int vsumi0 = vec_add(vec_mule(qv00, vs0), vec_mulo(qv00, vs0));
-        vector signed int vsumi1 = vec_add(vec_mule(qv10, vs1), vec_mulo(qv10, vs1));
-        vector signed int vsumi2 = vec_add(vec_mule(qv01, vs2), vec_mulo(qv01, vs2));
-        vector signed int vsumi3 = vec_add(vec_mule(qv11, vs3), vec_mulo(qv11, vs3));
-
-        vsumf0 = vec_madd(vec_ctf(vsumi0, 0), vd, vsumf0);
-        vsumf1 = vec_madd(vec_ctf(vsumi1, 0), vd, vsumf1);
-        vsumf2 = vec_madd(vec_ctf(vsumi2, 0), vd, vsumf2);
-        vsumf3 = vec_madd(vec_ctf(vsumi3, 0), vd, vsumf3);
-    }
-
-    vsumf0 = vec_add(vsumf0, vsumf2);
-    vsumf1 = vec_add(vsumf1, vsumf3);
-
-    vsumf0 = vec_add(vsumf0, vsumf1);
-
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 4));
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
-
-    *s = vec_extract(vsumf0, 0);
-#else
-
-    int8_t  aux8[QK_K];
-    int16_t aux16[8];
-    float   sums [8];
-    int32_t aux32[8];
-    int32_t scales[4];
-    memset(sums, 0, 8*sizeof(float));
-
-    float sumf = 0;
-    for (int i = 0; i < nb; ++i) {
-        const uint8_t * restrict q3 = x[i].qs;
-        const uint8_t * restrict hm = x[i].hmask;
-        const  int8_t * restrict q8 = y[i].qs;
-        int8_t * restrict a = aux8;
-        for (int l = 0; l < 8; ++l) {
-            a[l+ 0] = (int8_t)((q3[l+0] >> 0) & 3) - (hm[l] & 0x01 ? 0 : 4);
-            a[l+ 8] = (int8_t)((q3[l+8] >> 0) & 3) - (hm[l] & 0x02 ? 0 : 4);
-            a[l+16] = (int8_t)((q3[l+0] >> 2) & 3) - (hm[l] & 0x04 ? 0 : 4);
-            a[l+24] = (int8_t)((q3[l+8] >> 2) & 3) - (hm[l] & 0x08 ? 0 : 4);
-            a[l+32] = (int8_t)((q3[l+0] >> 4) & 3) - (hm[l] & 0x10 ? 0 : 4);
-            a[l+40] = (int8_t)((q3[l+8] >> 4) & 3) - (hm[l] & 0x20 ? 0 : 4);
-            a[l+48] = (int8_t)((q3[l+0] >> 6) & 3) - (hm[l] & 0x40 ? 0 : 4);
-            a[l+56] = (int8_t)((q3[l+8] >> 6) & 3) - (hm[l] & 0x80 ? 0 : 4);
-        }
-
-        scales[0] = (x[i].scales[0] & 0xF) - 8;
-        scales[1] = (x[i].scales[0] >>  4) - 8;
-        scales[2] = (x[i].scales[1] & 0xF) - 8;
-        scales[3] = (x[i].scales[1] >>  4) - 8;
-
-        memset(aux32, 0, 8*sizeof(int32_t));
-        for (int j = 0; j < QK_K/16; ++j) {
-            for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
-            q8 += 8; a += 8;
-            for (int l = 0; l < 8; ++l) aux16[l] += q8[l] * a[l];
-            q8 += 8; a += 8;
-            for (int l = 0; l < 8; ++l) aux32[l] += scales[j] * aux16[l];
-        }
-        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
-        for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
-    }
-    for (int l = 0; l < 8; ++l) sumf += sums[l];
-    *s = sumf;
-
-#endif
-
-}
-#endif
-
-#if QK_K == 256
 void ggml_vec_dot_q4_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
     assert(n % QK_K == 0);
     assert(nrc == 1);
@@ -7444,8 +7336,69 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 
     *s = vec_extract(vsumf0, 0);
 
-#else
+#elif defined __loongarch_asx
 
+    const __m256i m4 = __lasx_xvreplgr2vr_b(0xF);
+
+    __m256 acc = (__m256)__lasx_xvldi(0);
+    __m128 acc_m = (__m128)__lsx_vldi(0);
+
+   for (int i = 0; i < nb; ++i) {
+
+        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
+        const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
+
+        memcpy(utmp, x[i].scales, 12);
+
+        const uint8_t * restrict q4 = x[i].qs;
+        const int8_t  * restrict q8 = y[i].qs;
+
+        const __m256i mins_and_scales = lasx_extu8_16(lsx_set_w(utmp[3], utmp[2], utmp[1], utmp[0]));
+
+        const __m256i q8sums = __lasx_xvld((const __m256i*)y[i].bsums, 0);
+        const __m128i q8s = lsx_hadd_h(lasx_extracti128(q8sums, 0), lasx_extracti128(q8sums, 1));
+        const __m128i prod = lsx_madd_h(lasx_extracti128(mins_and_scales, 1), q8s);
+        acc_m = __lsx_vfmadd_s(__lsx_vreplfr2vr_s(dmin), __lsx_vffint_s_w(prod), acc_m);
+
+        const __m128i sc128  = lasx_extracti128(mins_and_scales, 0);
+        const __m256i scales = lasx_insertf128(sc128, sc128);
+
+        __m256i sumi = __lasx_xvldi(0);
+
+        for (int j = 0; j < QK_K/64; ++j) {
+
+            const __m256i scale_l = lasx_shuffle_b(scales, get_scale_shuffle_k4(2*j+0));
+            const __m256i scale_h = lasx_shuffle_b(scales, get_scale_shuffle_k4(2*j+1));
+
+            const __m256i q4bits = __lasx_xvld((const __m256i*)q4, 0); q4 += 32;
+            const __m256i q4l = __lasx_xvand_v(q4bits, m4);
+            const __m256i q4h = __lasx_xvand_v(__lasx_xvsrli_h(q4bits, 4), m4);
+
+            const __m256i q8l = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            __m256i p16l = lasx_maddubs_h(q4l, q8l);
+            p16l = lasx_madd_h(scale_l, p16l);
+
+            const __m256i q8h = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            __m256i p16h = lasx_maddubs_h(q4h, q8h);
+            p16h = lasx_madd_h(scale_h, p16h);
+            const __m256i sumj = __lasx_xvadd_w(p16l, p16h);
+
+            sumi = __lasx_xvadd_w(sumi, sumj);
+        }
+
+        __m256 vd = __lasx_xvreplfr2vr_s(d);
+        acc = __lasx_xvfmadd_s(vd, __lasx_xvffint_s_w(sumi), acc);
+    }
+
+    acc_m = __lsx_vfadd_s(acc_m, (__m128)__lsx_vpermi_w((__m128i)acc_m, (__m128i)acc_m, 0xee));
+    __m128i tmp1 = __lsx_vinsgr2vr_w(__lsx_vldi(0), __lsx_vpickve2gr_w((__m128i)acc_m, 1), 0);
+    acc_m = __lsx_vfadd_s(acc_m, (__m128)tmp1);
+
+    ft_union fi;
+    fi.i = __lsx_vpickve2gr_w(acc_m, 0);
+    *s = hsum_float_8(acc) + fi.f ;
+
+#else
 
     const uint8_t * scales = (const uint8_t*)&utmp[0];
     const uint8_t * mins   = (const uint8_t*)&utmp[2];
@@ -7503,336 +7456,7 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * restrict s, size_t bs, const void * r
     *s = sumf;
 #endif
 }
-#else
-void ggml_vec_dot_q4_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
-    assert(n % QK_K == 0);
-    assert(nrc == 1);
-    UNUSED(nrc);
-    UNUSED(bx);
-    UNUSED(by);
-    UNUSED(bs);
 
-    const block_q4_K * restrict x = vx;
-    const block_q8_K * restrict y = vy;
-
-    const int nb = n / QK_K;
-
-#ifdef __ARM_NEON
-    const uint8x16_t m4b = vdupq_n_u8(0xf);
-
-    const int32x4_t mzero = vdupq_n_s32(0);
-
-    float sumf = 0;
-
-    ggml_int8x16x2_t q4bytes;
-    ggml_int8x16x4_t q8bytes;
-
-    float sum_mins = 0.f;
-
-    uint16_t aux16[2];
-    const uint8_t * restrict scales = (const uint8_t *)aux16;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const uint8_t * restrict q4 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const uint16_t * restrict a = (const uint16_t *)x[i].scales;
-        aux16[0] = a[0] & 0x0f0f;
-        aux16[1] = (a[0] >> 4) & 0x0f0f;
-
-        const int32_t summi = scales[2] * (y[i].bsums[0] + y[i].bsums[1]) + scales[3] * (y[i].bsums[2] + y[i].bsums[3]);
-        sum_mins += y[i].d * GGML_FP16_TO_FP32(x[i].d[1]) * summi;
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d[0]);
-
-        const ggml_uint8x16x2_t q4bits = ggml_vld1q_u8_x2(q4);
-
-        q8bytes = ggml_vld1q_s8_x4(q8);
-        q4bytes.val[0] = vreinterpretq_s8_u8(vandq_u8  (q4bits.val[0], m4b));
-        q4bytes.val[1] = vreinterpretq_s8_u8(vandq_u8  (q4bits.val[1], m4b));
-
-        const int32x4_t p1 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[0]), q4bytes.val[1], q8bytes.val[1]);
-        const int32_t sumi1 = vaddvq_s32(p1) * scales[0];
-
-        q4bytes.val[0] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[0], 4));
-        q4bytes.val[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[1], 4));
-
-        const int32x4_t p2 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[2]), q4bytes.val[1], q8bytes.val[3]);
-        const int32_t sumi2 = vaddvq_s32(p2) * scales[1];
-
-        sumf += d * (sumi1 + sumi2);
-    }
-
-    *s = sumf - sum_mins;
-
-#elif defined __AVX2__
-
-    const __m256i m4 = _mm256_set1_epi8(0xF);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    float summs = 0;
-
-    uint16_t aux16[2];
-    const uint8_t * scales = (const uint8_t *)aux16;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = GGML_FP16_TO_FP32(x[i].d[0]) * y[i].d;
-        const float m = GGML_FP16_TO_FP32(x[i].d[1]) * y[i].d;
-        const __m256 vd = _mm256_set1_ps(d);
-
-        const uint16_t * a = (const uint16_t *)x[i].scales;
-        aux16[0] = a[0] & 0x0f0f;
-        aux16[1] = (a[0] >> 4) & 0x0f0f;
-
-        summs += m * (scales[2] * (y[i].bsums[0] + y[i].bsums[1]) + scales[3] * (y[i].bsums[2] + y[i].bsums[3]));
-
-        const uint8_t * restrict q4 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const __m256i q4bits = _mm256_loadu_si256((const __m256i*)q4);
-        const __m256i q4l = _mm256_and_si256(q4bits, m4);
-        const __m256i q4h = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), m4);
-
-        const __m256i q8l = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8h = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        const __m256i p16l = _mm256_maddubs_epi16(q4l, q8l);
-        const __m256i p16h = _mm256_maddubs_epi16(q4h, q8h);
-
-        const __m256i p32l = _mm256_madd_epi16(_mm256_set1_epi16(scales[0]), p16l);
-        acc = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(p32l), acc);
-
-        const __m256i p32h = _mm256_madd_epi16(_mm256_set1_epi16(scales[1]), p16h);
-        acc = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(p32h), acc);
-
-    }
-
-    *s = hsum_float_8(acc) - summs;
-
-#elif defined __AVX__
-
-    const __m128i m4 = _mm_set1_epi8(0xF);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    float summs = 0;
-
-    uint16_t aux16[2];
-    const uint8_t * scales = (const uint8_t *)aux16;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = GGML_FP16_TO_FP32(x[i].d[0]) * y[i].d;
-        const float m = GGML_FP16_TO_FP32(x[i].d[1]) * y[i].d;
-        const __m256 vd = _mm256_set1_ps(d);
-
-        const uint16_t * a = (const uint16_t *)x[i].scales;
-        aux16[0] = a[0] & 0x0f0f;
-        aux16[1] = (a[0] >> 4) & 0x0f0f;
-
-        summs += m * (scales[2] * (y[i].bsums[0] + y[i].bsums[1]) + scales[3] * (y[i].bsums[2] + y[i].bsums[3]));
-
-        const uint8_t * restrict q4 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const __m256i q4bits = _mm256_loadu_si256((const __m256i*)q4);
-        const __m128i q4bits_0 = _mm256_extractf128_si256(q4bits, 0);
-        const __m128i q4bits_1 = _mm256_extractf128_si256(q4bits, 1);
-        const __m128i q4_0 = _mm_and_si128(q4bits_0, m4);
-        const __m128i q4_1 = _mm_and_si128(q4bits_1, m4);
-        const __m128i q4_2 = _mm_and_si128(_mm_srli_epi16(q4bits_0, 4), m4);
-        const __m128i q4_3 = _mm_and_si128(_mm_srli_epi16(q4bits_1, 4), m4);
-
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        const __m128i p16_0 = _mm_maddubs_epi16(q4_0, _mm256_extractf128_si256(q8_0, 0));
-        const __m128i p16_1 = _mm_maddubs_epi16(q4_1, _mm256_extractf128_si256(q8_0, 1));
-        const __m128i p16_2 = _mm_maddubs_epi16(q4_2, _mm256_extractf128_si256(q8_1, 0));
-        const __m128i p16_3 = _mm_maddubs_epi16(q4_3, _mm256_extractf128_si256(q8_1, 1));
-
-        const __m128i p32_0 = _mm_madd_epi16(_mm_set1_epi16(scales[0]), p16_0);
-        const __m128i p32_1 = _mm_madd_epi16(_mm_set1_epi16(scales[0]), p16_1);
-        acc = _mm256_add_ps(_mm256_mul_ps(vd, _mm256_cvtepi32_ps(MM256_SET_M128I(p32_1, p32_0))), acc);
-
-        const __m128i p32_2 = _mm_madd_epi16(_mm_set1_epi16(scales[1]), p16_2);
-        const __m128i p32_3 = _mm_madd_epi16(_mm_set1_epi16(scales[1]), p16_3);
-        acc = _mm256_add_ps(_mm256_mul_ps(vd, _mm256_cvtepi32_ps(MM256_SET_M128I(p32_3, p32_2))), acc);
-
-    }
-
-    *s = hsum_float_8(acc) - summs;
-
-#elif defined __riscv_v_intrinsic
-
-    uint16_t s16[2];
-    const uint8_t * restrict scales = (const uint8_t *)s16;
-
-    float sumf = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const uint8_t * restrict q4 = x[i].qs;
-        const  int8_t * restrict q8 = y[i].qs;
-
-        const uint16_t * restrict b = (const uint16_t *)x[i].scales;
-        s16[0] = b[0] & 0x0f0f;
-        s16[1] = (b[0] >> 4) & 0x0f0f;
-
-        sumf -= y[i].d * GGML_FP16_TO_FP32(x[i].d[1]) * (scales[2] * (y[i].bsums[0] + y[i].bsums[1]) + scales[3] * (y[i].bsums[2] + y[i].bsums[3]));
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d[0]);
-
-        size_t vl = 32;
-
-        vint16m1_t vzero = __riscv_vmv_v_x_i16m1(0, 1);
-
-        // load Q4
-        vuint8m1_t q4_x = __riscv_vle8_v_u8m1(q4, vl);
-
-        // load Q8 and multiply it with lower Q4 nibble
-        vint8m1_t  q4_a = __riscv_vreinterpret_v_u8m1_i8m1(__riscv_vand_vx_u8m1(q4_x, 0x0F, vl));
-        vint16m2_t va_0 = __riscv_vwmul_vv_i16m2(q4_a, __riscv_vle8_v_i8m1(q8, vl), vl);
-        vint16m1_t aux1 = __riscv_vredsum_vs_i16m2_i16m1(va_0, vzero, vl);
-
-        sumf += d*scales[0]*__riscv_vmv_x_s_i16m1_i16(aux1);
-
-        // load Q8 and multiply it with upper Q4 nibble
-        vint8m1_t  q4_s = __riscv_vreinterpret_v_u8m1_i8m1(__riscv_vsrl_vx_u8m1(q4_x, 0x04, vl));
-        vint16m2_t va_1 = __riscv_vwmul_vv_i16m2(q4_s, __riscv_vle8_v_i8m1(q8+32, vl), vl);
-        vint16m1_t aux2 = __riscv_vredsum_vs_i16m2_i16m1(va_1, vzero, vl);
-
-        sumf += d*scales[1]*__riscv_vmv_x_s_i16m1_i16(aux2);
-
-    }
-
-    *s = sumf;
-
-#elif defined(__POWER9_VECTOR__)
-    const vector signed char lowMask = vec_splats((signed char)0xF);
-    const vector unsigned char v4 = vec_splats((unsigned char)0x4);
-
-    vector float vsumf0 = vec_splats(0.0f);
-    vector float vsumf1 = vec_splats(0.0f);
-    vector float vsumf2 = vec_splats(0.0f);
-    vector float vsumf3 = vec_splats(0.0f);
-
-#pragma GCC unroll 2
-    for (int i = 0; i < nb; ++i) {
-        __builtin_prefetch(x[i].qs, 0, 1);
-        __builtin_prefetch(y[i].qs, 0, 1);
-
-        vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d[1]));
-        vector float vyd = vec_splats(y[i].d);
-        vector float vd= vec_mul(vxd, vyd);
-
-        uint16_t s16[2];
-        const uint8_t * scales = (const uint8_t *)s16;
-
-        const uint16_t * restrict b = (const uint16_t *)x[i].scales;
-        s16[0] = b[0] & 0x0f0f;
-        s16[1] = (b[0] >> 4) & 0x0f0f;
-
-        vector signed char utmps = (vector signed char)vec_xl_len(scales, 4);
-        vector signed short vscales = (vector signed short)vec_unpackh(utmps);
-        vector signed short q4xmins0 = vec_mergeh(vscales, vscales);
-        q4xmins0 = vec_sld(q4xmins0, q4xmins0, 8);
-
-        vector signed short q8ysums0 = vec_xl_len((const int16_t *)(y[i].bsums), 8);
-
-        vector signed int prod0 = vec_mule(q4xmins0, q8ysums0);
-        vector signed int prod1 = vec_mulo(q4xmins0, q8ysums0);
-
-        vsumf0 = vec_nmsub(vec_ctf(prod0, 0), vd, vsumf0);
-        vsumf1 = vec_nmsub(vec_ctf(prod1, 0), vd, vsumf1);
-
-        vd = vec_mul(vyd, vec_splats(GGML_FP16_TO_FP32(x[i].d[0])));
-
-        vector signed char qxs0 = (vector signed char)vec_xl( 0, x[i].qs);
-        vector signed char qxs1 = (vector signed char)vec_xl(16, x[i].qs);
-        vector signed char q4x00 = vec_and(qxs0, lowMask);
-        vector signed char q4x01 = vec_sr(qxs0, v4);
-        vector signed char q4x10 = vec_and(qxs1, lowMask);
-        vector signed char q4x11 = vec_sr(qxs1, v4);
-
-        vector signed char q8y00 = vec_xl( 0, y[i].qs);
-        vector signed char q8y10 = vec_xl(16, y[i].qs);
-        vector signed char q8y01 = vec_xl(32, y[i].qs);
-        vector signed char q8y11 = vec_xl(48, y[i].qs);
-
-        vector signed short qv00 = vec_add(vec_mule(q4x00, q8y00), vec_mulo(q4x00, q8y00));
-        vector signed short qv01 = vec_add(vec_mule(q4x01, q8y01), vec_mulo(q4x01, q8y01));
-        vector signed short qv10 = vec_add(vec_mule(q4x10, q8y10), vec_mulo(q4x10, q8y10));
-        vector signed short qv11 = vec_add(vec_mule(q4x11, q8y11), vec_mulo(q4x11, q8y11));
-
-        vector signed short vs0 = vec_splat(vscales, 0);
-        vector signed short vs1 = vec_splat(vscales, 1);
-
-        vector signed int vsumi0 = vec_add(vec_mule(qv00, vs0), vec_mulo(qv00, vs0));
-        vector signed int vsumi1 = vec_add(vec_mule(qv10, vs0), vec_mulo(qv10, vs0));
-        vector signed int vsumi2 = vec_add(vec_mule(qv01, vs1), vec_mulo(qv01, vs1));
-        vector signed int vsumi3 = vec_add(vec_mule(qv11, vs1), vec_mulo(qv11, vs1));
-
-        vsumf0 = vec_madd(vec_ctf(vsumi0, 0), vd, vsumf0);
-        vsumf1 = vec_madd(vec_ctf(vsumi1, 0), vd, vsumf1);
-        vsumf2 = vec_madd(vec_ctf(vsumi2, 0), vd, vsumf2);
-        vsumf3 = vec_madd(vec_ctf(vsumi3, 0), vd, vsumf3);
-    }
-
-    vsumf0 = vec_add(vsumf0, vsumf2);
-    vsumf1 = vec_add(vsumf1, vsumf3);
-
-    vsumf0 = vec_add(vsumf0, vsumf1);
-
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 4));
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
-
-    *s = vec_extract(vsumf0, 0);
-
-#else
-
-    uint8_t aux8[QK_K];
-    int16_t aux16[16];
-    float   sums [8];
-    memset(sums, 0, 8*sizeof(float));
-
-    uint16_t s16[2];
-    const uint8_t * restrict scales = (const uint8_t *)s16;
-
-    float sumf = 0;
-    for (int i = 0; i < nb; ++i) {
-        const uint8_t * restrict q4 = x[i].qs;
-        const  int8_t * restrict q8 = y[i].qs;
-        uint8_t * restrict a = aux8;
-        for (int l = 0; l < 32; ++l) a[l+ 0] = q4[l] & 0xF;
-        for (int l = 0; l < 32; ++l) a[l+32] = q4[l]  >> 4;
-
-        const uint16_t * restrict b = (const uint16_t *)x[i].scales;
-        s16[0] = b[0] & 0x0f0f;
-        s16[1] = (b[0] >> 4) & 0x0f0f;
-
-        sumf -= y[i].d * GGML_FP16_TO_FP32(x[i].d[1]) * (scales[2] * (y[i].bsums[0] + y[i].bsums[1]) + scales[3] * (y[i].bsums[2] + y[i].bsums[3]));
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d[0]);
-
-        for (int j = 0; j < QK_K/32; ++j) {
-            for (int l = 0; l < 16; ++l) aux16[l] = q8[l] * a[l];
-            q8 += 16; a += 16;
-            for (int l = 0; l < 16; ++l) aux16[l] += q8[l] * a[l];
-            q8 += 16; a += 16;
-            const float dl = d * scales[j];
-            for (int l = 0; l < 8; ++l) sums[l] += dl * (aux16[l] + aux16[l+8]);
-        }
-    }
-    for (int l = 0; l < 8; ++l) sumf += sums[l];
-    *s = sumf;
-#endif
-}
-#endif
-
-#if QK_K == 256
 void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy,  size_t by, int nrc) {
     assert(n % QK_K == 0);
     assert(nrc == 1);
@@ -7930,12 +7554,10 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 
     float summs = 0.f;
 
-   for (int i = 0; i < nb; ++i) {
-
+    for (int i = 0; i < nb; ++i) {
         const uint8_t * restrict q5 = x[i].qs;
         const int8_t  * restrict q8 = y[i].qs;
 
-#if QK_K == 256
         const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
         const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
 
@@ -7945,10 +7567,6 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, size_t bs, const void * r
         utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4);
         utmp[2] = uaux;
         utmp[0] &= kmask1;
-#else
-        // TODO
-        const float d = 0, dmin = 0;
-#endif
 
         const __m256i mins_and_scales = _mm256_cvtepu8_epi16(_mm_set_epi32(utmp[3], utmp[2], utmp[1], utmp[0]));
 
@@ -8316,6 +7934,79 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 
     *s = vec_extract(vsumf0, 0);
 
+#elif defined __loongarch_asx
+
+    const __m256i m4 = __lasx_xvreplgr2vr_b(0xF);
+    const __m128i mzero = __lsx_vldi(0);
+    const __m256i mone  = __lasx_xvreplgr2vr_b(1);
+
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    float summs = 0.f;
+
+   for (int i = 0; i < nb; ++i) {
+
+        const uint8_t * restrict q5 = x[i].qs;
+        const int8_t  * restrict q8 = y[i].qs;
+
+        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
+        const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
+
+        memcpy(utmp, x[i].scales, 12);
+
+        const __m256i mins_and_scales = lasx_extu8_16(lsx_set_w(utmp[3], utmp[2], utmp[1], utmp[0]));
+
+        const __m256i q8sums = __lasx_xvld((const __m256i*)y[i].bsums, 0);
+        const __m128i q8s = lsx_hadd_h(lasx_extracti128(q8sums, 0), lasx_extracti128(q8sums, 1));
+        const __m128i prod = lsx_madd_h(lasx_extracti128(mins_and_scales, 1), q8s);
+        const __m128i hsum = lsx_hadd_w(lsx_hadd_w(prod, mzero), mzero);
+        summs += dmin * __lsx_vpickve2gr_w(hsum, 0);    //TODO check
+
+        const __m128i sc128  = lasx_extracti128(mins_and_scales, 0);
+        const __m256i scales = lasx_insertf128(sc128, sc128);
+
+        const __m256i hbits = __lasx_xvld((const __m256i*)x[i].qh, 0);
+        __m256i hmask = mone;
+
+        __m256i sumi = __lasx_xvldi(0);
+
+        int bit = 0;
+
+        for (int j = 0; j < QK_K/64; ++j) {
+
+            const __m256i scale_0 = lasx_shuffle_b(scales, get_scale_shuffle_k4(2*j+0));
+            const __m256i scale_1 = lasx_shuffle_b(scales, get_scale_shuffle_k4(2*j+1));
+
+            const __m256i q5bits = __lasx_xvld((const __m256i*)q5, 0); q5 += 32;
+
+            const __m256i q5l_0 = __lasx_xvand_v(q5bits, m4);
+            const __m256i q5h_0 = __lasx_xvslli_h(__lasx_xvsrli_h(__lasx_xvand_v(hbits, hmask), bit++), 4);
+            const __m256i q5_0  = __lasx_xvadd_b(q5l_0, q5h_0);
+            hmask = __lasx_xvslli_h(hmask, 1);
+
+            const __m256i q5l_1 = __lasx_xvand_v(__lasx_xvsrli_h(q5bits, 4), m4);
+            const __m256i q5h_1 = __lasx_xvslli_h(__lasx_xvsrli_h(__lasx_xvand_v(hbits, hmask), bit++), 4);
+            const __m256i q5_1  = __lasx_xvadd_b(q5l_1, q5h_1);
+            hmask = __lasx_xvslli_h(hmask, 1);
+
+            const __m256i q8_0 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_1 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+
+            __m256i p16_0 = lasx_maddubs_h(q5_0, q8_0);
+            __m256i p16_1 = lasx_maddubs_h(q5_1, q8_1);
+
+            p16_0 = lasx_madd_h(scale_0, p16_0);
+            p16_1 = lasx_madd_h(scale_1, p16_1);
+
+            sumi = __lasx_xvadd_w(sumi, __lasx_xvadd_w(p16_0, p16_1));
+        }
+
+        __m256 vd = __lasx_xvreplfr2vr_s(d);
+        acc = __lasx_xvfmadd_s(vd, __lasx_xvffint_s_w(sumi), acc);
+    }
+
+    *s = hsum_float_8(acc) + summs;
+
 #else
 
     const uint8_t * scales = (const uint8_t*)&utmp[0];
@@ -8380,356 +8071,6 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 #endif
 }
 
-#else
-
-void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
-    assert(n % QK_K == 0);
-    assert(nrc == 1);
-    UNUSED(nrc);
-    UNUSED(bx);
-    UNUSED(by);
-    UNUSED(bs);
-
-    const block_q5_K * restrict x = vx;
-    const block_q8_K * restrict y = vy;
-
-    const int nb = n / QK_K;
-
-#ifdef __ARM_NEON
-    const uint8x16_t m4b = vdupq_n_u8(0xf);
-    const uint8x16_t mh = vdupq_n_u8(16);
-    const int32x4_t mzero = vdupq_n_s32(0);
-
-    ggml_int8x16x4_t q5bytes;
-    ggml_uint8x16x4_t q5h;
-
-    float sumf = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const int8_t * sc = x[i].scales;
-
-        const uint8_t * restrict q5 = x[i].qs;
-        const uint8_t * restrict qh = x[i].qh;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const uint8x8_t qhbits = vld1_u8(qh);
-
-        const ggml_uint8x16x2_t q5bits = ggml_vld1q_u8_x2(q5);
-        const ggml_int8x16x4_t q8bytes = ggml_vld1q_s8_x4(q8);
-
-        const uint8x16_t htmp = vcombine_u8(qhbits, vshr_n_u8(qhbits, 1));
-        q5h.val[0] = vbicq_u8(mh, vshlq_n_u8(htmp, 4));
-        q5h.val[1] = vbicq_u8(mh, vshlq_n_u8(htmp, 2));
-        q5h.val[2] = vbicq_u8(mh, htmp);
-        q5h.val[3] = vbicq_u8(mh, vshrq_n_u8(htmp, 2));
-
-        q5bytes.val[0] = vsubq_s8(vreinterpretq_s8_u8(vandq_u8(q5bits.val[0], m4b)), vreinterpretq_s8_u8(q5h.val[0]));
-        q5bytes.val[1] = vsubq_s8(vreinterpretq_s8_u8(vandq_u8(q5bits.val[1], m4b)), vreinterpretq_s8_u8(q5h.val[1]));
-        q5bytes.val[2] = vsubq_s8(vreinterpretq_s8_u8(vshrq_n_u8(q5bits.val[0], 4)), vreinterpretq_s8_u8(q5h.val[2]));
-        q5bytes.val[3] = vsubq_s8(vreinterpretq_s8_u8(vshrq_n_u8(q5bits.val[1], 4)), vreinterpretq_s8_u8(q5h.val[3]));
-
-        int32_t sumi1 = sc[0] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[0], q8bytes.val[0]));
-        int32_t sumi2 = sc[1] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[1], q8bytes.val[1]));
-        int32_t sumi3 = sc[2] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[2], q8bytes.val[2]));
-        int32_t sumi4 = sc[3] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[3], q8bytes.val[3]));
-
-        sumf += d * (sumi1 + sumi2 + sumi3 + sumi4);
-    }
-
-    *s = sumf;
-
-#elif defined __AVX2__
-
-    const __m256i m4 = _mm256_set1_epi8(0xF);
-    const __m256i mone  = _mm256_set1_epi8(1);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    for (int i = 0; i < nb; ++i) {
-
-        const uint8_t * restrict q5 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        const __m256i q5bits = _mm256_loadu_si256((const __m256i*)q5);
-
-        const __m256i scale_l = MM256_SET_M128I(_mm_set1_epi16(x[i].scales[1]), _mm_set1_epi16(x[i].scales[0]));
-        const __m256i scale_h = MM256_SET_M128I(_mm_set1_epi16(x[i].scales[3]), _mm_set1_epi16(x[i].scales[2]));
-
-        int64_t aux64;
-        memcpy(&aux64, x[i].qh, 8);
-        const __m128i haux128 = _mm_set_epi64x(aux64 >> 1, aux64);
-        const __m256i haux256 = MM256_SET_M128I(_mm_srli_epi16(haux128, 2), haux128);
-
-        const __m256i q5h_0 = _mm256_slli_epi16(_mm256_andnot_si256(haux256, mone), 4);
-        const __m256i q5h_1 = _mm256_slli_epi16(_mm256_andnot_si256(_mm256_srli_epi16(haux256, 4), mone), 4);
-
-        const __m256i q5l_0 = _mm256_and_si256(q5bits, m4);
-        const __m256i q5l_1 = _mm256_and_si256(_mm256_srli_epi16(q5bits, 4), m4);
-
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        const __m256i p16_0 = _mm256_madd_epi16(scale_l, _mm256_maddubs_epi16(q5l_0, q8_0));
-        const __m256i p16_1 = _mm256_madd_epi16(scale_h, _mm256_maddubs_epi16(q5l_1, q8_1));
-        const __m256i s16_0 = _mm256_madd_epi16(scale_l, _mm256_maddubs_epi16(q5h_0, q8_0));
-        const __m256i s16_1 = _mm256_madd_epi16(scale_h, _mm256_maddubs_epi16(q5h_1, q8_1));
-
-        const __m256i dot = _mm256_sub_epi32(_mm256_add_epi32(p16_0, p16_1), _mm256_add_epi32(s16_0, s16_1));
-
-        acc = _mm256_fmadd_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(dot), acc);
-
-    }
-
-    *s = hsum_float_8(acc);
-
-#elif defined __AVX__
-
-    const __m128i m4 = _mm_set1_epi8(0xF);
-    const __m128i mone  = _mm_set1_epi8(1);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    for (int i = 0; i < nb; ++i) {
-
-        const uint8_t * restrict q5 = x[i].qs;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        const __m256i q5bits = _mm256_loadu_si256((const __m256i*)q5);
-
-        const __m128i scale_0 = _mm_set1_epi16(x[i].scales[0]);
-        const __m128i scale_1 = _mm_set1_epi16(x[i].scales[1]);
-        const __m128i scale_2 = _mm_set1_epi16(x[i].scales[2]);
-        const __m128i scale_3 = _mm_set1_epi16(x[i].scales[3]);
-
-        int64_t aux64;
-        memcpy(&aux64, x[i].qh, 8);
-        const __m128i haux128_0 = _mm_set_epi64x(aux64 >> 1, aux64);
-        const __m128i haux128_1 = _mm_srli_epi16(haux128_0, 2);
-
-        const __m128i q5h_0 = _mm_slli_epi16(_mm_andnot_si128(haux128_0, mone), 4);
-        const __m128i q5h_1 = _mm_slli_epi16(_mm_andnot_si128(haux128_1, mone), 4);
-        const __m128i q5h_2 = _mm_slli_epi16(_mm_andnot_si128(_mm_srli_epi16(haux128_0, 4), mone), 4);
-        const __m128i q5h_3 = _mm_slli_epi16(_mm_andnot_si128(_mm_srli_epi16(haux128_1, 4), mone), 4);
-
-        const __m128i q5l_0 = _mm_and_si128(_mm256_extractf128_si256(q5bits, 0), m4);
-        const __m128i q5l_1 = _mm_and_si128(_mm256_extractf128_si256(q5bits, 1), m4);
-        const __m128i q5l_2 = _mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q5bits, 0), 4), m4);
-        const __m128i q5l_3 = _mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q5bits, 1), 4), m4);
-
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        const __m128i p16_0 = _mm_madd_epi16(scale_0, _mm_maddubs_epi16(q5l_0, _mm256_extractf128_si256(q8_0, 0)));
-        const __m128i p16_1 = _mm_madd_epi16(scale_1, _mm_maddubs_epi16(q5l_1, _mm256_extractf128_si256(q8_0, 1)));
-        const __m128i p16_2 = _mm_madd_epi16(scale_2, _mm_maddubs_epi16(q5l_2, _mm256_extractf128_si256(q8_1, 0)));
-        const __m128i p16_3 = _mm_madd_epi16(scale_3, _mm_maddubs_epi16(q5l_3, _mm256_extractf128_si256(q8_1, 1)));
-        const __m128i s16_0 = _mm_madd_epi16(scale_0, _mm_maddubs_epi16(q5h_0, _mm256_extractf128_si256(q8_0, 0)));
-        const __m128i s16_1 = _mm_madd_epi16(scale_1, _mm_maddubs_epi16(q5h_1, _mm256_extractf128_si256(q8_0, 1)));
-        const __m128i s16_2 = _mm_madd_epi16(scale_2, _mm_maddubs_epi16(q5h_2, _mm256_extractf128_si256(q8_1, 0)));
-        const __m128i s16_3 = _mm_madd_epi16(scale_3, _mm_maddubs_epi16(q5h_3, _mm256_extractf128_si256(q8_1, 1)));
-
-        const __m128i dot_0 = _mm_sub_epi32(_mm_add_epi32(p16_0, p16_2), _mm_add_epi32(s16_0, s16_2));
-        const __m128i dot_1 = _mm_sub_epi32(_mm_add_epi32(p16_1, p16_3), _mm_add_epi32(s16_1, s16_3));
-
-        acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(MM256_SET_M128I(dot_1, dot_0))), acc);
-
-    }
-
-    *s = hsum_float_8(acc);
-
-#elif defined __riscv_v_intrinsic
-
-    float sumf = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const int8_t * sc = x[i].scales;
-
-        const uint8_t * restrict q5 = x[i].qs;
-        const uint8_t * restrict qh = x[i].qh;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        vint32m1_t vzero = __riscv_vmv_v_x_i32m1(0, 1);
-
-        // load qh
-        vuint8mf4_t qh_x1   = __riscv_vle8_v_u8mf4(qh, 8);
-        vuint8mf2_t qh_x2   = __riscv_vlmul_ext_v_u8mf4_u8mf2(__riscv_vsrl_vx_u8mf4(qh_x1, 1, 8));
-
-        size_t vl = 16;
-
-        // combine both qh_1 and qh_2
-        vuint8mf2_t qh_x = __riscv_vslideup_vx_u8mf2(__riscv_vlmul_ext_v_u8mf4_u8mf2(qh_x1), qh_x2, vl/2, vl);
-
-        vuint8mf2_t qh_h0 = __riscv_vand_vx_u8mf2(__riscv_vnot_v_u8mf2(__riscv_vsll_vx_u8mf2(qh_x, 0x4, vl), vl), 16, vl);
-        vuint8mf2_t qh_h1 = __riscv_vand_vx_u8mf2(__riscv_vnot_v_u8mf2(__riscv_vsll_vx_u8mf2(qh_x, 0x2, vl), vl), 16, vl);
-        vuint8mf2_t qh_h2 = __riscv_vand_vx_u8mf2(__riscv_vnot_v_u8mf2(qh_x, vl), 16, vl);
-        vuint8mf2_t qh_h3 = __riscv_vand_vx_u8mf2(__riscv_vnot_v_u8mf2(__riscv_vsrl_vx_u8mf2(qh_x, 0x4, vl), vl), 16, vl);
-
-        vint8mf2_t qh_0 = __riscv_vreinterpret_v_u8mf2_i8mf2(qh_h0);
-        vint8mf2_t qh_1 = __riscv_vreinterpret_v_u8mf2_i8mf2(qh_h1);
-        vint8mf2_t qh_2 = __riscv_vreinterpret_v_u8mf2_i8mf2(qh_h2);
-        vint8mf2_t qh_3 = __riscv_vreinterpret_v_u8mf2_i8mf2(qh_h3);
-
-        // load q5
-        vuint8mf2_t q5_x1  = __riscv_vle8_v_u8mf2(q5, vl);
-        vuint8mf2_t q5_x2  = __riscv_vle8_v_u8mf2(q5+16, vl);
-
-        vint8mf2_t q5s_0 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vand_vx_u8mf2(q5_x1, 0xF, vl));
-        vint8mf2_t q5s_1 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vand_vx_u8mf2(q5_x2, 0xF, vl));
-        vint8mf2_t q5s_2 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vsrl_vx_u8mf2(q5_x1, 0x4, vl));
-        vint8mf2_t q5s_3 = __riscv_vreinterpret_v_u8mf2_i8mf2(__riscv_vsrl_vx_u8mf2(q5_x2, 0x4, vl));
-
-        vint8mf2_t q5_0 = __riscv_vsub_vv_i8mf2(q5s_0, qh_0, vl);
-        vint8mf2_t q5_1 = __riscv_vsub_vv_i8mf2(q5s_1, qh_1, vl);
-        vint8mf2_t q5_2 = __riscv_vsub_vv_i8mf2(q5s_2, qh_2, vl);
-        vint8mf2_t q5_3 = __riscv_vsub_vv_i8mf2(q5s_3, qh_3, vl);
-
-        // load Q8 and multiply it with Q5
-        vint16m1_t p0 = __riscv_vwmul_vv_i16m1(q5_0, __riscv_vle8_v_i8mf2(q8, vl), vl);
-        vint16m1_t p1 = __riscv_vwmul_vv_i16m1(q5_1, __riscv_vle8_v_i8mf2(q8+16, vl), vl);
-        vint16m1_t p2 = __riscv_vwmul_vv_i16m1(q5_2, __riscv_vle8_v_i8mf2(q8+32, vl), vl);
-        vint16m1_t p3 = __riscv_vwmul_vv_i16m1(q5_3, __riscv_vle8_v_i8mf2(q8+48, vl), vl);
-
-        vint32m1_t vs_0 = __riscv_vwredsum_vs_i16m1_i32m1(p0, vzero, vl);
-        vint32m1_t vs_1 = __riscv_vwredsum_vs_i16m1_i32m1(p1, vzero, vl);
-        vint32m1_t vs_2 = __riscv_vwredsum_vs_i16m1_i32m1(p2, vzero, vl);
-        vint32m1_t vs_3 = __riscv_vwredsum_vs_i16m1_i32m1(p3, vzero, vl);
-
-        int32_t sumi1 = sc[0] * __riscv_vmv_x_s_i32m1_i32(vs_0);
-        int32_t sumi2 = sc[1] * __riscv_vmv_x_s_i32m1_i32(vs_1);
-        int32_t sumi3 = sc[2] * __riscv_vmv_x_s_i32m1_i32(vs_2);
-        int32_t sumi4 = sc[3] * __riscv_vmv_x_s_i32m1_i32(vs_3);
-
-        sumf += d * (sumi1 + sumi2 + sumi3 + sumi4);
-
-    }
-
-    *s = sumf;
-
-#elif defined(__POWER9_VECTOR__)
-    const vector signed char lowMask = vec_splats((signed char)0xF);
-    const vector unsigned char v1 = vec_splats((unsigned char)0x1);
-    const vector unsigned char v2 = vec_splats((unsigned char)0x2);
-    const vector unsigned char v4 = vec_splats((unsigned char)0x4);
-
-    vector float vsumf0 = vec_splats(0.0f);
-    vector float vsumf1 = vec_splats(0.0f);
-    vector float vsumf2 = vec_splats(0.0f);
-    vector float vsumf3 = vec_splats(0.0f);
-
-#pragma GCC unroll 2
-    for (int i = 0; i < nb; ++i) {
-        __builtin_prefetch(x[i].qs, 0, 1);
-        __builtin_prefetch(y[i].qs, 0, 1);
-
-        vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
-        vector float vyd = vec_splats(y[i].d);
-        vector float vd= vec_mul(vxd, vyd);
-
-        vector signed char qxs0 = (vector signed char)vec_xl( 0, x[i].qs);
-        vector signed char qxs1 = (vector signed char)vec_xl(16, x[i].qs);
-        vector signed char qxs00 = (vector signed char)vec_and(qxs0, lowMask);
-        vector signed char qxs01 = (vector signed char)vec_sr(qxs0, v4);
-        vector signed char qxs10 = (vector signed char)vec_and(qxs1, lowMask);
-        vector signed char qxs11 = (vector signed char)vec_sr(qxs1, v4);
-
-        vector signed char qxhs = (vector signed char)vec_xl_len(x[i].qh, 8);
-        vector signed char qxhs0 = vec_or(qxhs, vec_sr(vec_sld(qxhs, qxhs, 8), v1));
-        vector signed char qxhs1 = vec_sr(qxhs0, v2);
-        vector signed char qxh00 = vec_sl(vec_andc((vector signed char)v1, qxhs0), v4);
-        vector signed char qxh10 = vec_sl(vec_andc((vector signed char)v1, qxhs1), v4);
-        vector signed char qxh01 = vec_sl(vec_andc((vector signed char)v1, vec_sr(qxhs0, v4)), v4);
-        vector signed char qxh11 = vec_sl(vec_andc((vector signed char)v1, vec_sr(qxhs1, v4)), v4);
-
-        vector signed char q5x00 = vec_sub(qxs00, qxh00);
-        vector signed char q5x10 = vec_sub(qxs10, qxh10);
-        vector signed char q5x01 = vec_sub(qxs01, qxh01);
-        vector signed char q5x11 = vec_sub(qxs11, qxh11);
-
-        vector signed char q8y00 = vec_xl( 0, y[i].qs);
-        vector signed char q8y10 = vec_xl(16, y[i].qs);
-        vector signed char q8y01 = vec_xl(32, y[i].qs);
-        vector signed char q8y11 = vec_xl(48, y[i].qs);
-
-        vector signed short qv00 = vec_add(vec_mule(q5x00, q8y00), vec_mulo(q5x00, q8y00));
-        vector signed short qv01 = vec_add(vec_mule(q5x01, q8y01), vec_mulo(q5x01, q8y01));
-        vector signed short qv10 = vec_add(vec_mule(q5x10, q8y10), vec_mulo(q5x10, q8y10));
-        vector signed short qv11 = vec_add(vec_mule(q5x11, q8y11), vec_mulo(q5x11, q8y11));
-
-        vector signed short vs = (vector signed short)vec_unpackh(vec_xl_len(x[i].scales, 4));
-        vector signed short vs0 = vec_splat(vs, 0);
-        vector signed short vs1 = vec_splat(vs, 1);
-        vector signed short vs2 = vec_splat(vs, 2);
-        vector signed short vs3 = vec_splat(vs, 3);
-
-        vector signed int vsumi0 = vec_add(vec_mule(qv00, vs0), vec_mulo(qv00, vs0));
-        vector signed int vsumi1 = vec_add(vec_mule(qv10, vs1), vec_mulo(qv10, vs1));
-        vector signed int vsumi2 = vec_add(vec_mule(qv01, vs2), vec_mulo(qv01, vs2));
-        vector signed int vsumi3 = vec_add(vec_mule(qv11, vs3), vec_mulo(qv11, vs3));
-
-        vsumf0 = vec_madd(vec_ctf(vsumi0, 0), vd, vsumf0);
-        vsumf1 = vec_madd(vec_ctf(vsumi1, 0), vd, vsumf1);
-        vsumf2 = vec_madd(vec_ctf(vsumi2, 0), vd, vsumf2);
-        vsumf3 = vec_madd(vec_ctf(vsumi3, 0), vd, vsumf3);
-    }
-
-    vsumf0 = vec_add(vsumf0, vsumf2);
-    vsumf1 = vec_add(vsumf1, vsumf3);
-
-    vsumf0 = vec_add(vsumf0, vsumf1);
-
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 4));
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
-
-    *s = vec_extract(vsumf0, 0);
-
-#else
-
-    int8_t aux8[QK_K];
-    int16_t aux16[16];
-    float   sums [8];
-    memset(sums, 0, 8*sizeof(float));
-
-    float sumf = 0;
-    for (int i = 0; i < nb; ++i) {
-        const uint8_t * restrict q4 = x[i].qs;
-        const uint8_t * restrict hm = x[i].qh;
-        const  int8_t * restrict q8 = y[i].qs;
-        int8_t * restrict a = aux8;
-        for (int l = 0; l < 32; ++l) {
-            a[l+ 0] = q4[l] & 0xF;
-            a[l+32] = q4[l]  >> 4;
-        }
-        for (int is = 0; is < 8; ++is) {
-            uint8_t m = 1 << is;
-            for (int l = 0; l < 8; ++l) a[8*is + l] -= (hm[l] & m ? 0 : 16);
-        }
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-        const int8_t * restrict sc = x[i].scales;
-
-        for (int j = 0; j < QK_K/16; ++j) {
-            const float dl = d * sc[j];
-            for (int l = 0; l < 16; ++l) aux16[l] = q8[l] * a[l];
-            for (int l = 0; l <  8; ++l) sums[l] += dl * (aux16[l] + aux16[8+l]);
-            q8 += 16; a += 16;
-        }
-    }
-    for (int l = 0; l < 8; ++l) sumf += sums[l];
-    *s = sumf;
-#endif
-}
-#endif
-
-
-#if QK_K == 256
 void ggml_vec_dot_q6_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
     assert(n % QK_K == 0);
     assert(nrc == 1);
@@ -9265,6 +8606,84 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 
     *s = vec_extract(vsumf0, 0);
 
+#elif defined __loongarch_asx
+
+    const __m256i m4 = __lasx_xvreplgr2vr_b(0xF);
+    const __m256i m2 = __lasx_xvreplgr2vr_b(3);
+    const __m256i m32s = __lasx_xvreplgr2vr_b(32);
+
+    __m256 acc = (__m256)__lasx_xvldi(0);
+
+    for (int i = 0; i < nb; ++i) {
+
+        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
+
+        const uint8_t * restrict q4 = x[i].ql;
+        const uint8_t * restrict qh = x[i].qh;
+        const int8_t  * restrict q8 = y[i].qs;
+
+        const __m128i scales = __lsx_vld((const __m128i*)x[i].scales, 0);
+
+        __m256i sumi = __lasx_xvldi(0);
+
+        int is = 0;
+
+        for (int j = 0; j < QK_K/128; ++j) {
+
+            const __m128i scale_0 = lsx_shuffle_b(scales, get_scale_shuffle(is + 0));
+            const __m128i scale_1 = lsx_shuffle_b(scales, get_scale_shuffle(is + 1));
+            const __m128i scale_2 = lsx_shuffle_b(scales, get_scale_shuffle(is + 2));
+            const __m128i scale_3 = lsx_shuffle_b(scales, get_scale_shuffle(is + 3));
+            is += 4;
+
+            const __m256i q4bits1 = __lasx_xvld((const __m256i*)q4, 0); q4 += 32;
+            const __m256i q4bits2 = __lasx_xvld((const __m256i*)q4, 0); q4 += 32;
+            const __m256i q4bitsH = __lasx_xvld((const __m256i*)qh, 0); qh += 32;
+
+            const __m256i q4h_0 = __lasx_xvslli_h(__lasx_xvand_v(q4bitsH, m2), 4);
+            const __m256i q4h_1 = __lasx_xvslli_h(__lasx_xvand_v(__lasx_xvsrli_h(q4bitsH, 2), m2), 4);
+            const __m256i q4h_2 = __lasx_xvslli_h(__lasx_xvand_v(__lasx_xvsrli_h(q4bitsH, 4), m2), 4);
+            const __m256i q4h_3 = __lasx_xvslli_h(__lasx_xvand_v(__lasx_xvsrli_h(q4bitsH, 6), m2), 4);
+
+            const __m256i q4_0 = __lasx_xvor_v(__lasx_xvand_v(q4bits1, m4), q4h_0);
+            const __m256i q4_1 = __lasx_xvor_v(__lasx_xvand_v(q4bits2, m4), q4h_1);
+            const __m256i q4_2 = __lasx_xvor_v(__lasx_xvand_v(__lasx_xvsrli_h(q4bits1, 4), m4), q4h_2);
+            const __m256i q4_3 = __lasx_xvor_v(__lasx_xvand_v(__lasx_xvsrli_h(q4bits2, 4), m4), q4h_3);
+
+            const __m256i q8_0 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_1 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8_3 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+
+            __m256i q8s_0 = lasx_maddubs_h(m32s, q8_0);
+            __m256i q8s_1 = lasx_maddubs_h(m32s, q8_1);
+            __m256i q8s_2 = lasx_maddubs_h(m32s, q8_2);
+            __m256i q8s_3 = lasx_maddubs_h(m32s, q8_3);
+
+            __m256i p16_0 = lasx_maddubs_h(q4_0, q8_0);
+            __m256i p16_1 = lasx_maddubs_h(q4_1, q8_1);
+            __m256i p16_2 = lasx_maddubs_h(q4_2, q8_2);
+            __m256i p16_3 = lasx_maddubs_h(q4_3, q8_3);
+
+            p16_0 = __lasx_xvsub_h(p16_0, q8s_0);
+            p16_1 = __lasx_xvsub_h(p16_1, q8s_1);
+            p16_2 = __lasx_xvsub_h(p16_2, q8s_2);
+            p16_3 = __lasx_xvsub_h(p16_3, q8s_3);
+
+            p16_0 = lasx_madd_h(lasx_ext8_16(scale_0), p16_0);
+            p16_1 = lasx_madd_h(lasx_ext8_16(scale_1), p16_1);
+            p16_2 = lasx_madd_h(lasx_ext8_16(scale_2), p16_2);
+            p16_3 = lasx_madd_h(lasx_ext8_16(scale_3), p16_3);
+
+            sumi = __lasx_xvadd_w(sumi, __lasx_xvadd_w(p16_0, p16_1));
+            sumi = __lasx_xvadd_w(sumi, __lasx_xvadd_w(p16_2, p16_3));
+        }
+
+        acc = __lasx_xvfmadd_s((__m256)__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(sumi), acc);
+    }
+
+    *s = hsum_float_8(acc);
+
 #else
 
     int8_t  aux8[QK_K];
@@ -9310,388 +8729,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * restrict s, size_t bs, const void * r
 #endif
 }
 
-#else
-
-void ggml_vec_dot_q6_K_q8_K(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
-    assert(n % QK_K == 0);
-    assert(nrc == 1);
-    UNUSED(nrc);
-    UNUSED(bx);
-    UNUSED(by);
-    UNUSED(bs);
-
-    const block_q6_K * restrict x = vx;
-    const block_q8_K * restrict y = vy;
-
-    const int nb = n / QK_K;
-
-#ifdef __ARM_NEON
-    float sum = 0;
-
-    const uint8x16_t m4b = vdupq_n_u8(0xF);
-    const int8x16_t  m32s = vdupq_n_s8(32);
-    const int32x4_t  vzero = vdupq_n_s32(0);
-
-    const uint8x16_t mone = vdupq_n_u8(3);
-
-    ggml_int8x16x4_t q6bytes;
-    ggml_uint8x16x4_t q6h;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d_all = GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8_t * restrict q6 = x[i].ql;
-        const uint8_t * restrict qh = x[i].qh;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const int8_t * restrict scale = x[i].scales;
-
-        int32_t isum = 0;
-
-        uint8x16_t qhbits = vld1q_u8(qh);
-        ggml_uint8x16x2_t q6bits = ggml_vld1q_u8_x2(q6);
-        ggml_int8x16x4_t q8bytes = ggml_vld1q_s8_x4(q8);
-
-        q6h.val[0] = vshlq_n_u8(vandq_u8(mone, qhbits), 4);
-        uint8x16_t shifted = vshrq_n_u8(qhbits, 2);
-        q6h.val[1] = vshlq_n_u8(vandq_u8(mone, shifted), 4);
-        shifted = vshrq_n_u8(qhbits, 4);
-        q6h.val[2] = vshlq_n_u8(vandq_u8(mone, shifted), 4);
-        shifted = vshrq_n_u8(qhbits, 6);
-        q6h.val[3] = vshlq_n_u8(vandq_u8(mone, shifted), 4);
-
-        q6bytes.val[0] = vsubq_s8(vreinterpretq_s8_u8(vorrq_u8(vandq_u8(q6bits.val[0], m4b), q6h.val[0])), m32s);
-        q6bytes.val[1] = vsubq_s8(vreinterpretq_s8_u8(vorrq_u8(vandq_u8(q6bits.val[1], m4b), q6h.val[1])), m32s);
-        q6bytes.val[2] = vsubq_s8(vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6bits.val[0], 4), q6h.val[2])), m32s);
-        q6bytes.val[3] = vsubq_s8(vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6bits.val[1], 4), q6h.val[3])), m32s);
-
-        isum += vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[0], q8bytes.val[0])) * scale[0] +
-                vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[1], q8bytes.val[1])) * scale[1] +
-                vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[2], q8bytes.val[2])) * scale[2] +
-                vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[3], q8bytes.val[3])) * scale[3];
-
-        sum += isum * d_all * y[i].d;
-
-    }
-    *s = sum;
-
-#elif defined __AVX2__
-
-    const __m256i m4 = _mm256_set1_epi8(0xF);
-    const __m256i m2 = _mm256_set1_epi8(3);
-    const __m256i m32s = _mm256_set1_epi8(32);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8_t * restrict q4 = x[i].ql;
-        const uint8_t * restrict qh = x[i].qh;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const __m64 scales_1 = _mm_set1_pi8(x[i].scales[0]);
-        const __m64 scales_2 = _mm_set1_pi8(x[i].scales[1]);
-        const __m64 scales_3 = _mm_set1_pi8(x[i].scales[2]);
-        const __m64 scales_4 = _mm_set1_pi8(x[i].scales[3]);
-
-        __m256i sumi = _mm256_setzero_si256();
-
-        const __m128i scale_0 = _mm_set_epi64(scales_2, scales_1);
-        const __m128i scale_1 = _mm_set_epi64(scales_4, scales_3);
-
-        const __m256i q4bits1 = _mm256_loadu_si256((const __m256i*)q4);
-        const __m128i q4bitsH = _mm_loadu_si128((const __m128i*)qh);
-
-        const __m256i q4h_0 = _mm256_slli_epi16(_mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q4bitsH, 2), q4bitsH), m2), 4);
-        const __m256i q4h_1 = _mm256_slli_epi16(_mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q4bitsH, 6), _mm_srli_epi16(q4bitsH, 4)), m2), 4);
-
-        const __m256i q4_0 = _mm256_or_si256(_mm256_and_si256(q4bits1, m4), q4h_0);
-        const __m256i q4_1 = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(q4bits1, 4), m4), q4h_1);
-
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        __m256i q8s_0 = _mm256_maddubs_epi16(m32s, q8_0);
-        __m256i q8s_1 = _mm256_maddubs_epi16(m32s, q8_1);
-
-        __m256i p16_0 = _mm256_maddubs_epi16(q4_0, q8_0);
-        __m256i p16_1 = _mm256_maddubs_epi16(q4_1, q8_1);
-
-        p16_0 = _mm256_sub_epi16(p16_0, q8s_0);
-        p16_1 = _mm256_sub_epi16(p16_1, q8s_1);
-
-        p16_0 = _mm256_madd_epi16(_mm256_cvtepi8_epi16(scale_0), p16_0);
-        p16_1 = _mm256_madd_epi16(_mm256_cvtepi8_epi16(scale_1), p16_1);
-
-        sumi = _mm256_add_epi32(sumi, _mm256_add_epi32(p16_0, p16_1));
-
-        acc = _mm256_fmadd_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(sumi), acc);
-    }
-
-    *s = hsum_float_8(acc);
-
-#elif defined __AVX__
-
-    const __m128i m4 = _mm_set1_epi8(0xF);
-    const __m128i m2 = _mm_set1_epi8(3);
-    const __m128i m32s = _mm_set1_epi8(32);
-
-    __m256 acc = _mm256_setzero_ps();
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8_t * restrict q4 = x[i].ql;
-        const uint8_t * restrict qh = x[i].qh;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const __m64 scales_1 = _mm_set1_pi8(x[i].scales[0]);
-        const __m64 scales_2 = _mm_set1_pi8(x[i].scales[1]);
-        const __m64 scales_3 = _mm_set1_pi8(x[i].scales[2]);
-        const __m64 scales_4 = _mm_set1_pi8(x[i].scales[3]);
-
-        __m128i sumi_0 = _mm_setzero_si128();
-        __m128i sumi_1 = _mm_setzero_si128();
-
-        const __m128i scale_0 = _mm_set_epi64(scales_2, scales_1);
-        const __m128i scale_1 = _mm_set_epi64(scales_4, scales_3);
-
-        const __m256i q4bits1 = _mm256_loadu_si256((const __m256i*)q4);
-        const __m128i q4bitsH = _mm_loadu_si128((const __m128i*)qh);
-
-        const __m128i q4h_0 = _mm_slli_epi16(_mm_and_si128(q4bitsH, m2), 4);
-        const __m128i q4h_1 = _mm_slli_epi16(_mm_and_si128(_mm_srli_epi16(q4bitsH, 2), m2), 4);
-        const __m128i q4h_2 = _mm_slli_epi16(_mm_and_si128(_mm_srli_epi16(q4bitsH, 4), m2), 4);
-        const __m128i q4h_3 = _mm_slli_epi16(_mm_and_si128(_mm_srli_epi16(q4bitsH, 6), m2), 4);
-
-        const __m128i q4_0 = _mm_or_si128(_mm_and_si128(_mm256_extractf128_si256(q4bits1, 0), m4), q4h_0);
-        const __m128i q4_1 = _mm_or_si128(_mm_and_si128(_mm256_extractf128_si256(q4bits1, 1), m4), q4h_1);
-        const __m128i q4_2 = _mm_or_si128(_mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q4bits1, 0), 4), m4), q4h_2);
-        const __m128i q4_3 = _mm_or_si128(_mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q4bits1, 1), 4), m4), q4h_3);
-
-        const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
-
-        __m128i q8s_0 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_0, 0));
-        __m128i q8s_1 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_0, 1));
-        __m128i q8s_2 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_1, 0));
-        __m128i q8s_3 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_1, 1));
-
-        __m128i p16_0 = _mm_maddubs_epi16(q4_0, _mm256_extractf128_si256(q8_0, 0));
-        __m128i p16_1 = _mm_maddubs_epi16(q4_1, _mm256_extractf128_si256(q8_0, 1));
-        __m128i p16_2 = _mm_maddubs_epi16(q4_2, _mm256_extractf128_si256(q8_1, 0));
-        __m128i p16_3 = _mm_maddubs_epi16(q4_3, _mm256_extractf128_si256(q8_1, 1));
-
-        p16_0 = _mm_sub_epi16(p16_0, q8s_0);
-        p16_1 = _mm_sub_epi16(p16_1, q8s_1);
-        p16_2 = _mm_sub_epi16(p16_2, q8s_2);
-        p16_3 = _mm_sub_epi16(p16_3, q8s_3);
-
-        p16_0 = _mm_madd_epi16(_mm_cvtepi8_epi16(scale_0), p16_0);
-        p16_1 = _mm_madd_epi16(_mm_cvtepi8_epi16(_mm_unpackhi_epi64(scale_0, scale_0)), p16_1);
-        p16_2 = _mm_madd_epi16(_mm_cvtepi8_epi16(scale_1), p16_2);
-        p16_3 = _mm_madd_epi16(_mm_cvtepi8_epi16(_mm_unpackhi_epi64(scale_1, scale_1)), p16_3);
-
-        sumi_0 = _mm_add_epi32(sumi_0, _mm_add_epi32(p16_0, p16_2));
-        sumi_1 = _mm_add_epi32(sumi_1, _mm_add_epi32(p16_1, p16_3));
-
-        acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(MM256_SET_M128I(sumi_1, sumi_0))), acc);
-    }
-
-    *s = hsum_float_8(acc);
-
-#elif defined __riscv_v_intrinsic
-
-    float sumf = 0;
-
-    for (int i = 0; i < nb; ++i) {
-
-        const float d_all = GGML_FP16_TO_FP32(x[i].d);
-
-        const uint8_t * restrict q6 = x[i].ql;
-        const uint8_t * restrict qh = x[i].qh;
-        const int8_t  * restrict q8 = y[i].qs;
-
-        const int8_t * restrict scale = x[i].scales;
-
-        int32_t isum = 0;
-
-        size_t vl = 16;
-
-        vint32m1_t vzero = __riscv_vmv_v_x_i32m1(0, 1);
-
-        // load Q6
-        vuint8mf2_t q6_0 = __riscv_vle8_v_u8mf2(q6, vl);
-        vuint8mf2_t q6_1 = __riscv_vle8_v_u8mf2(q6+16, vl);
-
-        // load qh
-        vuint8mf2_t qh_x = __riscv_vle8_v_u8mf2(qh, vl);
-
-        vuint8mf2_t qh0 = __riscv_vsll_vx_u8mf2(__riscv_vand_vx_u8mf2(qh_x, 0x3, vl), 0x4, vl);
-        qh_x = __riscv_vsrl_vx_u8mf2(qh_x, 0x2, vl);
-        vuint8mf2_t qh1 = __riscv_vsll_vx_u8mf2(__riscv_vand_vx_u8mf2(qh_x, 0x3, vl), 0x4, vl);
-        qh_x = __riscv_vsrl_vx_u8mf2(qh_x, 0x2, vl);
-        vuint8mf2_t qh2 = __riscv_vsll_vx_u8mf2(__riscv_vand_vx_u8mf2(qh_x, 0x3, vl), 0x4, vl);
-        qh_x = __riscv_vsrl_vx_u8mf2(qh_x, 0x2, vl);
-        vuint8mf2_t qh3 = __riscv_vsll_vx_u8mf2(__riscv_vand_vx_u8mf2(qh_x, 0x3, vl), 0x4, vl);
-
-        vuint8mf2_t q6h_0 = __riscv_vor_vv_u8mf2(__riscv_vand_vx_u8mf2(q6_0, 0xF, vl), qh0, vl);
-        vuint8mf2_t q6h_1 = __riscv_vor_vv_u8mf2(__riscv_vand_vx_u8mf2(q6_1, 0xF, vl), qh1, vl);
-        vuint8mf2_t q6h_2 = __riscv_vor_vv_u8mf2(__riscv_vsrl_vx_u8mf2(q6_0, 0x4, vl), qh2, vl);
-        vuint8mf2_t q6h_3 = __riscv_vor_vv_u8mf2(__riscv_vsrl_vx_u8mf2(q6_1, 0x4, vl), qh3, vl);
-
-        vint8mf2_t q6v_0 = __riscv_vsub_vx_i8mf2(__riscv_vreinterpret_v_u8mf2_i8mf2(q6h_0), 32, vl);
-        vint8mf2_t q6v_1 = __riscv_vsub_vx_i8mf2(__riscv_vreinterpret_v_u8mf2_i8mf2(q6h_1), 32, vl);
-        vint8mf2_t q6v_2 = __riscv_vsub_vx_i8mf2(__riscv_vreinterpret_v_u8mf2_i8mf2(q6h_2), 32, vl);
-        vint8mf2_t q6v_3 = __riscv_vsub_vx_i8mf2(__riscv_vreinterpret_v_u8mf2_i8mf2(q6h_3), 32, vl);
-
-        // load Q8 and take product
-        vint16m1_t p0 = __riscv_vwmul_vv_i16m1(q6v_0, __riscv_vle8_v_i8mf2(q8, vl), vl);
-        vint16m1_t p1 = __riscv_vwmul_vv_i16m1(q6v_1, __riscv_vle8_v_i8mf2(q8+16, vl), vl);
-        vint16m1_t p2 = __riscv_vwmul_vv_i16m1(q6v_2, __riscv_vle8_v_i8mf2(q8+32, vl), vl);
-        vint16m1_t p3 = __riscv_vwmul_vv_i16m1(q6v_3, __riscv_vle8_v_i8mf2(q8+48, vl), vl);
-
-        vint32m1_t vs_0 = __riscv_vwredsum_vs_i16m1_i32m1(p0, vzero, vl);
-        vint32m1_t vs_1 = __riscv_vwredsum_vs_i16m1_i32m1(p1, vzero, vl);
-        vint32m1_t vs_2 = __riscv_vwredsum_vs_i16m1_i32m1(p2, vzero, vl);
-        vint32m1_t vs_3 = __riscv_vwredsum_vs_i16m1_i32m1(p3, vzero, vl);
-
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_0) * scale[0];
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_1) * scale[1];
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_2) * scale[2];
-        isum += __riscv_vmv_x_s_i32m1_i32(vs_3) * scale[3];
-
-        sumf += isum * d_all * y[i].d;
-
-    }
-
-    *s = sumf;
-
-#elif defined(__POWER9_VECTOR__)
-    const vector signed char lowMask = vec_splats((signed char)0xF);
-    const vector unsigned char v2 = vec_splats((unsigned char)0x2);
-    const vector unsigned char v3 = vec_splats((unsigned char)0x3);
-    const vector unsigned char v4 = vec_splats((unsigned char)0x4);
-    const vector unsigned char v6 = vec_splats((unsigned char)0x6);
-    const vector signed char off = vec_splats((signed char)0x20);
-
-    vector float vsumf0 = vec_splats(0.0f);
-    vector float vsumf1 = vec_splats(0.0f);
-    vector float vsumf2 = vec_splats(0.0f);
-    vector float vsumf3 = vec_splats(0.0f);
-
-#pragma GCC unroll 2
-    for (int i = 0; i < nb; ++i) {
-        __builtin_prefetch(x[i].ql, 0, 1);
-        __builtin_prefetch(x[i].qh, 0, 1);
-        __builtin_prefetch(y[i].qs, 0, 1);
-
-        vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
-        vector float vyd = vec_splats(y[i].d);
-        vector float vd= vec_mul(vxd, vyd);
-
-        vector signed char qxs0 = (vector signed char)vec_xl( 0, x[i].ql);
-        vector signed char qxs1 = (vector signed char)vec_xl(16, x[i].ql);
-        vector signed char qxs00 = vec_and(qxs0, lowMask);
-        vector signed char qxs01 = vec_sr(qxs0, v4);
-        vector signed char qxs10 = vec_and(qxs1, lowMask);
-        vector signed char qxs11 = vec_sr(qxs1, v4);
-
-        vector signed char qxhs0 = (vector signed char)vec_xl( 0, x[i].qh);
-
-        vector signed char qxh00 = vec_sl(vec_and((vector signed char)v3, qxhs0), v4);
-        vector signed char qxh01 = vec_sl(vec_and((vector signed char)v3, vec_sr(qxhs0, v4)), v4);
-        vector signed char qxh10 = vec_sl(vec_and((vector signed char)v3, vec_sr(qxhs0, v2)), v4);
-        vector signed char qxh11 = vec_sl(vec_and((vector signed char)v3, vec_sr(qxhs0, v6)), v4);
-
-        vector signed char q6x00 = vec_sub(vec_or(qxh00, qxs00), off);
-        vector signed char q6x01 = vec_sub(vec_or(qxh01, qxs01), off);
-        vector signed char q6x10 = vec_sub(vec_or(qxh10, qxs10), off);
-        vector signed char q6x11 = vec_sub(vec_or(qxh11, qxs11), off);
-
-        vector signed char q8y00 = vec_xl( 0, y[i].qs);
-        vector signed char q8y10 = vec_xl(16, y[i].qs);
-        vector signed char q8y01 = vec_xl(32, y[i].qs);
-        vector signed char q8y11 = vec_xl(48, y[i].qs);
-
-        vector signed short qv00 = vec_add(vec_mule(q6x00, q8y00), vec_mulo(q6x00, q8y00));
-        vector signed short qv10 = vec_add(vec_mule(q6x10, q8y10), vec_mulo(q6x10, q8y10));
-        vector signed short qv01 = vec_add(vec_mule(q6x01, q8y01), vec_mulo(q6x01, q8y01));
-        vector signed short qv11 = vec_add(vec_mule(q6x11, q8y11), vec_mulo(q6x11, q8y11));
-
-        vector signed short vs = (vector signed short)vec_unpackh(vec_xl_len(x[i].scales, 4));
-        vector signed short vs0 = vec_splat(vs, 0);
-        vector signed short vs1 = vec_splat(vs, 1);
-        vector signed short vs2 = vec_splat(vs, 2);
-        vector signed short vs3 = vec_splat(vs, 3);
-
-        vector signed int vsumi0 = vec_add(vec_mule(qv00, vs0), vec_mulo(qv00, vs0));
-        vector signed int vsumi1 = vec_add(vec_mule(qv10, vs1), vec_mulo(qv10, vs1));
-        vector signed int vsumi2 = vec_add(vec_mule(qv01, vs2), vec_mulo(qv01, vs2));
-        vector signed int vsumi3 = vec_add(vec_mule(qv11, vs3), vec_mulo(qv11, vs3));
-
-        vsumf0 = vec_madd(vec_ctf(vsumi0, 0), vd, vsumf0);
-        vsumf1 = vec_madd(vec_ctf(vsumi1, 0), vd, vsumf1);
-        vsumf2 = vec_madd(vec_ctf(vsumi2, 0), vd, vsumf2);
-        vsumf3 = vec_madd(vec_ctf(vsumi3, 0), vd, vsumf3);
-    }
-
-    vsumf0 = vec_add(vsumf0, vsumf2);
-    vsumf1 = vec_add(vsumf1, vsumf3);
-
-    vsumf0 = vec_add(vsumf0, vsumf1);
-
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 4));
-    vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
-
-    *s = vec_extract(vsumf0, 0);
-
-#else
-
-    int8_t  aux8[QK_K];
-    int16_t aux16[8];
-    float   sums [8];
-    int32_t aux32[8];
-    memset(sums, 0, 8*sizeof(float));
-
-    float sumf = 0;
-    for (int i = 0; i < nb; ++i) {
-        const uint8_t * restrict q4 = x[i].ql;
-        const uint8_t * restrict qh = x[i].qh;
-        const  int8_t * restrict q8 = y[i].qs;
-        memset(aux32, 0, 8*sizeof(int32_t));
-        int8_t * restrict a = aux8;
-        for (int l = 0; l < 16; ++l) {
-            a[l+ 0] = (int8_t)((q4[l+ 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
-            a[l+16] = (int8_t)((q4[l+16] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
-            a[l+32] = (int8_t)((q4[l+ 0] >>  4) | (((qh[l] >> 4) & 3) << 4)) - 32;
-            a[l+48] = (int8_t)((q4[l+16] >>  4) | (((qh[l] >> 6) & 3) << 4)) - 32;
-        }
-        int is = 0;
-        for (int j = 0; j < QK_K/16; ++j) {
-            int scale = x[i].scales[is++];
-            for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
-            for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
-            q8 += 8; a += 8;
-            for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
-            for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
-            q8 += 8; a += 8;
-        }
-        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
-        for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
-    }
-    for (int l = 0; l < 8; ++l) sumf += sums[l];
-    *s = sumf;
-#endif
-}
-
-#endif
-
-#if defined (__AVX2__) || defined (__ARM_NEON) || defined (__POWER9_VECTOR__)
+#if defined (__AVX2__) || defined (__ARM_NEON) || defined (__POWER9_VECTOR__) || defined(__loongarch_asx)
 static const int8_t keven_signs_q2xs[1024] = {
      1,  1,  1,  1,  1,  1,  1,  1, -1,  1,  1,  1,  1,  1,  1, -1,  1, -1,  1,  1,  1,  1,  1, -1, -1, -1,  1,  1,  1,  1,  1,  1,
      1,  1, -1,  1,  1,  1,  1, -1, -1,  1, -1,  1,  1,  1,  1,  1,  1, -1, -1,  1,  1,  1,  1,  1, -1, -1, -1,  1,  1,  1,  1, -1,
@@ -9921,6 +8959,49 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * restrict s, size_t bs, const void
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = 0.125f * vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+
+    const uint64_t * signs64 = (const uint64_t *)keven_signs_q2xs;
+
+    uint32_t aux32[4];
+    const uint8_t * aux8 = (const uint8_t *)aux32;
+
+    __m256 accumf = (__m256)__lasx_xvldi(0);
+    for (int i = 0; i < nb; ++i) {
+        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
+        const uint16_t * restrict q2 = x[i].qs;
+        const int8_t   * restrict q8 = y[i].qs;
+        __m256i sumi1 = __lasx_xvldi(0);
+        __m256i sumi2 = __lasx_xvldi(0);
+        for (int ib32 = 0; ib32 < QK_K/32; ib32 += 2) {
+            const __m256i q8_1 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            memcpy(aux32, q2, 4*sizeof(uint32_t)); q2 += 8;
+
+            const __m256i q2_1 = lasx_set_d(iq2xxs_grid[aux8[ 3]], iq2xxs_grid[aux8[ 2]], iq2xxs_grid[aux8[1]], iq2xxs_grid[aux8[0]]);
+            const __m256i q2_2 = lasx_set_d(iq2xxs_grid[aux8[11]], iq2xxs_grid[aux8[10]], iq2xxs_grid[aux8[9]], iq2xxs_grid[aux8[8]]);
+            const __m256i s2_1 = lasx_set_d(signs64[(aux32[1] >> 21) & 127], signs64[(aux32[1] >> 14) & 127],
+                                                   signs64[(aux32[1] >>  7) & 127], signs64[(aux32[1] >>  0) & 127]);
+            const __m256i s2_2 = lasx_set_d(signs64[(aux32[3] >> 21) & 127], signs64[(aux32[3] >> 14) & 127],
+                                                   signs64[(aux32[3] >>  7) & 127], signs64[(aux32[3] >>  0) & 127]);
+            const __m256i q8s_1 = __lasx_xvsigncov_b(s2_1, q8_1);
+            const __m256i q8s_2 = __lasx_xvsigncov_b(s2_2, q8_2);
+            const __m256i dot1  = lasx_maddubs_h(q2_1, q8s_1);
+            const __m256i dot2  = lasx_maddubs_h(q2_2, q8s_2);
+            const uint16_t ls1 = aux32[1] >> 28;
+            const uint16_t ls2 = aux32[3] >> 28;
+            const __m256i p1 = lasx_madd_h(dot1, __lasx_xvreplgr2vr_h(2*ls1+1));
+            const __m256i p2 = lasx_madd_h(dot2, __lasx_xvreplgr2vr_h(2*ls2+1));
+            sumi1 = __lasx_xvadd_w(sumi1, p1);
+            sumi2 = __lasx_xvadd_w(sumi2, p2);
+        }
+
+        accumf = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(__lasx_xvadd_w(sumi1, sumi2)), accumf);
+    }
+
+    *s = 0.125f * hsum_float_8(accumf);
+
 #else
 
     uint32_t aux32[2];
@@ -10039,64 +9120,6 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * restrict s, size_t bs, const void *
     const __m256i block_sign_shuffle_1 = _mm256_loadu_si256((const __m256i*)block_sign_shuffle_mask_1);
     const __m256i block_sign_shuffle_2 = _mm256_loadu_si256((const __m256i*)block_sign_shuffle_mask_2);
 
-#if QK_K == 64
-    static const uint8_t k_bit_helper[16] = {
-        0x00, 0x80, 0x80, 0x00, 0x80, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00, 0x80, 0x00, 0x80, 0x80, 0x00,
-    };
-    const __m128i bit_helper = _mm_loadu_si128((const __m128i*)k_bit_helper);
-    const __m128i m511 = _mm_set1_epi16(511);
-    typedef union {
-        __m128i vec_index;
-        uint16_t index[8];
-    } index_t;
-
-    index_t idx;
-    __m256 accumf = _mm256_setzero_ps();
-    for (int i = 0; i < nb; ++i) {
-        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
-        const __m128i q2_data = _mm_loadu_si128((const __m128i*)x[i].qs);
-        idx.vec_index = _mm_and_si128(q2_data, m511);
-
-        const __m128i partial_sign_bits = _mm_srli_epi16(q2_data, 9);
-        const __m128i partial_sign_bits_upper = _mm_srli_epi16(q2_data, 13);
-        const __m128i partial_sign_bits_for_counting = _mm_xor_si128(partial_sign_bits, partial_sign_bits_upper);
-
-        const __m128i odd_bits = _mm_shuffle_epi8(bit_helper, partial_sign_bits_for_counting);
-        const __m128i full_sign_bits = _mm_or_si128(partial_sign_bits, odd_bits);
-        const __m256i full_signs = MM256_SET_M128I(full_sign_bits, full_sign_bits);
-
-        const __m256i q8_1 = _mm256_loadu_si256((const __m256i *)y[i].qs);
-        const __m256i q8_2 = _mm256_loadu_si256((const __m256i *)(y[i].qs+32));
-
-        const __m256i q2_1 = _mm256_set_epi64x(iq2xs_grid[idx.index[3]], iq2xs_grid[idx.index[2]],
-                                               iq2xs_grid[idx.index[1]], iq2xs_grid[idx.index[0]]);
-        const __m256i q2_2 = _mm256_set_epi64x(iq2xs_grid[idx.index[7]], iq2xs_grid[idx.index[6]],
-                                               iq2xs_grid[idx.index[5]], iq2xs_grid[idx.index[4]]);
-
-        __m256i signs;
-        signs = _mm256_shuffle_epi8(full_signs, block_sign_shuffle_1);
-        signs = _mm256_cmpeq_epi8(_mm256_and_si256(signs, bit_selector_mask), bit_selector_mask);
-        const __m256i q8s_1 = _mm256_sign_epi8(q8_1, _mm256_or_si256(signs, mone));
-
-        signs = _mm256_shuffle_epi8(full_signs, block_sign_shuffle_2);
-        signs = _mm256_cmpeq_epi8(_mm256_and_si256(signs, bit_selector_mask), bit_selector_mask);
-        const __m256i q8s_2 = _mm256_sign_epi8(q8_2, _mm256_or_si256(signs, mone));
-
-        const __m256i dot1  = _mm256_maddubs_epi16(q2_1, q8s_1);
-        const __m256i dot2  = _mm256_maddubs_epi16(q2_2, q8s_2);
-
-        const __m256i sc1 = MM256_SET_M128I(_mm_set1_epi16(2*(x[i].scales[0] >> 4)+1), _mm_set1_epi16(2*(x[i].scales[0] & 0xf)+1));
-        const __m256i sc2 = MM256_SET_M128I(_mm_set1_epi16(2*(x[i].scales[1] >> 4)+1), _mm_set1_epi16(2*(x[i].scales[1] & 0xf)+1));
-
-        const __m256i sum = _mm256_add_epi32(_mm256_madd_epi16(sc1, dot1), _mm256_madd_epi16(sc2, dot2));
-
-        accumf = _mm256_fmadd_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(sum), accumf);
-
-    }
-
-    *s = 0.125f * hsum_float_8(accumf);
-#else
-
     static const uint8_t k_bit_helper[32] = {
         0x00, 0x80, 0x80, 0x00, 0x80, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00, 0x80, 0x00, 0x80, 0x80, 0x00,
         0x00, 0x80, 0x80, 0x00, 0x80, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00, 0x80, 0x00, 0x80, 0x80, 0x00,
@@ -10194,8 +9217,123 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * restrict s, size_t bs, const void *
     }
 
     *s = 0.125f * hsum_float_8(accumf);
-#endif
+#elif defined(__loongarch_asx)
 
+    const __m256i mone = __lasx_xvreplgr2vr_b(1);
+    static const char block_sign_shuffle_mask_1[32] = {
+        0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x02,
+        0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x06, 0x06, 0x06, 0x06, 0x06, 0x06, 0x06, 0x06,
+    };
+    static const char block_sign_shuffle_mask_2[32] = {
+        0x08, 0x08, 0x08, 0x08, 0x08, 0x08, 0x08, 0x08, 0x0a, 0x0a, 0x0a, 0x0a, 0x0a, 0x0a, 0x0a, 0x0a,
+        0x0c, 0x0c, 0x0c, 0x0c, 0x0c, 0x0c, 0x0c, 0x0c, 0x0e, 0x0e, 0x0e, 0x0e, 0x0e, 0x0e, 0x0e, 0x0e,
+    };
+    static const uint8_t bit_selector_mask_bytes[32] = {
+        0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80, 0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80,
+        0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80, 0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80,
+    };
+
+    const __m256i bit_selector_mask = __lasx_xvld((const __m256i*)bit_selector_mask_bytes, 0);
+    const __m256i block_sign_shuffle_1 = __lasx_xvld((const __m256i*)block_sign_shuffle_mask_1, 0);
+    const __m256i block_sign_shuffle_2 = __lasx_xvld((const __m256i*)block_sign_shuffle_mask_2, 0);
+
+    static const uint8_t k_bit_helper[32] = {
+        0x00, 0x80, 0x80, 0x00, 0x80, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00, 0x80, 0x00, 0x80, 0x80, 0x00,
+        0x00, 0x80, 0x80, 0x00, 0x80, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00, 0x80, 0x00, 0x80, 0x80, 0x00,
+    };
+    const __m256i bit_helper = __lasx_xvld((const __m256i*)k_bit_helper, 0);
+    const __m256i m511 = __lasx_xvreplgr2vr_h(511);
+    const __m128i m4 = __lsx_vreplgr2vr_b(0xf);
+    const __m128i m1 = __lsx_vreplgr2vr_b(1);
+
+    uint64_t aux64;
+
+    // somewhat hacky, but gives a significant boost in performance
+    __m256i aux_gindex;
+    const uint16_t * gindex = (const uint16_t *)&aux_gindex;
+
+    __m256 accumf = (__m256)__lasx_xvldi(0);
+    for (int i = 0; i < nb; ++i) {
+        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
+        const uint16_t * restrict q2 = x[i].qs;
+        const int8_t   * restrict q8 = y[i].qs;
+
+        memcpy(&aux64, x[i].scales, 8);
+        __m128i stmp = __lsx_vreplgr2vr_d(aux64);
+        stmp = __lsx_vilvl_b( __lsx_vand_v(__lsx_vsrli_h(stmp, 4), m4), __lsx_vand_v(stmp, m4));
+        const __m128i scales = __lsx_vadd_b(__lsx_vslli_h(stmp, 1), m1);
+
+        __m256i sumi1 = __lasx_xvldi(0);
+        __m256i sumi2 = __lasx_xvldi(0);
+        for (int ib32 = 0; ib32 < QK_K/32; ib32 += 4) {
+
+            const __m256i q2_data = __lasx_xvld((const __m256i*)q2, 0);  q2 += 16;
+            aux_gindex = __lasx_xvand_v(q2_data, m511);
+
+            const __m256i partial_sign_bits = __lasx_xvsrli_h(q2_data, 9);
+            const __m256i partial_sign_bits_upper = __lasx_xvsrli_h(q2_data, 13);
+            const __m256i partial_sign_bits_for_counting = __lasx_xvxor_v(partial_sign_bits, partial_sign_bits_upper);
+
+            const __m256i odd_bits = lasx_shuffle_b(bit_helper, partial_sign_bits_for_counting);
+            const __m256i full_sign_bits = __lasx_xvor_v(partial_sign_bits, odd_bits);
+
+            const __m256i q8_1 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8_3 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8_4 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+
+            const __m256i q2_1 = lasx_set_d(iq2xs_grid[gindex[ 3]], iq2xs_grid[gindex[ 2]],
+                                                   iq2xs_grid[gindex[ 1]], iq2xs_grid[gindex[ 0]]);
+            const __m256i q2_2 = lasx_set_d(iq2xs_grid[gindex[ 7]], iq2xs_grid[gindex[ 6]],
+                                                   iq2xs_grid[gindex[ 5]], iq2xs_grid[gindex[ 4]]);
+            const __m256i q2_3 = lasx_set_d(iq2xs_grid[gindex[11]], iq2xs_grid[gindex[10]],
+                                                   iq2xs_grid[gindex[ 9]], iq2xs_grid[gindex[ 8]]);
+            const __m256i q2_4 = lasx_set_d(iq2xs_grid[gindex[15]], iq2xs_grid[gindex[14]],
+                                                   iq2xs_grid[gindex[13]], iq2xs_grid[gindex[12]]);
+
+            const __m128i full_signs_l = lasx_extracti128(full_sign_bits, 0);
+            const __m128i full_signs_h = lasx_extracti128(full_sign_bits, 1);
+            const __m256i full_signs_1 = lasx_insertf128(full_signs_l, full_signs_l);
+            const __m256i full_signs_2 = lasx_insertf128(full_signs_h, full_signs_h);
+
+            __m256i signs;
+            signs = lasx_shuffle_b(full_signs_1, block_sign_shuffle_1);
+            signs = __lasx_xvseq_b(__lasx_xvand_v(signs, bit_selector_mask), bit_selector_mask);
+            const __m256i q8s_1 = __lasx_xvsigncov_b(__lasx_xvor_v(signs, mone), q8_1);
+
+            signs = lasx_shuffle_b(full_signs_1, block_sign_shuffle_2);
+            signs = __lasx_xvseq_b(__lasx_xvand_v(signs, bit_selector_mask), bit_selector_mask);
+            const __m256i q8s_2 = __lasx_xvsigncov_b(__lasx_xvor_v(signs, mone), q8_2);
+
+            signs = lasx_shuffle_b(full_signs_2, block_sign_shuffle_1);
+            signs = __lasx_xvseq_b(__lasx_xvand_v(signs, bit_selector_mask), bit_selector_mask);
+            const __m256i q8s_3 = __lasx_xvsigncov_b(__lasx_xvor_v(signs, mone), q8_3);
+
+            signs = lasx_shuffle_b(full_signs_2, block_sign_shuffle_2);
+            signs = __lasx_xvseq_b(__lasx_xvand_v(signs, bit_selector_mask), bit_selector_mask);
+            const __m256i q8s_4 = __lasx_xvsigncov_b(__lasx_xvor_v(signs, mone), q8_4);
+
+            const __m256i dot1  = lasx_maddubs_h(q2_1, q8s_1);
+            const __m256i dot2  = lasx_maddubs_h(q2_2, q8s_2);
+            const __m256i dot3  = lasx_maddubs_h(q2_3, q8s_3);
+            const __m256i dot4  = lasx_maddubs_h(q2_4, q8s_4);
+
+            const __m256i sc1 = lasx_ext8_16(lsx_shuffle_b(scales, get_scale_shuffle(ib32+0)));
+            const __m256i sc2 = lasx_ext8_16(lsx_shuffle_b(scales, get_scale_shuffle(ib32+1)));
+            const __m256i sc3 = lasx_ext8_16(lsx_shuffle_b(scales, get_scale_shuffle(ib32+2)));
+            const __m256i sc4 = lasx_ext8_16(lsx_shuffle_b(scales, get_scale_shuffle(ib32+3)));
+
+            sumi1 = __lasx_xvadd_w(sumi1, lasx_madd_h(dot1, sc1));
+            sumi2 = __lasx_xvadd_w(sumi2, lasx_madd_h(dot2, sc2));
+            sumi1 = __lasx_xvadd_w(sumi1, lasx_madd_h(dot3, sc3));
+            sumi2 = __lasx_xvadd_w(sumi2, lasx_madd_h(dot4, sc4));
+        }
+
+        accumf = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(__lasx_xvadd_w(sumi1, sumi2)), accumf);
+
+    }
+
+    *s = 0.125f * hsum_float_8(accumf);
 #elif defined(__POWER9_VECTOR__)
     vector float vsumf0 = vec_splats(0.0f);
     vector float vsumf1 = vec_splats(0.0f);
@@ -10612,6 +9750,81 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * restrict s, size_t bs, const void *
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = 0.125f * vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+
+   static const uint8_t k_mask1[32] = {0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x01, 0x01, 0x01, 0x01, 0x01, 0x01, 0x01,
+                                       0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x03, 0x03, 0x03, 0x03, 0x03, 0x03, 0x03, 0x03
+   };
+
+    static const uint8_t k_mask2[32] = {0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80, 0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80,
+                                        0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80, 0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80,
+    };
+
+
+    const __m128i m4 = __lsx_vreplgr2vr_b(0xf);
+    const __m128i m1 = __lsx_vreplgr2vr_b(1);
+
+    const __m256i mask1 = __lasx_xvld((const __m256i*)k_mask1, 0);
+    const __m256i mask2 = __lasx_xvld((const __m256i*)k_mask2, 0);
+    uint64_t aux64;
+
+    __m256 accumf = (__m256)__lasx_xvldi(0);
+    for (int i = 0; i < nb; ++i) {
+        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
+        const uint8_t * restrict qs = x[i].qs;
+        const uint8_t * restrict qh = x[i].qh;
+        const uint16_t * restrict signs = (const uint16_t *)(x[i].qs + QK_K/8);
+        const int8_t  * restrict q8 = y[i].qs;
+
+        __m128i tmp1;
+        memcpy(&aux64, x[i].scales, 8);
+        tmp1 = __lsx_vinsgr2vr_d(tmp1, aux64, 0);
+        tmp1 = __lsx_vinsgr2vr_d(tmp1, aux64 >> 4, 1);
+        const __m128i scales8 = __lsx_vadd_b(__lsx_vslli_h(__lsx_vand_v(tmp1, m4), 1), m1);
+        const __m256i scales16 = lasx_ext8_16(scales8); // 0 2 4 6 8 10 12 14 1 3 5 7 9 11 13 15
+
+        __m256i sumi1 = __lasx_xvldi(0);
+        __m256i sumi2 = __lasx_xvldi(0);
+        for (int ib32 = 0; ib32 < QK_K/32; ib32 += 2) {
+            const __m256i q8_1 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q2_1 = lasx_set_d(iq2s_grid[qs[3] | ((qh[ib32+0] << 2) & 0x300)],
+                                                   iq2s_grid[qs[2] | ((qh[ib32+0] << 4) & 0x300)],
+                                                   iq2s_grid[qs[1] | ((qh[ib32+0] << 6) & 0x300)],
+                                                   iq2s_grid[qs[0] | ((qh[ib32+0] << 8) & 0x300)]);
+            const __m256i q2_2 = lasx_set_d(iq2s_grid[qs[7] | ((qh[ib32+1] << 2) & 0x300)],
+                                                   iq2s_grid[qs[6] | ((qh[ib32+1] << 4) & 0x300)],
+                                                   iq2s_grid[qs[5] | ((qh[ib32+1] << 6) & 0x300)],
+                                                   iq2s_grid[qs[4] | ((qh[ib32+1] << 8) & 0x300)]);
+            qs += 8;
+
+            __m256i aux256 = __lasx_xvreplgr2vr_w(signs[0] | ((uint32_t) signs[1] << 16));
+            aux256 = __lasx_xvand_v(lasx_shuffle_b(aux256,mask1), mask2);
+            const __m256i s2_1 = __lasx_xvseq_b(aux256, mask2);
+            const __m256i q8s_1 = __lasx_xvsub_b(__lasx_xvxor_v(s2_1, q8_1), s2_1);
+
+            aux256 = __lasx_xvreplgr2vr_w(signs[2] | ((uint32_t) signs[3] << 16));
+            aux256 = __lasx_xvand_v(lasx_shuffle_b(aux256,mask1), mask2);
+            const __m256i s2_2 = __lasx_xvseq_b(aux256, mask2);
+            const __m256i q8s_2 = __lasx_xvsub_b(__lasx_xvxor_v(s2_2, q8_2), s2_2);
+
+            signs += 4;
+
+            const __m256i dot1  = lasx_maddubs_h(q2_1, q8s_1); // blocks 2*ib32+0, 2*ib32+1
+            const __m256i dot2  = lasx_maddubs_h(q2_2, q8s_2); // blocks 2*ib32+2, 2*ib32+3
+
+            const __m256i p1 = lasx_madd_h(dot1, lasx_shuffle_b(scales16, get_scale_shuffle_k4(ib32+0)));
+            const __m256i p2 = lasx_madd_h(dot2, lasx_shuffle_b(scales16, get_scale_shuffle_k4(ib32+1)));
+            sumi1 = __lasx_xvadd_w(sumi1, p1);
+            sumi2 = __lasx_xvadd_w(sumi2, p2);
+        }
+
+        accumf = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(__lasx_xvadd_w(sumi1, sumi2)), accumf);
+    }
+
+    *s = 0.125f * hsum_float_8(accumf);
+
 #else
 
     float sumf = 0;
@@ -10851,6 +10064,54 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * restrict s, size_t bs, const void
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = 0.25f * vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+
+    const uint64_t * signs64 = (const uint64_t *)keven_signs_q2xs;
+
+    uint32_t aux32[2];
+
+    __m256 accumf = (__m256)__lasx_xvldi(0);
+    for (int i = 0; i < nb; ++i) {
+        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
+        const uint8_t * restrict q3 = x[i].qs;
+        const uint8_t * restrict gas = x[i].qs + QK_K/4;
+        const int8_t  * restrict q8 = y[i].qs;
+        __m256i sumi1 = __lasx_xvldi(0);
+        __m256i sumi2 = __lasx_xvldi(0);
+        for (int ib32 = 0; ib32 < QK_K/32; ib32 += 2) {
+            const __m256i q8_1 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q2_1 = lasx_set_w(iq3xxs_grid[q3[7]], iq3xxs_grid[q3[6]], iq3xxs_grid[q3[5]], iq3xxs_grid[q3[4]],
+                                                iq3xxs_grid[q3[3]], iq3xxs_grid[q3[2]], iq3xxs_grid[q3[1]], iq3xxs_grid[q3[0]]);
+            q3 += 8;
+            const __m256i q2_2 = lasx_set_w(iq3xxs_grid[q3[7]], iq3xxs_grid[q3[6]], iq3xxs_grid[q3[5]], iq3xxs_grid[q3[4]],
+                                                iq3xxs_grid[q3[3]], iq3xxs_grid[q3[2]], iq3xxs_grid[q3[1]], iq3xxs_grid[q3[0]]);
+            q3 += 8;
+            memcpy(aux32, gas, 8); gas += 8;
+
+            const __m256i s2_1 = lasx_set_d(signs64[(aux32[0] >> 21) & 127], signs64[(aux32[0] >> 14) & 127],
+                                                   signs64[(aux32[0] >>  7) & 127], signs64[(aux32[0] >>  0) & 127]);
+            const __m256i s2_2 = lasx_set_d(signs64[(aux32[1] >> 21) & 127], signs64[(aux32[1] >> 14) & 127],
+                                                   signs64[(aux32[1] >>  7) & 127], signs64[(aux32[1] >>  0) & 127]);
+            const __m256i q8s_1 = __lasx_xvsigncov_b(s2_1, q8_1);
+            const __m256i q8s_2 = __lasx_xvsigncov_b(s2_2, q8_2);
+            const __m256i dot1  = lasx_maddubs_h(q2_1, q8s_1);
+            const __m256i dot2  = lasx_maddubs_h(q2_2, q8s_2);
+            const uint16_t ls1 = aux32[0] >> 28;
+            const uint16_t ls2 = aux32[1] >> 28;
+
+            const __m256i p1 = lasx_madd_h(dot1, __lasx_xvreplgr2vr_h(2*ls1+1));
+            const __m256i p2 = lasx_madd_h(dot2, __lasx_xvreplgr2vr_h(2*ls2+1));
+            sumi1 = __lasx_xvadd_w(sumi1, p1);
+            sumi2 = __lasx_xvadd_w(sumi2, p2);
+        }
+
+        accumf = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(__lasx_xvadd_w(sumi1, sumi2)), accumf);
+    }
+
+    *s = 0.25f * hsum_float_8(accumf);
+
 #else
 
     uint32_t aux32;
@@ -10925,10 +10186,8 @@ void ggml_vec_dot_iq3_s_q8_K (int n, float * restrict s, size_t bs, const void *
     ggml_int8x16x4_t q8b;
     vec_index_t idx;
 
-#if QK_K == 256
     uint32_t scales32[2];
     const uint8_t * scales8 = (const uint8_t *)scales32;
-#endif
 
     float sumf = 0;
     for (int i = 0; i < nb; ++i) {
@@ -10938,11 +10197,9 @@ void ggml_vec_dot_iq3_s_q8_K (int n, float * restrict s, size_t bs, const void *
         const uint16_t * restrict signs = (const uint16_t *)x[i].signs;
         const int8_t   * restrict q8 = y[i].qs;
 
-#if QK_K == 256
         memcpy(scales32, x[i].scales, 4);
         scales32[1] = (((scales32[0] >> 4) & 0x0f0f0f0f) << 1) | 0x01010101;
         scales32[0] = ((scales32[0] & 0x0f0f0f0f) << 1) | 0x01010101;
-#endif
 
         int sumi1 = 0, sumi2 = 0;
         for (int ib32 = 0; ib32 < QK_K/32; ib32 += 2) {
@@ -10983,13 +10240,9 @@ void ggml_vec_dot_iq3_s_q8_K (int n, float * restrict s, size_t bs, const void *
 
             const int32x4_t p1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), q3s.val[0], q8b.val[0]), q3s.val[1], q8b.val[1]);
             const int32x4_t p2 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), q3s.val[2], q8b.val[2]), q3s.val[3], q8b.val[3]);
-#if QK_K == 256
+
             sumi1 += vaddvq_s32(p1) * scales8[ib32/2+0];
             sumi2 += vaddvq_s32(p2) * scales8[ib32/2+4];
-#else
-            sumi1 += vaddvq_s32(p1) * (1 + 2*(x[i].scales[ib32/2] & 0xf));
-            sumi2 += vaddvq_s32(p2) * (1 + 2*(x[i].scales[ib32/2] >>  4));
-#endif
         }
         sumf += d*(sumi1 + sumi2);
     }
@@ -11196,6 +10449,89 @@ void ggml_vec_dot_iq3_s_q8_K (int n, float * restrict s, size_t bs, const void *
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+
+   static const uint8_t k_mask1[32] = {0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x01, 0x01, 0x01, 0x01, 0x01, 0x01, 0x01,
+                                       0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x02, 0x03, 0x03, 0x03, 0x03, 0x03, 0x03, 0x03, 0x03
+   };
+
+    static const uint8_t k_mask2[32] = {0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80, 0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80,
+                                        0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80, 0x01, 0x02, 0x04, 0x08, 0x10, 0x20, 0x40, 0x80,
+    };
+
+    const __m256i mask1 = __lasx_xvld((const __m256i*)k_mask1, 0);
+    const __m256i mask2 = __lasx_xvld((const __m256i*)k_mask2, 0);
+
+    __m256i idx_shift = lasx_set_w(1, 2, 3, 4, 5, 6, 7, 8);
+    const __m256i idx_mask  = __lasx_xvreplgr2vr_w(256);
+
+    typedef union {
+        __m256i  vec[2];
+        uint32_t index[16];
+    } index_t;
+
+    index_t idx;
+
+    __m256 accumf = (__m256)__lasx_xvldi(0);
+    for (int i = 0; i < nb; ++i) {
+        const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
+        const uint8_t * restrict qs = x[i].qs;
+        const uint8_t * restrict qh = x[i].qh;
+        const uint16_t * restrict signs = (const uint16_t *)x[i].signs;
+        const int8_t  * restrict q8 = y[i].qs;
+        __m256i sumi1 = __lasx_xvldi(0);
+        __m256i sumi2 = __lasx_xvldi(0);
+        for (int ib32 = 0; ib32 < QK_K/32; ib32 += 2) {
+            const __m256i q8_1 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8_2 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i idx_l = lasx_extu8_16(__lsx_vld(qs, 0)); qs += 16;
+            idx.vec[0] = __lasx_xvreplgr2vr_w(qh[ib32+0]);
+            idx.vec[1] = __lasx_xvreplgr2vr_w(qh[ib32+1]);
+            idx.vec[0] = __lasx_xvand_v(__lasx_xvsll_w(idx.vec[0], idx_shift), idx_mask);
+            idx.vec[1] = __lasx_xvand_v(__lasx_xvsll_w(idx.vec[1], idx_shift), idx_mask);
+            idx.vec[0] = __lasx_xvor_v(idx.vec[0], lasx_ext16_32(lasx_extracti128(idx_l, 0)));
+            idx.vec[1] = __lasx_xvor_v(idx.vec[1], lasx_ext16_32(lasx_extracti128(idx_l, 1)));
+
+            // At leat on my CPU (Ryzen 7950X), using _mm256_i32gather_epi32 is slower than _mm256_set_epi32. Strange.
+            //const __m256i q2_1 = _mm256_i32gather_epi32((const int *)iq3s_grid, idx.vec[0], 4);
+            //const __m256i q2_2 = _mm256_i32gather_epi32((const int *)iq3s_grid, idx.vec[1], 4);
+            const __m256i q2_1 = lasx_set_w(
+                    iq3s_grid[idx.index[7]], iq3s_grid[idx.index[6]], iq3s_grid[idx.index[5]], iq3s_grid[idx.index[4]],
+                    iq3s_grid[idx.index[3]], iq3s_grid[idx.index[2]], iq3s_grid[idx.index[1]], iq3s_grid[idx.index[0]]
+            );
+            const __m256i q2_2 = lasx_set_w(
+                    iq3s_grid[idx.index[15]], iq3s_grid[idx.index[14]], iq3s_grid[idx.index[13]], iq3s_grid[idx.index[12]],
+                    iq3s_grid[idx.index[11]], iq3s_grid[idx.index[10]], iq3s_grid[idx.index[ 9]], iq3s_grid[idx.index[ 8]]
+            );
+
+            __m256i aux256 = __lasx_xvreplgr2vr_w(signs[0] | (signs[1] << 16));
+            aux256 = __lasx_xvand_v(lasx_shuffle_b(aux256,mask1), mask2);
+            const __m256i s2_1 = __lasx_xvseq_b(aux256, mask2);
+            const __m256i q8s_1 = __lasx_xvsub_b(__lasx_xvxor_v(s2_1, q8_1), s2_1);
+
+            aux256 = __lasx_xvreplgr2vr_w(signs[2] | (signs[3] << 16));
+            aux256 = __lasx_xvand_v(lasx_shuffle_b(aux256,mask1), mask2);
+            const __m256i s2_2 = __lasx_xvseq_b(aux256, mask2);
+            const __m256i q8s_2 = __lasx_xvsub_b(__lasx_xvxor_v(s2_2, q8_2), s2_2);
+
+            signs += 4;
+
+            const __m256i dot1 = lasx_maddubs_h(q2_1, q8s_1);
+            const __m256i dot2  = lasx_maddubs_h(q2_2, q8s_2);
+            const uint16_t ls1 = x[i].scales[ib32/2] & 0xf;
+            const uint16_t ls2 = x[i].scales[ib32/2] >>  4;
+            const __m256i p1 = lasx_madd_h(dot1, __lasx_xvreplgr2vr_h(2*ls1+1));
+            const __m256i p2 = lasx_madd_h(dot2, __lasx_xvreplgr2vr_h(2*ls2+1));
+            sumi1 = __lasx_xvadd_w(sumi1, p1);
+            sumi2 = __lasx_xvadd_w(sumi2, p2);
+        }
+
+        accumf = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(__lasx_xvadd_w(sumi1, sumi2)), accumf);
+    }
+
+    *s = hsum_float_8(accumf);
+
 #else
 
     float sumf = 0.f;
@@ -11243,12 +10579,22 @@ void ggml_vec_dot_iq3_s_q8_K (int n, float * restrict s, size_t bs, const void *
 }
 
 
-#ifdef __AVX2__
+#if defined(__AVX2__)
 static inline __m256i mul_add_epi8(const __m256i x, const __m256i y) {
     const __m256i ax = _mm256_sign_epi8(x, x);
     const __m256i sy = _mm256_sign_epi8(y, x);
     return _mm256_maddubs_epi16(ax, sy);
 }
+#elif defined(__loongarch_asx)
+static inline __m256i mul_add_epi8(const __m256i x, const __m256i y) {
+    const __m256i ax = __lasx_xvsigncov_b(x, x);
+    const __m256i sy = __lasx_xvsigncov_b(x, y);
+    __m256i tmp1, tmp2, tmp3;
+    tmp1 = __lasx_xvmulwev_h_bu_b(ax, sy);
+    tmp2 = __lasx_xvmulwod_h_bu_b(ax, sy);
+    tmp3 = __lasx_xvadd_h(tmp1, tmp2);
+    return __lasx_xvsat_h(tmp3, 15);
+}
 #endif
 
 void ggml_vec_dot_iq1_s_q8_K  (int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) {
@@ -11457,6 +10803,62 @@ void ggml_vec_dot_iq1_s_q8_K  (int n, float * restrict s, size_t bs, const void
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+
+    __m256 accum = (__m256)__lasx_xvldi(0);
+    float accum1 = 0;
+    for (int i = 0; i < nb; ++i) {
+
+        const int8_t   * q8 = y[i].qs;
+        const uint8_t  * qs = x[i].qs;
+        const uint16_t * qh = x[i].qh;
+
+        __m256i sumi = __lasx_xvldi(0);
+        int sumi1 = 0;
+        for (int ib = 0; ib < QK_K/32; ib += 2) {
+            __m256i q1b_1 = __lasx_xvinsgr2vr_d(q1b_1, iq1s_grid[qs[0] | ((qh[ib+0] << 8) & 0x700)], 0);
+            q1b_1 = __lasx_xvinsgr2vr_d(q1b_1, iq1s_grid[qs[1] | ((qh[ib+0] << 5) & 0x700)], 1);
+            q1b_1 = __lasx_xvinsgr2vr_d(q1b_1, iq1s_grid[qs[2] | ((qh[ib+0] << 2) & 0x700)], 2);
+            q1b_1 = __lasx_xvinsgr2vr_d(q1b_1, iq1s_grid[qs[3] | ((qh[ib+0] >> 1) & 0x700)], 3);
+
+            __m256i q1b_2 = __lasx_xvinsgr2vr_d(q1b_2, iq1s_grid[qs[4] | ((qh[ib+1] << 8) & 0x700)], 0);
+            q1b_2 = __lasx_xvinsgr2vr_d(q1b_2, iq1s_grid[qs[5] | ((qh[ib+1] << 5) & 0x700)], 1);
+            q1b_2 = __lasx_xvinsgr2vr_d(q1b_2, iq1s_grid[qs[6] | ((qh[ib+1] << 2) & 0x700)], 2);
+            q1b_2 = __lasx_xvinsgr2vr_d(q1b_2, iq1s_grid[qs[7] | ((qh[ib+1] >> 1) & 0x700)], 3);
+
+            qs += 8;
+            const __m256i q8b_1 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+            const __m256i q8b_2 = __lasx_xvld((const __m256i*)q8, 0); q8 += 32;
+
+            const __m256i dot1 = mul_add_epi8(q1b_1, q8b_1);
+            const __m256i dot2 = mul_add_epi8(q1b_2, q8b_2);
+            const int16_t ls1 = 2*((qh[ib+0] >> 12) & 7) + 1;
+            const int16_t ls2 = 2*((qh[ib+1] >> 12) & 7) + 1;
+
+            __m256i tmp1, tmp5, tmp6;
+            tmp1 = __lasx_xvreplgr2vr_h(ls1);
+            tmp5 = __lasx_xvmulwev_w_h(dot1, tmp1);
+            tmp6 = __lasx_xvmulwod_w_h(dot1, tmp1);
+            const __m256i p1 = __lasx_xvadd_w(tmp5, tmp6);
+
+            tmp1 = __lasx_xvreplgr2vr_h(ls2);
+            tmp5 = __lasx_xvmulwev_w_h(dot2, tmp1);
+            tmp6 = __lasx_xvmulwod_w_h(dot2, tmp1);
+            const __m256i p2 = __lasx_xvadd_w(tmp5, tmp6);
+
+            sumi = __lasx_xvadd_w(sumi, __lasx_xvadd_w(p1, p2));
+            sumi1 += (y[i].bsums[2*ib+0] + y[i].bsums[2*ib+1]) * (qh[ib+0] & 0x8000 ? -1 : 1) * ls1
+                   + (y[i].bsums[2*ib+2] + y[i].bsums[2*ib+3]) * (qh[ib+1] & 0x8000 ? -1 : 1) * ls2;
+        }
+
+        const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
+        accum = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(sumi), accum);
+        accum1 += d * sumi1;
+    }
+
+    *s = hsum_float_8(accum) + IQ1S_DELTA * accum1;
+
 #else
 
     float sumf = 0;
@@ -11504,17 +10906,10 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
 
     const int nb = n / QK_K;
 
-#if QK_K != 64
     iq1m_scale_t scale;
-#endif
 
 #if defined __ARM_NEON
-
-#if QK_K == 64
-    const int32x4_t mask  = vdupq_n_s32(0xf);
-#else
     const int32x4_t mask  = vdupq_n_s32(0x7);
-#endif
     const int32x4_t mone  = vdupq_n_s32(1);
     const int32x4_t mzero = vdupq_n_s32(0);
 
@@ -11538,9 +10933,7 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
         const uint8_t  * qh = x[i].qh;
         const uint16_t * sc = (const uint16_t *)x[i].scales;
 
-#if QK_K != 64
         scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
-#endif
 
         int32x4_t sumi1 = mzero;
         int32x4_t sumi2 = mzero;
@@ -11569,11 +10962,8 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
             const int32x4_t p4 = vpaddq_s32(ggml_vdotq_s32(mzero, deltas.val[aux8[2]], q8b.val[2]), ggml_vdotq_s32(mzero, deltas.val[aux8[3]], q8b.val[3]));
             const int32x4_t p34 = vpaddq_s32(p3, p4);
 
-#if QK_K == 64
-            int32x4_t scales_4 = ggml_vld1q_u32(sc[0] >> 0, sc[0] >> 4, sc[0] >> 8, sc[0] >> 12);
-#else
             int32x4_t scales_4 = ggml_vld1q_u32(sc[ib/2] >> 0, sc[ib/2] >> 3, sc[ib/2] >> 6, sc[ib/2] >> 9);
-#endif
+
             scales_4 = vaddq_s32(vshlq_n_s32(vandq_s32(scales_4, mask), 1), mone);
 
             sumi1 = vmlaq_s32(sumi1, scales_4, p12);
@@ -11583,22 +10973,14 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
 
         }
 
-#if QK_K == 64
-        sumf += y[i].d * GGML_FP16_TO_FP32(x[i].d) * (vaddvq_s32(sumi1) + IQ1M_DELTA * vaddvq_s32(sumi2));
-#else
         sumf += y[i].d * GGML_FP16_TO_FP32(scale.f16) * (vaddvq_s32(sumi1) + IQ1M_DELTA * vaddvq_s32(sumi2));
-#endif
     }
 
     *s = sumf;
 
 #elif defined __AVX2__
 
-#if QK_K == 64
-    const __m256i mask = _mm256_set1_epi16(0xf);
-#else
     const __m256i mask = _mm256_set1_epi16(0x7);
-#endif
     const __m256i mone = _mm256_set1_epi16(1);
 
     __m256 accum1 = _mm256_setzero_ps();
@@ -11610,9 +10992,7 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
         const uint8_t  * qh = x[i].qh;
         const uint16_t * sc = (const uint16_t *)x[i].scales;
 
-#if QK_K != 64
         scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
-#endif
 
         __m256i sumi1 = _mm256_setzero_si256();
         __m256i sumi2 = _mm256_setzero_si256();
@@ -11642,13 +11022,10 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
 
             const __m256i dot3 = mul_add_epi8(delta1, q8b_1);
             const __m256i dot4 = mul_add_epi8(delta2, q8b_2);
-#if QK_K == 64
-            __m256i scale1 = MM256_SET_M128I(_mm_set1_epi16(sc[0] >>  4), _mm_set1_epi16(sc[0] >> 0));
-            __m256i scale2 = MM256_SET_M128I(_mm_set1_epi16(sc[0] >> 12), _mm_set1_epi16(sc[0] >> 8));
-#else
+
             __m256i scale1 = MM256_SET_M128I(_mm_set1_epi16(sc[ib/2] >> 3), _mm_set1_epi16(sc[ib/2] >> 0));
             __m256i scale2 = MM256_SET_M128I(_mm_set1_epi16(sc[ib/2] >> 9), _mm_set1_epi16(sc[ib/2] >> 6));
-#endif
+
             scale1 = _mm256_add_epi16(_mm256_slli_epi16(_mm256_and_si256(scale1, mask), 1), mone);
             scale2 = _mm256_add_epi16(_mm256_slli_epi16(_mm256_and_si256(scale2, mask), 1), mone);
             const __m256i p1 = _mm256_madd_epi16(dot1, scale1);
@@ -11662,14 +11039,10 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
             qs += 8; qh += 4;
         }
 
-#if QK_K == 64
-        const __m256 d = _mm256_set1_ps(y[i].d * GGML_FP16_TO_FP32(x[i].d));
-#else
         const __m256 d = _mm256_set1_ps(y[i].d * GGML_FP16_TO_FP32(scale.f16));
-#endif
+
         accum1 = _mm256_fmadd_ps(d, _mm256_cvtepi32_ps(sumi1), accum1);
         accum2 = _mm256_fmadd_ps(d, _mm256_cvtepi32_ps(sumi2), accum2);
-
     }
 
     *s = hsum_float_8(accum1) + IQ1M_DELTA * hsum_float_8(accum2);
@@ -11686,9 +11059,7 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
         const uint8_t  * qh = x[i].qh;
         const uint16_t * sc = (const uint16_t *)x[i].scales;
 
-#if QK_K != 64
         scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
-#endif
 
         int sumi1 = 0, sumi2 = 0;
         for (int ib = 0; ib < QK_K/32; ++ib) {
@@ -11708,24 +11079,17 @@ void ggml_vec_dot_iq1_m_q8_K  (int n, float * restrict s, size_t bs, const void
                 sum1[l/2] += lsum1;
                 sum2[l/2] += lsum2*delta[l];
             }
-#if QK_K == 64
-            const int ls1 = 2*((sc[0] >> (8*(ib%2)+0)) & 0xf) + 1;
-            const int ls2 = 2*((sc[0] >> (8*(ib%2)+4)) & 0xf) + 1;
-#else
+
             const int ls1 = 2*((sc[ib/2] >> (6*(ib%2)+0)) & 0x7) + 1;
             const int ls2 = 2*((sc[ib/2] >> (6*(ib%2)+3)) & 0x7) + 1;
-#endif
+
             sumi1 += sum1[0] * ls1 + sum1[1] * ls2;
             sumi2 += sum2[0] * ls1 + sum2[1] * ls2;
             qs += 4;
             qh += 2;
         }
 
-#if QK_K == 64
-        sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
-#else
         sumf += GGML_FP16_TO_FP32(scale.f16) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
-#endif
     }
 
     *s = sumf;
@@ -11858,6 +11222,39 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * restrict s, size_t bs, const void *
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined (__loongarch_asx)
+
+    const __m128i values128 = __lsx_vld((const __m128i*)kvalues_iq4nl, 0);
+    const __m128i m4b  = __lsx_vreplgr2vr_b(0x0f);
+    const __m256i mone = __lasx_xvreplgr2vr_h(1);
+
+    __m256 accum1 = (__m256)__lasx_xvldi(0);
+    __m256 accum2 = (__m256)__lasx_xvldi(0);
+    for (int ib = 0; ib < nb; ib += 2) {
+        const __m128i q4bits_1 = __lsx_vld((const __m128i*)x[0].qs, 0);
+        const __m128i q4bits_2 = __lsx_vld((const __m128i*)x[1].qs, 0);
+        const __m256i q8b_1 = __lasx_xvld((const __m256i *)y[0].qs, 0);
+        const __m256i q8b_2 = __lasx_xvld((const __m256i *)y[1].qs, 0);
+        const __m256i q4b_1 = lasx_insertf128(lsx_shuffle_b(values128, __lsx_vand_v(__lsx_vsrli_h(q4bits_1, 4), m4b)),
+                                              lsx_shuffle_b(values128, __lsx_vand_v(q4bits_1, m4b)));
+        const __m256i q4b_2 = lasx_insertf128(lsx_shuffle_b(values128, __lsx_vand_v(__lsx_vsrli_h(q4bits_2, 4), m4b)),
+                                              lsx_shuffle_b(values128, __lsx_vand_v(q4bits_2, m4b)));
+        const __m256i p16_1 = mul_add_epi8(q4b_1, q8b_1);
+        const __m256i p16_2 = mul_add_epi8(q4b_2, q8b_2);
+        const __m256i p_1 = lasx_madd_h(p16_1, mone);
+        const __m256i p_2 = lasx_madd_h(p16_2, mone);
+        accum1 = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(y[0].d)*GGML_FP16_TO_FP32(x[0].d)),
+                __lasx_xvffint_s_w(p_1), accum1);
+        accum2 = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(y[1].d)*GGML_FP16_TO_FP32(x[1].d)),
+                __lasx_xvffint_s_w(p_2), accum2);
+
+        y += 2;
+        x += 2;
+    }
+
+    *s = hsum_float_8(__lasx_xvfadd_s(accum1, accum2));
+
 #else
     float sumf = 0;
     for (int ib = 0; ib < nb; ++ib) {
@@ -11880,9 +11277,6 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * restrict s, size_t bs, const void *
     UNUSED(by);
     UNUSED(bs);
     assert(n % QK_K == 0);
-#if QK_K == 64
-    ggml_vec_dot_iq4_nl_q8_0(n, s, bs, vx, bx, vy, by, nrc);
-#else
 
     const block_iq4_xs * restrict x = vx;
     const block_q8_K   * restrict y = vy;
@@ -12068,6 +11462,80 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * restrict s, size_t bs, const void *
     vsumf0 = vec_add(vsumf0, vec_sld(vsumf0, vsumf0, 8));
 
     *s = vec_extract(vsumf0, 0);
+
+#elif defined(__loongarch_asx)
+
+    const __m128i values128 = __lsx_vld((const __m128i*)kvalues_iq4nl, 0);
+    const __m128i m4b  = __lsx_vreplgr2vr_b(0x0f);
+
+    __m256 accum = (__m256)__lasx_xvldi(0);
+    __m256i tmp1;
+    __m128i tmp0, tmp2, tmp3, tmp4, mask_8f, mask;
+
+    mask_8f = __lsx_vreplgr2vr_b(0x8f);
+    for (int ibl = 0; ibl < nb; ++ibl) {
+        const uint8_t * qs = x[ibl].qs;
+        const int8_t  * q8 = y[ibl].qs;
+        uint16_t sh = x[ibl].scales_h;
+        __m256i sumi1 = __lasx_xvldi(0);
+        __m256i sumi2 = __lasx_xvldi(0);
+        __m128i zero = __lsx_vldi(0);
+        for (int ib = 0; ib < QK_K/32; ib += 2) {
+            const __m128i q4bits_1 = __lsx_vld((const __m128i*)qs, 0);  qs += 16;
+            const __m128i q4bits_2 = __lsx_vld((const __m128i*)qs, 0);  qs += 16;
+            const __m256i q8b_1 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            const __m256i q8b_2 = __lasx_xvld((const __m256i *)q8, 0); q8 += 32;
+            tmp2 = __lsx_vand_v(__lsx_vand_v(__lsx_vsrli_h(q4bits_1, 4), m4b), mask_8f);
+            tmp0 = __lsx_vori_b(tmp2, 0x10);
+            mask = __lsx_vsle_b(zero, tmp2);
+            tmp3 = __lsx_vand_v(tmp0, mask);
+            tmp3 = __lsx_vshuf_b(values128, zero, tmp3);
+
+            tmp2 = __lsx_vand_v(__lsx_vand_v(q4bits_1, m4b), mask_8f);
+            tmp0 = __lsx_vori_b(tmp2, 0x10);
+            mask = __lsx_vsle_b(zero, tmp2);
+            tmp4 = __lsx_vand_v(tmp0, mask);
+            tmp4 = __lsx_vshuf_b(values128, zero, tmp4);
+
+            const __m256i q4b_1 = lasx_insertf128(tmp3, tmp4);
+
+            tmp2 = __lsx_vand_v(__lsx_vand_v(__lsx_vsrli_h(q4bits_2, 4), m4b), mask_8f);
+            tmp0 = __lsx_vori_b(tmp2, 0x10);
+            mask = __lsx_vsle_b(zero, tmp2);
+            tmp3 = __lsx_vand_v(tmp0, mask);
+            tmp3 = __lsx_vshuf_b(values128, zero, tmp3);
+
+            tmp2 = __lsx_vand_v(__lsx_vand_v(q4bits_2, m4b), mask_8f);
+            tmp0 = __lsx_vori_b(tmp2, 0x10);
+            mask = __lsx_vsle_b(zero, tmp2);
+            tmp4 = __lsx_vand_v(tmp0, mask);
+            tmp4 = __lsx_vshuf_b(values128, zero, tmp4);
+
+            const __m256i q4b_2 = lasx_insertf128(tmp3, tmp4);
+
+            const __m256i p16_1 = mul_add_epi8(q4b_1, q8b_1);
+            const __m256i p16_2 = mul_add_epi8(q4b_2, q8b_2);
+            const int16_t ls1 = ((x[ibl].scales_l[ib/2] & 0xf) | ((sh << 4) & 0x30)) - 32;
+            const int16_t ls2 = ((x[ibl].scales_l[ib/2] >>  4) | ((sh << 2) & 0x30)) - 32;
+            sh >>= 4;
+            __m256i tmp5, tmp6;
+            tmp1 = __lasx_xvreplgr2vr_h(ls1);
+            tmp5 = __lasx_xvmulwev_w_h(p16_1, tmp1);
+            tmp6 = __lasx_xvmulwod_w_h(p16_1, tmp1);
+            const __m256i p_1 = __lasx_xvadd_w(tmp5, tmp6);
+            tmp1 = __lasx_xvreplgr2vr_h(ls2);
+            tmp5 = __lasx_xvmulwev_w_h(p16_2, tmp1);
+            tmp6 = __lasx_xvmulwod_w_h(p16_2, tmp1);
+            const __m256i p_2 = __lasx_xvadd_w(tmp5, tmp6);
+            sumi1 = __lasx_xvadd_w(p_1, sumi1);
+            sumi2 = __lasx_xvadd_w(p_2, sumi2);
+        }
+        accum = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[ibl].d)*y[ibl].d),
+                __lasx_xvffint_s_w(__lasx_xvadd_w(sumi1, sumi2)), accum);
+    }
+
+    *s = hsum_float_8(accum);
+
 #else
     float sumf = 0;
     for (int ibl = 0; ibl < nb; ++ibl) {
@@ -12101,7 +11569,6 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * restrict s, size_t bs, const void *
     }
     *s = sumf;
 #endif
-#endif
 }
 
 // ================================ IQ2 quantization =============================================
@@ -12599,7 +12066,7 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
             }
             float max = xval[0];
             for (int i = 1; i < 32; ++i) max = MAX(max, xval[i]);
-            if (!max) {
+            if (max < GROUP_MAX_EPS) {
                 scales[ib] = 0;
                 memset(L, 0, 32);
                 continue;
@@ -12677,7 +12144,7 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
                     printf("\n");
                     GGML_ASSERT(false);
                 }
-                q2[2*ib+0] |= (grid_index << 8*k);
+                q2[2*ib+0] |= ((uint32_t) grid_index << 8*k);
                 q2[2*ib+1] |= (block_signs[k] << 7*k);
             }
             GGML_ASSERT(scale >= 0);
@@ -12775,7 +12242,7 @@ static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict v
             }
             float max = xval[0];
             for (int i = 1; i < 16; ++i) max = MAX(max, xval[i]);
-            if (!max) {
+            if (max < GROUP_MAX_EPS) {
                 scales[ib] = 0;
                 memset(L, 0, 16);
                 continue;
@@ -13216,7 +12683,7 @@ static void quantize_row_iq3_xxs_impl(int grid_size, const float * restrict x, v
             }
             float max = xval[0];
             for (int i = 1; i < 32; ++i) max = MAX(max, xval[i]);
-            if (!max) {
+            if (max < GROUP_MAX_EPS_IQ3_XXS) {
                 scales[ib] = 0;
                 memset(L, 0, 32);
                 continue;
@@ -13756,7 +13223,7 @@ static void quantize_row_iq1_s_impl(const float * restrict x, void * restrict vy
             for (int i = 0; i < block_size; ++i) weight[i] = qw[i] * sqrtf(sigma2 + xb[i]*xb[i]);
             float max = fabsf(xb[0]);
             for (int i = 1; i < block_size; ++i) max = MAX(max, fabsf(xb[i]));
-            if (!max) {
+            if (max < GROUP_MAX_EPS_IQ1_S) {
                 scales[ib] = 0;
                 memset(L, 1, block_size);
                 continue;
@@ -13919,10 +13386,6 @@ static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy
     const float * xx;
 
     for (int ibl = 0; ibl < nbl; ++ibl) {
-
-#if QK_K == 64
-        y[ibl].d = GGML_FP32_TO_FP16(0.f);
-#endif
         memset(y[ibl].qs, 0, QK_K/8);
         memset(y[ibl].qh, 0, QK_K/16);
         memset(y[ibl].scales, 0, QK_K/32);
@@ -13944,7 +13407,7 @@ static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy
             }
             float max = fabsf(xb[0]);
             for (int i = 1; i < block_size; ++i) max = MAX(max, fabsf(xb[i]));
-            if (!max) {
+            if (max < GROUP_MAX_EPS_IQ1_M) {
                 scales[ib] = 0;
                 memset(L, 1, block_size);
                 continue;
@@ -14097,22 +13560,13 @@ static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy
         }
 
         uint16_t * sc = (uint16_t *)y[ibl].scales;
-#if QK_K == 64
-        float d = max_scale/31;
-#else
         float d = max_scale/15;
-#endif
         float id = 1/d;
         float sumqx_f = 0, sumq2_f = 0;
         for (int ib = 0; ib < QK_K/block_size; ++ib) {
             int l = nearest_int(0.5f*(id*scales[ib+0]-1));
-#if QK_K == 64
-            l = MAX(0, MIN(15, l));
-            sc[ib/4] |= (l << 4*(ib%4));
-#else
             l = MAX(0, MIN(7, l));
             sc[ib/4] |= (l << 3*(ib%4));
-#endif
             y[ibl].qh[ib] |= masks[shifts[ib]];
             const float * xb = xbl + block_size*ib;
             if (quant_weights) {
@@ -14135,14 +13589,10 @@ static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy
         }
         if (sumq2_f > 0) d = sumqx_f/sumq2_f;
         s.f16 = GGML_FP32_TO_FP16(d*1.1125f); // 1.1125f is another fudge factor. Don't ask me why it is needed.
-#if QK_K == 64
-        y[ibl].d = s.f16;
-#else
         sc[0] |= ((s.u16 & 0x000f) << 12);
         sc[1] |= ((s.u16 & 0x00f0) <<  8);
         sc[2] |= ((s.u16 & 0x0f00) <<  4);
         sc[3] |= ((s.u16 & 0xf000) <<  0);
-#endif
     }
 }
 
@@ -14208,7 +13658,7 @@ static void quantize_row_iq4_nl_impl(const int super_block_size, const int block
                 amax = ax; max = xb[j];
             }
         }
-        if (!amax) {
+        if (amax < GROUP_MAX_EPS) {
             scales[ib] = 0;
             continue;
         }
@@ -14331,9 +13781,6 @@ void quantize_row_iq4_nl_reference(const float * restrict x, block_iq4_nl * rest
 }
 
 size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
-#if QK_K == 64
-    return quantize_iq4_nl(src, dst, nrow, n_per_row, quant_weights);
-#else
     GGML_ASSERT(n_per_row%QK_K == 0);
     int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
@@ -14351,7 +13798,6 @@ size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int64_t
         qrow += nblock*sizeof(block_iq4_xs);
     }
     return nrow * nblock * sizeof(block_iq4_xs);
-#endif
 }
 
 void quantize_row_iq4_xs(const float * restrict x, void * restrict vy, int64_t k) {
@@ -14429,7 +13875,7 @@ static void quantize_row_iq2_s_impl(const float * restrict x, void * restrict vy
             }
             float max = xval[0];
             for (int i = 1; i < 16; ++i) max = MAX(max, xval[i]);
-            if (!max) {
+            if (max < GROUP_MAX_EPS_IQ2_S) {
                 scales[ib] = 0;
                 continue;
             }
@@ -14763,19 +14209,11 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
             } break;
         case GGML_TYPE_Q4_K:
             {
-            #ifdef GGML_QKK_64
-                VALIDATE_ROW_DATA_DM_F16_IMPL(block_q4_K, data, nb, d[0], d[1]);
-            #else
                 VALIDATE_ROW_DATA_DM_F16_IMPL(block_q4_K, data, nb, d, dmin);
-            #endif
             } break;
         case GGML_TYPE_Q5_K:
             {
-            #ifdef GGML_QKK_64
-                VALIDATE_ROW_DATA_D_F16_IMPL(block_q5_K, data, nb);
-            #else
                 VALIDATE_ROW_DATA_DM_F16_IMPL(block_q5_K, data, nb, d, dmin);
-            #endif
             } break;
         case GGML_TYPE_Q6_K:
             {
@@ -14798,18 +14236,12 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
             {
                 const block_iq1_m * q = (const block_iq1_m *) data;
                 for (size_t i = 0; i < nb; ++i) {
-                #if QK_K == 64
-                    if (!validate_fp16(q[i].d, i)) {
-                        return false;
-                    }
-                #else
                     iq1m_scale_t scale;
                     const uint16_t * sc = (const uint16_t *)q[i].scales;
                     scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
                     if (!validate_fp16(scale.f16, i)) {
                         return false;
                     }
-                #endif
                 }
             } break;
         case GGML_TYPE_IQ2_XXS:
@@ -14834,12 +14266,9 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte
                 VALIDATE_ROW_DATA_D_F16_IMPL(block_iq3_s, data, nb);
             } break;
         case GGML_TYPE_IQ4_XS:
-        #if QK_K != 64
             {
                 VALIDATE_ROW_DATA_D_F16_IMPL(block_iq4_xs, data, nb);
             } break;
-        #endif
-        // with QK_K == 64, iq4_xs is iq4_nl
         case GGML_TYPE_IQ4_NL:
             {
                 VALIDATE_ROW_DATA_D_F16_IMPL(block_iq4_nl, data, nb);
diff --git a/ggml-rpc.cpp b/ggml-rpc.cpp
index 4a9bfa52d..cc1d3ace1 100644
--- a/ggml-rpc.cpp
+++ b/ggml-rpc.cpp
@@ -56,6 +56,7 @@ struct socket_t {
 };
 
 // ggml_tensor is serialized into rpc_tensor
+#pragma pack(push, 1)
 struct rpc_tensor {
     uint64_t id;
     uint32_t type;
@@ -71,6 +72,7 @@ struct rpc_tensor {
     uint64_t data;
     char name[GGML_MAX_NAME];
 };
+#pragma pack(pop)
 
 // RPC commands
 enum rpc_cmd {
@@ -340,23 +342,6 @@ static rpc_tensor serialize_tensor(const ggml_tensor * tensor) {
     return result;
 }
 
-static ggml_tensor * deserialize_tensor(struct ggml_context * ctx, const rpc_tensor * tensor) {
-    ggml_tensor * result = ggml_new_tensor_4d(ctx, (ggml_type) tensor->type,
-        tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3]);
-    for (uint32_t i = 0; i < GGML_MAX_DIMS; i++) {
-        result->nb[i] = tensor->nb[i];
-    }
-    result->buffer = reinterpret_cast<ggml_backend_buffer_t>(tensor->buffer);
-    result->op = (ggml_op) tensor->op;
-    for (uint32_t i = 0; i < GGML_MAX_OP_PARAMS / sizeof(int32_t); i++) {
-        result->op_params[i] = tensor->op_params[i];
-    }
-    result->flags = tensor->flags;
-    result->data = reinterpret_cast<void *>(tensor->data);
-    ggml_set_name(result, tensor->name);
-    return result;
-}
-
 GGML_CALL static void ggml_backend_rpc_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
     UNUSED(buffer);
     if (ggml_is_quantized(tensor->type)) {
@@ -465,13 +450,15 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_rpc_buffer_type_alloc_buffer
     memcpy(&remote_ptr, output.data(), sizeof(remote_ptr));
     size_t remote_size;
     memcpy(&remote_size, output.data() + sizeof(uint64_t), sizeof(remote_size));
-
-    ggml_backend_buffer_t buffer = ggml_backend_buffer_init(buft,
-        ggml_backend_rpc_buffer_interface,
-        new ggml_backend_rpc_buffer_context{buft_ctx->sock, {}, remote_ptr, "RPC"},
-        remote_size);
-
-    return buffer;
+    if (remote_ptr != 0) {
+        ggml_backend_buffer_t buffer = ggml_backend_buffer_init(buft,
+            ggml_backend_rpc_buffer_interface,
+            new ggml_backend_rpc_buffer_context{buft_ctx->sock, {}, remote_ptr, "RPC"},
+            remote_size);
+        return buffer;
+    } else {
+        return nullptr;
+    }
 }
 
 static size_t get_alignment(const std::shared_ptr<socket_t> & sock) {
@@ -658,7 +645,7 @@ GGML_CALL ggml_backend_t ggml_backend_rpc_init(const char * endpoint) {
         }
     }
 #endif
-    GGML_PRINT_DEBUG("Connecting to %s\n", endpoint);
+    fprintf(stderr, "Connecting to %s\n", endpoint);
     std::string host;
     int port;
     if (!parse_endpoint(endpoint, host, port)) {
@@ -731,22 +718,61 @@ GGML_API GGML_CALL void ggml_backend_rpc_get_device_memory(const char * endpoint
 
 // RPC server-side implementation
 
-static void rpc_alloc_buffer(ggml_backend_t backend, const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
+class rpc_server {
+public:
+    rpc_server(ggml_backend_t backend) : backend(backend) {}
+    ~rpc_server();
+
+    bool alloc_buffer(const std::vector<uint8_t> & input, std::vector<uint8_t> & output);
+    void get_alignment(std::vector<uint8_t> & output);
+    void get_max_size(std::vector<uint8_t> & output);
+    bool buffer_get_base(const std::vector<uint8_t> & input, std::vector<uint8_t> & output);
+    bool free_buffer(const std::vector<uint8_t> & input);
+    bool buffer_clear(const std::vector<uint8_t> & input);
+    bool set_tensor(const std::vector<uint8_t> & input);
+    bool get_tensor(const std::vector<uint8_t> & input, std::vector<uint8_t> & output);
+    bool copy_tensor(const std::vector<uint8_t> & input, std::vector<uint8_t> & output);
+    bool graph_compute(const std::vector<uint8_t> & input, std::vector<uint8_t> & output);
+
+private:
+    ggml_tensor * deserialize_tensor(struct ggml_context * ctx, const rpc_tensor * tensor);
+    ggml_tensor * create_node(uint64_t id,
+                              struct ggml_context * ctx,
+                              const std::unordered_map<uint64_t, const rpc_tensor*> & tensor_ptrs,
+                              std::unordered_map<uint64_t, struct ggml_tensor*> & tensor_map);
+
+
+    ggml_backend_t backend;
+    std::unordered_set<ggml_backend_buffer_t> buffers;
+};
+
+bool rpc_server::alloc_buffer(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
     // input serialization format: | size (8 bytes) |
+    if (input.size() != sizeof(uint64_t)) {
+        return false;
+    }
     uint64_t size;
     memcpy(&size, input.data(), sizeof(size));
     ggml_backend_buffer_type_t buft = ggml_backend_get_default_buffer_type(backend);
     ggml_backend_buffer_t buffer = ggml_backend_buft_alloc_buffer(buft, size);
-    uint64_t remote_ptr = reinterpret_cast<uint64_t>(buffer);
-    uint64_t remote_size = buffer->size;
-    GGML_PRINT_DEBUG("[%s] size: %" PRIu64 " -> remote_ptr: %" PRIx64 ", remote_size: %" PRIu64 "\n", __func__, size, remote_ptr, remote_size);
+    uint64_t remote_ptr = 0;
+    uint64_t remote_size = 0;
+    if (buffer != nullptr) {
+        remote_ptr = reinterpret_cast<uint64_t>(buffer);
+        remote_size = buffer->size;
+        GGML_PRINT_DEBUG("[%s] size: %" PRIu64 " -> remote_ptr: %" PRIx64 ", remote_size: %" PRIu64 "\n", __func__, size, remote_ptr, remote_size);
+        buffers.insert(buffer);
+    } else {
+        GGML_PRINT_DEBUG("[%s] size: %" PRIu64 " -> failed\n", __func__, size);
+    }
     // output serialization format: | remote_ptr (8 bytes) | remote_size (8 bytes) |
     output.resize(2*sizeof(uint64_t), 0);
     memcpy(output.data(), &remote_ptr, sizeof(remote_ptr));
     memcpy(output.data() + sizeof(uint64_t), &remote_size, sizeof(remote_size));
+    return true;
 }
 
-static void rpc_get_alignment(ggml_backend_t backend, std::vector<uint8_t> & output) {
+void rpc_server::get_alignment(std::vector<uint8_t> & output) {
     ggml_backend_buffer_type_t buft = ggml_backend_get_default_buffer_type(backend);
     size_t alignment = ggml_backend_buft_get_alignment(buft);
     GGML_PRINT_DEBUG("[%s] alignment: %lu\n", __func__, alignment);
@@ -755,7 +781,7 @@ static void rpc_get_alignment(ggml_backend_t backend, std::vector<uint8_t> & out
     memcpy(output.data(), &alignment, sizeof(alignment));
 }
 
-static void rpc_get_max_size(ggml_backend_t backend, std::vector<uint8_t> & output) {
+void rpc_server::get_max_size(std::vector<uint8_t> & output) {
     ggml_backend_buffer_type_t buft = ggml_backend_get_default_buffer_type(backend);
     size_t max_size = ggml_backend_buft_get_max_size(buft);
     GGML_PRINT_DEBUG("[%s] max_size: %lu\n", __func__, max_size);
@@ -764,41 +790,90 @@ static void rpc_get_max_size(ggml_backend_t backend, std::vector<uint8_t> & outp
     memcpy(output.data(), &max_size, sizeof(max_size));
 }
 
-static void rpc_buffer_get_base(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
+bool rpc_server::buffer_get_base(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
     // input serialization format: | remote_ptr (8 bytes) |
+    if (input.size() != sizeof(uint64_t)) {
+        return false;
+    }
     uint64_t remote_ptr;
     memcpy(&remote_ptr, input.data(), sizeof(remote_ptr));
     GGML_PRINT_DEBUG("[%s] remote_ptr: %" PRIx64 "\n", __func__, remote_ptr);
     ggml_backend_buffer_t buffer = reinterpret_cast<ggml_backend_buffer_t>(remote_ptr);
+    if (buffers.find(buffer) == buffers.end()) {
+        GGML_PRINT_DEBUG("[%s] buffer not found\n", __func__);
+        return false;
+    }
     void * base = ggml_backend_buffer_get_base(buffer);
     // output serialization format: | base_ptr (8 bytes) |
     uint64_t base_ptr = reinterpret_cast<uint64_t>(base);
     output.resize(sizeof(uint64_t), 0);
     memcpy(output.data(), &base_ptr, sizeof(base_ptr));
+    return true;
 }
 
-static void rpc_free_buffer(const std::vector<uint8_t> & input) {
+bool rpc_server::free_buffer(const std::vector<uint8_t> & input) {
     // input serialization format: | remote_ptr (8 bytes) |
+    if (input.size() != sizeof(uint64_t)) {
+        return false;
+    }
     uint64_t remote_ptr;
     memcpy(&remote_ptr, input.data(), sizeof(remote_ptr));
     GGML_PRINT_DEBUG("[%s] remote_ptr: %" PRIx64 "\n", __func__, remote_ptr);
     ggml_backend_buffer_t buffer = reinterpret_cast<ggml_backend_buffer_t>(remote_ptr);
+    if (buffers.find(buffer) == buffers.end()) {
+        GGML_PRINT_DEBUG("[%s] buffer not found\n", __func__);
+        return false;
+    }
     ggml_backend_buffer_free(buffer);
+    buffers.erase(buffer);
+    return true;
 }
 
-static void rpc_buffer_clear(const std::vector<uint8_t> & input) {
+bool rpc_server::buffer_clear(const std::vector<uint8_t> & input) {
     // input serialization format: | remote_ptr (8 bytes) | value (1 byte) |
+    if (input.size() != sizeof(uint64_t) + sizeof(uint8_t)) {
+        return false;
+    }
     uint64_t remote_ptr;
     memcpy(&remote_ptr, input.data(), sizeof(remote_ptr));
     uint8_t value;
     memcpy(&value, input.data() + sizeof(uint64_t), sizeof(value));
     GGML_PRINT_DEBUG("[%s] remote_ptr: %" PRIx64 ", value: %u\n", __func__, remote_ptr, value);
     ggml_backend_buffer_t buffer = reinterpret_cast<ggml_backend_buffer_t>(remote_ptr);
+    if (buffers.find(buffer) == buffers.end()) {
+        GGML_PRINT_DEBUG("[%s] buffer not found\n", __func__);
+        return false;
+    }
     ggml_backend_buffer_clear(buffer, value);
+    return true;
 }
 
-static void rpc_set_tensor(const std::vector<uint8_t> & input) {
+ggml_tensor * rpc_server::deserialize_tensor(struct ggml_context * ctx, const rpc_tensor * tensor) {
+    ggml_tensor * result = ggml_new_tensor_4d(ctx, (ggml_type) tensor->type,
+        tensor->ne[0], tensor->ne[1], tensor->ne[2], tensor->ne[3]);
+    for (uint32_t i = 0; i < GGML_MAX_DIMS; i++) {
+        result->nb[i] = tensor->nb[i];
+    }
+    result->buffer = reinterpret_cast<ggml_backend_buffer_t>(tensor->buffer);
+    if (result->buffer && buffers.find(result->buffer) == buffers.end()) {
+        return nullptr;
+    }
+    result->op = (ggml_op) tensor->op;
+    for (uint32_t i = 0; i < GGML_MAX_OP_PARAMS / sizeof(int32_t); i++) {
+        result->op_params[i] = tensor->op_params[i];
+    }
+    result->flags = tensor->flags;
+    result->data = reinterpret_cast<void *>(tensor->data);
+    ggml_set_name(result, tensor->name);
+    return result;
+}
+
+
+bool rpc_server::set_tensor(const std::vector<uint8_t> & input) {
     // serialization format: | rpc_tensor | offset (8 bytes) | data (size bytes) |
+    if (input.size() < sizeof(rpc_tensor) + sizeof(uint64_t)) {
+        return false;
+    }
     const rpc_tensor * in_tensor = (const rpc_tensor *)input.data();
     uint64_t offset;
     memcpy(&offset, input.data() + sizeof(rpc_tensor), sizeof(offset));
@@ -811,14 +886,23 @@ static void rpc_set_tensor(const std::vector<uint8_t> & input) {
     };
     struct ggml_context * ctx = ggml_init(params);
     ggml_tensor * tensor = deserialize_tensor(ctx, in_tensor);
+    if (tensor == nullptr) {
+        GGML_PRINT_DEBUG("[%s] error deserializing tensor\n", __func__);
+        ggml_free(ctx);
+        return false;
+    }
     GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %zu\n", __func__, (void*)tensor->buffer, tensor->data, offset, size);
     const void * data = input.data() + sizeof(rpc_tensor) + sizeof(offset);
     ggml_backend_tensor_set(tensor, data, offset, size);
     ggml_free(ctx);
+    return true;
 }
 
-static void rpc_get_tensor(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
+bool rpc_server::get_tensor(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
     // serialization format: | rpc_tensor | offset (8 bytes) | size (8 bytes) |
+    if (input.size() != sizeof(rpc_tensor) + 2*sizeof(uint64_t)) {
+        return false;
+    }
     const rpc_tensor * in_tensor = (const rpc_tensor *)input.data();
     uint64_t offset;
     memcpy(&offset, input.data() + sizeof(rpc_tensor), sizeof(offset));
@@ -832,15 +916,24 @@ static void rpc_get_tensor(const std::vector<uint8_t> & input, std::vector<uint8
     };
     struct ggml_context * ctx = ggml_init(params);
     ggml_tensor * tensor = deserialize_tensor(ctx, in_tensor);
+    if (tensor == nullptr) {
+        GGML_PRINT_DEBUG("[%s] error deserializing tensor\n", __func__);
+        ggml_free(ctx);
+        return false;
+    }
     GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %" PRIu64 "\n", __func__, (void*)tensor->buffer, tensor->data, offset, size);
     // output serialization format: | data (size bytes) |
     output.resize(size, 0);
     ggml_backend_tensor_get(tensor, output.data(), offset, size);
     ggml_free(ctx);
+    return true;
 }
 
-static void rpc_copy_tensor(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
+bool rpc_server::copy_tensor(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
     // serialization format: | rpc_tensor src | rpc_tensor dst |
+    if (input.size() != 2*sizeof(rpc_tensor)) {
+        return false;
+    }
     const rpc_tensor * rpc_src = (const rpc_tensor *)input.data();
     const rpc_tensor * rpc_dst = (const rpc_tensor *)(input.data() + sizeof(rpc_src));
 
@@ -852,18 +945,24 @@ static void rpc_copy_tensor(const std::vector<uint8_t> & input, std::vector<uint
     struct ggml_context * ctx = ggml_init(params);
     ggml_tensor * src = deserialize_tensor(ctx, rpc_src);
     ggml_tensor * dst = deserialize_tensor(ctx, rpc_dst);
+    if (src == nullptr || dst == nullptr) {
+        GGML_PRINT_DEBUG("[%s] error deserializing tensors\n", __func__);
+        ggml_free(ctx);
+        return false;
+    }
     GGML_PRINT_DEBUG("[%s] src->buffer: %p, dst->buffer: %p\n", __func__, (void*)src->buffer, (void*)dst->buffer);
     bool result = ggml_backend_buffer_copy_tensor(src, dst);
     // output serialization format: | result (1 byte) |
     output.resize(1, 0);
     output[0] = result;
     ggml_free(ctx);
+    return true;
 }
 
-static struct ggml_tensor * create_node(uint64_t id,
-                                        struct ggml_context * ctx,
-                                        const std::unordered_map<uint64_t, const rpc_tensor*> & tensor_ptrs,
-                                        std::unordered_map<uint64_t, struct ggml_tensor*> & tensor_map) {
+ggml_tensor * rpc_server::create_node(uint64_t id,
+                                      struct ggml_context * ctx,
+                                      const std::unordered_map<uint64_t, const rpc_tensor*> & tensor_ptrs,
+                                      std::unordered_map<uint64_t, struct ggml_tensor*> & tensor_map) {
     if (id == 0) {
         return nullptr;
     }
@@ -872,6 +971,9 @@ static struct ggml_tensor * create_node(uint64_t id,
     }
     const rpc_tensor * tensor = tensor_ptrs.at(id);
     struct ggml_tensor * result = deserialize_tensor(ctx, tensor);
+    if (result == nullptr) {
+        return nullptr;
+    }
     tensor_map[id] = result;
     for (int i = 0; i < GGML_MAX_SRC; i++) {
         result->src[i] = create_node(tensor->src[i], ctx, tensor_ptrs, tensor_map);
@@ -881,14 +983,23 @@ static struct ggml_tensor * create_node(uint64_t id,
     return result;
 }
 
-static void rpc_graph_compute(ggml_backend_t backend, const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
+bool rpc_server::graph_compute(const std::vector<uint8_t> & input, std::vector<uint8_t> & output) {
     // serialization format:
     // | n_nodes (4 bytes) | nodes (n_nodes * sizeof(uint64_t) | n_tensors (4 bytes) | tensors (n_tensors * sizeof(rpc_tensor)) |
+    if (input.size() < sizeof(uint32_t)) {
+        return false;
+    }
     uint32_t n_nodes;
     memcpy(&n_nodes, input.data(), sizeof(n_nodes));
+    if (input.size() < sizeof(uint32_t) + n_nodes*sizeof(uint64_t) + sizeof(uint32_t)) {
+        return false;
+    }
     const uint64_t * nodes = (const uint64_t *)(input.data() + sizeof(n_nodes));
     uint32_t n_tensors;
     memcpy(&n_tensors, input.data() + sizeof(n_nodes) + n_nodes*sizeof(uint64_t), sizeof(n_tensors));
+    if (input.size() < sizeof(uint32_t) + n_nodes*sizeof(uint64_t) + sizeof(uint32_t) + n_tensors*sizeof(rpc_tensor)) {
+        return false;
+    }
     const rpc_tensor * tensors = (const rpc_tensor *)(input.data() + sizeof(n_nodes) + n_nodes*sizeof(uint64_t) + sizeof(n_tensors));
     GGML_PRINT_DEBUG("[%s] n_nodes: %u, n_tensors: %u\n", __func__, n_nodes, n_tensors);
 
@@ -914,9 +1025,17 @@ static void rpc_graph_compute(ggml_backend_t backend, const std::vector<uint8_t>
     output.resize(1, 0);
     output[0] = status;
     ggml_free(ctx);
+    return true;
+}
+
+rpc_server::~rpc_server() {
+    for (auto buffer : buffers) {
+        ggml_backend_buffer_free(buffer);
+    }
 }
 
 static void rpc_serve_client(ggml_backend_t backend, sockfd_t sockfd, size_t free_mem, size_t total_mem) {
+    rpc_server server(backend);
     while (true) {
         uint8_t cmd;
         if (!recv_data(sockfd, &cmd, 1)) {
@@ -932,45 +1051,46 @@ static void rpc_serve_client(ggml_backend_t backend, sockfd_t sockfd, size_t fre
         if (!recv_data(sockfd, input.data(), input_size)) {
             break;
         }
+        bool ok = true;
         switch (cmd) {
             case ALLOC_BUFFER: {
-                rpc_alloc_buffer(backend, input, output);
+                ok = server.alloc_buffer(input, output);
                 break;
             }
             case GET_ALIGNMENT: {
-                rpc_get_alignment(backend, output);
+                server.get_alignment(output);
                 break;
             }
             case GET_MAX_SIZE: {
-                rpc_get_max_size(backend, output);
+                server.get_max_size(output);
                 break;
             }
             case BUFFER_GET_BASE: {
-                rpc_buffer_get_base(input, output);
+                ok = server.buffer_get_base(input, output);
                 break;
             }
             case FREE_BUFFER: {
-                rpc_free_buffer(input);
+                ok = server.free_buffer(input);
                 break;
             }
             case BUFFER_CLEAR: {
-                rpc_buffer_clear(input);
+                ok = server.buffer_clear(input);
                 break;
             }
             case SET_TENSOR: {
-                rpc_set_tensor(input);
+                ok = server.set_tensor(input);
                 break;
             }
             case GET_TENSOR: {
-                rpc_get_tensor(input, output);
+                ok = server.get_tensor(input, output);
                 break;
             }
             case COPY_TENSOR: {
-                rpc_copy_tensor(input, output);
+                ok = server.copy_tensor(input, output);
                 break;
             }
             case GRAPH_COMPUTE: {
-                rpc_graph_compute(backend, input, output);
+                ok = server.graph_compute(input, output);
                 break;
             }
             case GET_DEVICE_MEMORY: {
@@ -982,9 +1102,12 @@ static void rpc_serve_client(ggml_backend_t backend, sockfd_t sockfd, size_t fre
             }
             default: {
                 fprintf(stderr, "Unknown command: %d\n", cmd);
-                return;
+                ok = false;
             }
         }
+        if (!ok) {
+            break;
+        }
         uint64_t output_size = output.size();
         if (!send_data(sockfd, &output_size, sizeof(output_size))) {
             break;
diff --git a/ggml-sycl.cpp b/ggml-sycl.cpp
index 19d22d637..496ec61c3 100644
--- a/ggml-sycl.cpp
+++ b/ggml-sycl.cpp
@@ -3847,21 +3847,27 @@ static void concat_f32(const float  *x,const float  *y, float *dst, const int ne
     }
 }
 
-static void upscale_f32(const float  *x, float *dst, const int ne00, const int nb02, const int scale_factor,
-                        const sycl::nd_item<3> &item_ct1) {
-    int ne0 = ne00 * scale_factor;
-    int nidx = item_ct1.get_local_id(2) +
-               item_ct1.get_group(2) * item_ct1.get_local_range(2);
-    if (nidx >= ne0) {
+static void upscale_f32(const float  *x, float *dst, const int nb00, const int nb01,
+                        const int nb02, const int nb03, const int ne10, const int ne11,
+                        const int ne12, const int ne13, const float sf0, const float sf1,
+                        const float sf2, const float sf3, const sycl::nd_item<1> &item_ct1) {
+    int index = item_ct1.get_local_id(0) +
+               item_ct1.get_group(0) * item_ct1.get_local_range(0);
+    if (index >= ne10 * ne11 * ne12 * ne13) {
         return;
     }
     // operation
-    int i00 = nidx / scale_factor;
-    int i01 = item_ct1.get_group(1) / scale_factor;
-    int offset_src = i00 + i01 * ne00 + item_ct1.get_group(0) * nb02;
-    int offset_dst = nidx + item_ct1.get_group(1) * ne0 +
-                     item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
-    dst[offset_dst] = x[offset_src];
+    int i10 = index % ne10;
+    int i11 = (index / ne10) % ne11;
+    int i12 = (index / (ne10 * ne11)) % ne12;
+    int i13 = (index / (ne10 * ne11 * ne12)) % ne13;
+
+    int i00 = i10 / sf0;
+    int i01 = i11 / sf1;
+    int i02 = i12 / sf2;
+    int i03 = i13 / sf3;
+
+    dst[index] = *(float *)((char *)x + i03 * nb03 + i02 * nb02 + i01 * nb01 + i00 * nb00);
 }
 
 static void pad_f32(const float  *x, float *dst, const int ne0, const int ne00, const int ne01, const int ne02,
@@ -4191,7 +4197,6 @@ static void dequantize_block_q2_K(const void * __restrict__ vx, dst_t * __restri
     const block_q2_K * x = (const block_q2_K *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int n   = tid/32;
     const int l   = tid - 32*n;
     const int is  = 8*n + l/16;
@@ -4205,18 +4210,6 @@ static void dequantize_block_q2_K(const void * __restrict__ vx, dst_t * __restri
     y[l+32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 2) & 3) - dmin * (x[i].scales[is+2] >> 4);
     y[l+64] = dall * (x[i].scales[is+4] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+4] >> 4);
     y[l+96] = dall * (x[i].scales[is+6] & 0xF) * ((q >> 6) & 3) - dmin * (x[i].scales[is+6] >> 4);
-#else
-    const int is = tid/16;  // 0 or 1
-    const int il = tid%16;  // 0...15
-    const uint8_t q = x[i].qs[il] >> (2*is);
-    dst_t * y = yy + i*QK_K + 16*is + il;
-
-    float dall = x[i].dm[0];
-    float dmin = x[i].dm[1];
-    y[ 0] = dall * (x[i].scales[is+0] & 0xF) * ((q >> 0) & 3) - dmin * (x[i].scales[is+0] >> 4);
-    y[32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+2] >> 4);
-#endif
-
 }
 
 template<typename dst_t>
@@ -4226,7 +4219,6 @@ static void dequantize_block_q3_K(const void * __restrict__ vx, dst_t * __restri
     const int i = item_ct1.get_group(2);
     const block_q3_K * x = (const block_q3_K *) vx;
 
-#if QK_K == 256
     const int r = item_ct1.get_local_id(2) / 4;
     const int tid = r/2;
     const int is0 = r%2;
@@ -4250,31 +4242,8 @@ static void dequantize_block_q3_K(const void * __restrict__ vx, dst_t * __restri
     const uint8_t * hm = x[i].hmask;
 
     for (int l = l0; l < l0+4; ++l) y[l] = dl * ((int8_t)((q[l] >> shift) & 3) - ((hm[l] & m) ? 0 : 4));
-#else
-    const int tid = item_ct1.get_local_id(2);
-    const int is  = tid/16;  // 0 or 1
-    const int il  = tid%16;  // 0...15
-    const int im  = il/8;    // 0...1
-    const int in  = il%8;    // 0...7
-
-    dst_t * y = yy + i*QK_K + 16*is + il;
-
-    const uint8_t q = x[i].qs[il] >> (2*is);
-    const uint8_t h = x[i].hmask[in] >> (2*is + im);
-    const float   d = (float)x[i].d;
-
-    if (is == 0) {
-        y[ 0] = d * ((x[i].scales[0] & 0xF) - 8) * ((int8_t)((q >> 0) & 3) - ((h >> 0) & 1 ? 0 : 4));
-        y[32] = d * ((x[i].scales[1] & 0xF) - 8) * ((int8_t)((q >> 4) & 3) - ((h >> 4) & 1 ? 0 : 4));
-    } else {
-        y[ 0] = d * ((x[i].scales[0] >>  4) - 8) * ((int8_t)((q >> 0) & 3) - ((h >> 0) & 1 ? 0 : 4));
-        y[32] = d * ((x[i].scales[1] >>  4) - 8) * ((int8_t)((q >> 4) & 3) - ((h >> 4) & 1 ? 0 : 4));
-    }
-#endif
-
 }
 
-#if QK_K == 256
 static inline void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8_t & m) {
     if (j < 4) {
         d = q[j] & 63; m = q[j + 4] & 63;
@@ -4283,7 +4252,6 @@ static inline void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8
         m = (q[j+4] >>  4) | ((q[j-0] >> 6) << 4);
     }
 }
-#endif
 
 template<typename dst_t>
 static void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restrict__ yy,
@@ -4292,7 +4260,6 @@ static void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restri
 
     const int i = item_ct1.get_group(2);
 
-#if QK_K == 256
     // assume 32 threads
     const int tid = item_ct1.get_local_id(2);
     const int il  = tid/8;
@@ -4316,15 +4283,6 @@ static void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restri
         y[l + 0] = d1 * (q[l] & 0xF) - m1;
         y[l +32] = d2 * (q[l] >>  4) - m2;
     }
-#else
-    const int tid = item_ct1.get_local_id(2);
-    const uint8_t * q = x[i].qs;
-    dst_t * y = yy + i*QK_K;
-    const float d = (float)x[i].dm[0];
-    const float m = (float)x[i].dm[1];
-    y[tid+ 0] = d * (x[i].scales[0] & 0xF) * (q[tid] & 0xF) - m * (x[i].scales[0] >> 4);
-    y[tid+32] = d * (x[i].scales[1] & 0xF) * (q[tid] >>  4) - m * (x[i].scales[1] >> 4);
-#endif
 }
 
 template<typename dst_t>
@@ -4334,7 +4292,6 @@ static void dequantize_block_q5_K(const void * __restrict__ vx, dst_t * __restri
 
     const int i = item_ct1.get_group(2);
 
-#if QK_K == 256
     // assume 64 threads - this is very slightly better than the one below
     const int tid = item_ct1.get_local_id(2);
     const int il  = tid/16;   // il is in 0...3
@@ -4361,18 +4318,6 @@ static void dequantize_block_q5_K(const void * __restrict__ vx, dst_t * __restri
     hm <<= 1;
     y[32] = d2 * ((ql[ 0] >>  4) + (qh[ 0] & hm ? 16 : 0)) - m2;
     y[33] = d2 * ((ql[ 1] >>  4) + (qh[ 1] & hm ? 16 : 0)) - m2;
-#else
-    const int tid = item_ct1.get_local_id(2);
-    const uint8_t q = x[i].qs[tid];
-    const int im = tid/8;  // 0...3
-    const int in = tid%8;  // 0...7
-    const int is = tid/16; // 0 or 1
-    const uint8_t h = x[i].qh[in] >> im;
-    const float d = x[i].d;
-    dst_t * y = yy + i*QK_K + tid;
-    y[ 0] = d * x[i].scales[is+0] * ((q & 0xF) - ((h >> 0) & 1 ? 0 : 16));
-    y[32] = d * x[i].scales[is+2] * ((q >>  4) - ((h >> 4) & 1 ? 0 : 16));
-#endif
 }
 
 template<typename dst_t>
@@ -4381,7 +4326,6 @@ static void dequantize_block_q6_K(const void * __restrict__ vx, dst_t * __restri
     const block_q6_K * x = (const block_q6_K *) vx;
 
     const int i = item_ct1.get_group(2);
-#if QK_K == 256
 
     // assume 64 threads - this is very slightly better than the one below
     const int tid = item_ct1.get_local_id(2);
@@ -4401,24 +4345,6 @@ static void dequantize_block_q6_K(const void * __restrict__ vx, dst_t * __restri
     y[32] = d * sc[2] * ((int8_t)((ql[32] & 0xF) | (((qh >> 2) & 3) << 4)) - 32);
     y[64] = d * sc[4] * ((int8_t)((ql[ 0]  >> 4) | (((qh >> 4) & 3) << 4)) - 32);
     y[96] = d * sc[6] * ((int8_t)((ql[32]  >> 4) | (((qh >> 6) & 3) << 4)) - 32);
-#else
-
-    // assume 32 threads
-    const int tid = item_ct1.get_local_id(2);
-    const int ip  = tid/16;         // 0 or 1
-    const int il  = tid - 16*ip;    // 0...15
-
-    dst_t * y = yy + i*QK_K + 16*ip + il;
-
-    const float d = x[i].d;
-
-    const uint8_t   ql = x[i].ql[16*ip + il];
-    const uint8_t   qh = x[i].qh[il] >> (2*ip);
-    const int8_t  * sc = x[i].scales;
-
-    y[ 0] = d * sc[ip+0] * ((int8_t)((ql & 0xF) | (((qh >> 0) & 3) << 4)) - 32);
-    y[32] = d * sc[ip+2] * ((int8_t)((ql  >> 4) | (((qh >> 4) & 3) << 4)) - 32);
-#endif
 }
 
 template<typename dst_t>
@@ -4432,7 +4358,6 @@ static void dequantize_block_iq2_xxs(const void * __restrict__ vx, dst_t * __res
     const block_iq2_xxs * x = (const block_iq2_xxs  *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -4443,10 +4368,6 @@ static void dequantize_block_iq2_xxs(const void * __restrict__ vx, dst_t * __res
     const float d = (float)x[i].d * (0.5f + (aux32 >> 28)) * 0.25f;
     const uint8_t signs = ksigns_iq2xs_ptr[(aux32 >> 7*il) & 127];
     for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs_ptr[j] ? -1.f : 1.f);
-#else
-    assert(false);
-#endif
-
 }
 
 template<typename dst_t>
@@ -4460,7 +4381,6 @@ static void dequantize_block_iq2_xs(const void * __restrict__ vx, dst_t * __rest
     const block_iq2_xs * x = (const block_iq2_xs *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -4469,10 +4389,6 @@ static void dequantize_block_iq2_xs(const void * __restrict__ vx, dst_t * __rest
     const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f;
     const uint8_t signs = ksigns_iq2xs[q2[il] >> 9];
     for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
-#else
-    assert(false);
-#endif
-
 }
 
 template <typename dst_t>
@@ -4484,7 +4400,6 @@ dequantize_block_iq2_s(const void *__restrict__ vx, dst_t *__restrict__ yy,
     const block_iq2_s * x = (const block_iq2_s *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -4492,13 +4407,9 @@ dequantize_block_iq2_s(const void *__restrict__ vx, dst_t *__restrict__ yy,
     const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f;
     const uint8_t signs = x[i].qs[QK_K/8+4*ib+il];
 #pragma unroll
-    for (int j = 0; j < 8; ++j)
+    for (int j = 0; j < 8; ++j) {
         y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
-#else
-    assert(false);
-
-#endif
-
+    }
 }
 
 template<typename dst_t>
@@ -4512,7 +4423,6 @@ static void dequantize_block_iq3_xxs(const void * __restrict__ vx, dst_t * __res
     const block_iq3_xxs * x = (const block_iq3_xxs  *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -4527,10 +4437,6 @@ static void dequantize_block_iq3_xxs(const void * __restrict__ vx, dst_t * __res
         y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f);
         y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
     }
-#else
-    assert(false);
-#endif
-
 }
 
 template <typename dst_t>
@@ -4543,7 +4449,6 @@ dequantize_block_iq3_s(const void *__restrict__ vx, dst_t *__restrict__ yy,
     const block_iq3_s * x = (const block_iq3_s *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -4557,10 +4462,6 @@ dequantize_block_iq3_s(const void *__restrict__ vx, dst_t *__restrict__ yy,
         y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f);
         y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
     }
-#else
-    assert(false);
-#endif
-
 }
 
 template <typename dst_t>
@@ -4573,7 +4474,6 @@ dequantize_block_iq1_s(const void *__restrict__ vx, dst_t *__restrict__ yy,
     const block_iq1_s * x = (const block_iq1_s  *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -4587,10 +4487,6 @@ dequantize_block_iq1_s(const void *__restrict__ vx, dst_t *__restrict__ yy,
     for (int j = 0; j < 8; ++j) {
         y[j] = d * (q[j] + delta);
     }
-#else
-    assert(false);
-#endif
-
 }
 
 template <typename dst_t>
@@ -4603,7 +4499,6 @@ dequantize_block_iq1_m(const void *__restrict__ vx, dst_t *__restrict__ yy,
     const block_iq1_m * x = (const block_iq1_m  *) vx;
 
     const int tid = item_ct1.get_local_id(2);
-#if QK_K == 256
     const int il = tid/8; // 0...3
     const int ib = tid%8; // 0...7
     dst_t * y = yy + i*QK_K + 32*ib + 8*il;
@@ -4621,10 +4516,6 @@ dequantize_block_iq1_m(const void *__restrict__ vx, dst_t *__restrict__ yy,
     for (int j = 0; j < 8; ++j) {
         y[j] = d * (q[j] + delta);
     }
-#else
-    assert(false);
-#endif
-
 }
 
 template <typename dst_t>
@@ -4698,7 +4589,6 @@ static void dequantize_mul_mat_vec_q2_k(const void *__restrict__ vx,
 
     float tmp = 0; // partial sum for thread in warp
 
-#if QK_K == 256
     const int tid =
         item_ct1.get_local_id(2) / K_QUANTS_PER_ITERATION; // 0...31 or 0...15
     const int ix =
@@ -4749,42 +4639,6 @@ static void dequantize_mul_mat_vec_q2_k(const void *__restrict__ vx,
         tmp += dall * sum1 - dmin * sum2;
 
     }
-#else
-    const int tid = item_ct1.get_local_id(2) /
-                    (2 * K_QUANTS_PER_ITERATION); // 0...15 or 0...7
-    const int ix = item_ct1.get_local_id(2) %
-                   (2 * K_QUANTS_PER_ITERATION); // 0....1 or 0...3
-    const int offset = tid * K_QUANTS_PER_ITERATION;
-
-    uint32_t uaux[2];
-    const uint8_t * d = (const uint8_t *)uaux;
-
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-
-        const float   * y = yy + i * QK_K + offset;
-        const uint8_t * q = x[i].qs + offset;
-        const uint32_t * s = (const uint32_t *)x[i].scales;
-
-        uaux[0] = s[0] & 0x0f0f0f0f;
-        uaux[1] = (s[0] >> 4) & 0x0f0f0f0f;
-
-        const sycl::float2 dall =
-            x[i].dm.convert<float, sycl::rounding_mode::automatic>();
-
-        float sum1 = 0, sum2 = 0;
-        for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
-            const uint8_t ql = q[l];
-            sum1 += y[l+ 0] * d[0] * ((ql >> 0) & 3)
-                  + y[l+16] * d[1] * ((ql >> 2) & 3)
-                  + y[l+32] * d[2] * ((ql >> 4) & 3)
-                  + y[l+48] * d[3] * ((ql >> 6) & 3);
-            sum2 += y[l+0] * d[4] + y[l+16] * d[5] + y[l+32] * d[6] + y[l+48] * d[7];
-        }
-        tmp += dall.x() * sum1 - dall.y() * sum2;
-    }
-
-#endif
 
     // sum up partial sums and write back result
 #pragma unroll
@@ -4822,8 +4676,6 @@ static void dequantize_mul_mat_vec_q3_k(const void *__restrict__ vx,
 
     float tmp = 0; // partial sum for thread in warp
 
-#if QK_K == 256
-
     const uint16_t kmask1 = 0x0303;
     const uint16_t kmask2 = 0x0f0f;
 
@@ -4876,34 +4728,6 @@ static void dequantize_mul_mat_vec_q3_k(const void *__restrict__ vx,
         tmp += d * sum;
 
     }
-#else
-
-    const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION);  // 0...15 or 0...7
-    const int ix  = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION);  // 0....1 or 0...3
-    const int offset = tid * K_QUANTS_PER_ITERATION;         // 0...15 or 0...14
-    const int in = offset/8;                                 // 0 or 1
-    const int im = offset%8;                                 // 0...7
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-
-        const float   * y = yy + i * QK_K + offset;
-        const uint8_t * q = x[i].qs + offset;
-        const uint8_t * s = x[i].scales;
-
-        const float dall = (float)x[i].d;
-
-        float sum = 0;
-        for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
-            const uint8_t hl = x[i].hmask[im+l] >> in;
-            const uint8_t ql = q[l];
-            sum += y[l+ 0] * dall * ((s[0] & 0xF) - 8) * ((int8_t)((ql >> 0) & 3) - ((hl >> 0) & 1 ? 0 : 4))
-                 + y[l+16] * dall * ((s[0] >>  4) - 8) * ((int8_t)((ql >> 2) & 3) - ((hl >> 2) & 1 ? 0 : 4))
-                 + y[l+32] * dall * ((s[1] & 0xF) - 8) * ((int8_t)((ql >> 4) & 3) - ((hl >> 4) & 1 ? 0 : 4))
-                 + y[l+48] * dall * ((s[1] >>  4) - 8) * ((int8_t)((ql >> 6) & 3) - ((hl >> 6) & 1 ? 0 : 4));
-        }
-        tmp += sum;
-    }
-#endif
 
     // sum up partial sums and write back result
 #pragma unroll
@@ -4938,7 +4762,6 @@ static void dequantize_mul_mat_vec_q4_k(const void *__restrict__ vx,
 
     const block_q4_K * x = (const block_q4_K *)vx + ib0;
 
-#if QK_K == 256
     const uint16_t kmask1 = 0x3f3f;
     const uint16_t kmask2 = 0x0f0f;
     const uint16_t kmask3 = 0xc0c0;
@@ -5027,36 +4850,6 @@ static void dequantize_mul_mat_vec_q4_k(const void *__restrict__ vx,
 #endif
 
     }
-#else
-    const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION);  // 0...15
-    const int ix  = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION);
-
-    const int step = tid * K_QUANTS_PER_ITERATION;
-
-    uint16_t aux16[2];
-    const uint8_t * s = (const uint8_t *)aux16;
-
-    float tmp = 0;
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-        const uint8_t * q = x[i].qs + step;
-        const float   * y = yy + i*QK_K + step;
-        const uint16_t * a = (const uint16_t *)x[i].scales;
-        aux16[0] = a[0] & 0x0f0f;
-        aux16[1] = (a[0] >> 4) & 0x0f0f;
-        const float d = (float)x[i].dm[0];
-        const float m = (float)x[i].dm[1];
-        float sum = 0.f;
-        for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
-            sum += y[j+ 0] * (d * s[0] * (q[j+ 0] & 0xF) - m * s[2])
-                 + y[j+16] * (d * s[0] * (q[j+16] & 0xF) - m * s[2])
-                 + y[j+32] * (d * s[1] * (q[j+ 0] >>  4) - m * s[3])
-                 + y[j+48] * (d * s[1] * (q[j+16] >>  4) - m * s[3]);
-        }
-        tmp += sum;
-    }
-
-#endif
 
     // sum up partial sums and write back result
 #pragma unroll
@@ -5091,7 +4884,6 @@ static void dequantize_mul_mat_vec_q5_k(const void *__restrict__ vx,
 
     float tmp = 0; // partial sum for thread in warp
 
-#if QK_K == 256
     const uint16_t kmask1 = 0x3f3f;
     const uint16_t kmask2 = 0x0f0f;
     const uint16_t kmask3 = 0xc0c0;
@@ -5168,30 +4960,6 @@ static void dequantize_mul_mat_vec_q5_k(const void *__restrict__ vx,
                dmin * smin;
     }
 
-#else
-    const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION);  // 0...15
-    const int ix  = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION);
-    const int step = tid * K_QUANTS_PER_ITERATION;
-    const int im = step/8;
-    const int in = step%8;
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-        const uint8_t * q = x[i].qs + step;
-        const int8_t  * s = x[i].scales;
-        const float   * y = yy + i*QK_K + step;
-        const float     d = x[i].d;
-        float sum = 0.f;
-        for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
-            const uint8_t h = x[i].qh[in+j] >> im;
-            sum += y[j+ 0] * d * s[0] * ((q[j+ 0] & 0xF) - ((h >> 0) & 1 ? 0 : 16))
-                 + y[j+16] * d * s[1] * ((q[j+16] & 0xF) - ((h >> 2) & 1 ? 0 : 16))
-                 + y[j+32] * d * s[2] * ((q[j+ 0] >>  4) - ((h >> 4) & 1 ? 0 : 16))
-                 + y[j+48] * d * s[3] * ((q[j+16] >>  4) - ((h >> 6) & 1 ? 0 : 16));
-        }
-        tmp += sum;
-    }
-#endif
-
     // sum up partial sums and write back result
 #pragma unroll
     for (int mask = 16; mask > 0; mask >>= 1) {
@@ -5218,8 +4986,6 @@ static void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx, const floa
 
     const block_q6_K * x = (const block_q6_K *)vx + ib0;
 
-#if QK_K == 256
-
     const int tid =
         item_ct1.get_local_id(2) / K_QUANTS_PER_ITERATION; // 0...31 or 0...16
     const int ix =
@@ -5276,37 +5042,6 @@ static void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx, const floa
 
     }
 
-#else
-
-    const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION);  // 0...7
-    const int ix  = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION);  // 0...3
-
-    const int step = tid * K_QUANTS_PER_ITERATION;
-
-    float tmp = 0; // partial sum for thread in warp
-
-    for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
-
-        const float   * y  = yy + i * QK_K + step;
-        const uint8_t * ql = x[i].ql + step;
-        const uint8_t * qh = x[i].qh + step;
-        const int8_t  * s  = x[i].scales;
-
-        const float d = x[i+0].d;
-
-        float sum = 0;
-        for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
-            sum += y[j+ 0] * s[0] * d * ((int8_t)((ql[j+ 0] & 0xF) | ((qh[j] & 0x03) << 4)) - 32)
-                 + y[j+16] * s[1] * d * ((int8_t)((ql[j+16] & 0xF) | ((qh[j] & 0x0c) << 2)) - 32)
-                 + y[j+32] * s[2] * d * ((int8_t)((ql[j+ 0] >>  4) | ((qh[j] & 0x30) >> 0)) - 32)
-                 + y[j+48] * s[3] * d * ((int8_t)((ql[j+16] >>  4) | ((qh[j] & 0xc0) >> 2)) - 32);
-        }
-        tmp += sum;
-
-    }
-
-#endif
-
     // sum up partial sums and write back result
 #pragma unroll
     for (int mask = 16; mask > 0; mask >>= 1) {
@@ -6851,7 +6586,6 @@ static __dpct_inline__ float
 vec_dot_q4_K_q8_1(const void *__restrict__ vbq,
                   const block_q8_1 *__restrict__ bq8_1, const int &iqs) {
 
-#ifndef GGML_QKK_64
     const block_q4_K * bq4_K = (const block_q4_K *) vbq;
 
     int    v[2];
@@ -6893,52 +6627,6 @@ vec_dot_q4_K_q8_1(const void *__restrict__ vbq,
     }
 
     return vec_dot_q4_K_q8_1_impl_vmmq(v, u, sc, m, bq4_K->dm, d8);
-
-#else
-
-#if __SYCL_ARCH__ >= VER_4VEC // lowest compute capability for integer intrinsics
-    const block_q4_K * bq4_K = (const block_q4_K *) vbq;
-
-    float sumf_d = 0.0f;
-    float sumf_m = 0.0f;
-
-    uint16_t aux16[2];
-    const uint8_t * s = (const uint8_t *)aux16;
-
-    const uint16_t * a = (const uint16_t *)bq4_K->scales;
-    aux16[0] = a[0] & 0x0f0f;
-    aux16[1] = (a[0] >> 4) & 0x0f0f;
-
-    const float dall = bq4_K->dm[0];
-    const float dmin = bq4_K->dm[1];
-
-    const float d8_1 = bq8_1[0].ds[0];
-    const float d8_2 = bq8_1[1].ds[1];
-
-    const int ui1 = *((const int *)bq8_1[0].qs + (iqs/2));
-    const int ui2 = *((const int *)bq8_1[0].qs + (iqs/2) + 4);
-    const int ui3 = *((const int *)bq8_1[1].qs + (iqs/2));
-    const int ui4 = *((const int *)bq8_1[1].qs + (iqs/2) + 4);
-
-    const int * q4 = (const int *)bq4_K->qs + (iqs/2);
-    const int v1 = q4[0];
-    const int v2 = q4[4];
-
-    const int dot1 = dpct::dp4a(ui2, v2 & 0x0f0f0f0f, dpct::dp4a(ui1, v1 & 0x0f0f0f0f, 0));
-    const int dot2 = dpct::dp4a(ui4, (v2 >> 4) & 0x0f0f0f0f, dpct::dp4a(ui3, (v1 >> 4) & 0x0f0f0f0f, 0));
-    const int dot3 = dpct::dp4a(0x01010101, ui2, dpct::dp4a(0x01010101, ui1, 0));
-    const int dot4 = dpct::dp4a(0x01010101, ui4, dpct::dp4a(0x01010101, ui3, 0));
-
-    sumf_d += d8_1 * (dot1 * s[0]) + d8_2 * (dot2 * s[1]);
-    sumf_m += d8_1 * (dot3 * s[2]) + d8_2 * (dot4 * s[3]);
-
-    return dall * sumf_d - dmin * sumf_m;
-
-#else
-    bad_arch();
-#endif // __SYCL_ARCH__ >= VER_4VEC
-
-#endif
 }
 
 template <int mmq_y>
@@ -6997,11 +6685,7 @@ load_tiles_q4_K(const void *__restrict__ vx, int *__restrict__ x_ql,
 
         const block_q4_K * bxi = bx0 + i*blocks_per_row + kbxd;
 
-#if QK_K == 256
         x_dm[i * (WARP_SIZE/QI4_K) + i / QI4_K + kbxd] = bxi->dm;
-#else
-        x_dm[i * (WARP_SIZE/QI4_K) + i / QI4_K + kbxd] = {bxi->dm[0], bxi->dm[1]};
-#endif
     }
 
 #pragma unroll
@@ -7044,7 +6728,6 @@ static __dpct_inline__ float
 vec_dot_q5_K_q8_1(const void *__restrict__ vbq,
                   const block_q8_1 *__restrict__ bq8_1, const int &iqs) {
 
-#ifndef GGML_QKK_64
     const block_q5_K * bq5_K = (const block_q5_K *) vbq;
 
     int   vl[2];
@@ -7086,48 +6769,6 @@ vec_dot_q5_K_q8_1(const void *__restrict__ vbq,
     }
 
     return vec_dot_q5_K_q8_1_impl_vmmq(vl, vh, u, sc, m, bq5_K->dm, d8);
-
-#else
-
-#if __SYCL_ARCH__ >= VER_4VEC // lowest compute capability for integer intrinsics
-    const block_q5_K * bq5_K = (const block_q5_K *) vbq;
-
-    const int8_t * s = bq5_K->scales;
-
-    const float d = bq5_K->d;
-
-    const float d8_1 = bq8_1[0].ds[0];
-    const float d8_2 = bq8_1[1].ds[1];
-
-    const int ui1 = *((const int *)bq8_1[0].qs + (iqs/2));
-    const int ui2 = *((const int *)bq8_1[0].qs + (iqs/2) + 4);
-    const int ui3 = *((const int *)bq8_1[1].qs + (iqs/2));
-    const int ui4 = *((const int *)bq8_1[1].qs + (iqs/2) + 4);
-
-    const int * ql = (const int *)bq5_K->qs + (iqs/2);
-    const int vl1 = ql[0];
-    const int vl2 = ql[4];
-
-    const int step = 4 * (iqs/2); // 0, 4, 8, 12
-    const int im = step/8; // = 0 for iqs = 0, 2, = 1 for iqs = 4, 6
-    const int in = step%8; // 0, 4, 0, 4
-    const int vh = (*((const int *)(bq5_K->qh + in))) >> im;
-
-    const int v1 = (((vh << 4) & 0x10101010) ^ 0x10101010) | ((vl1 >> 0) & 0x0f0f0f0f);
-    const int v2 = (((vh << 2) & 0x10101010) ^ 0x10101010) | ((vl2 >> 0) & 0x0f0f0f0f);
-    const int v3 = (((vh >> 0) & 0x10101010) ^ 0x10101010) | ((vl1 >> 4) & 0x0f0f0f0f);
-    const int v4 = (((vh >> 2) & 0x10101010) ^ 0x10101010) | ((vl2 >> 4) & 0x0f0f0f0f);
-
-    const float sumf_d = d8_1 * (dpct::dp4a(ui1, v1, 0) * s[0] + dpct::dp4a(ui2, v2, 0) * s[1])
-                       + d8_2 * (dpct::dp4a(ui3, v3, 0) * s[2] + dpct::dp4a(ui4, v4, 0) * s[3]);
-
-    return d * sumf_d;
-
-#else
-    bad_arch();
-#endif // __SYCL_ARCH__ >= VER_4VEC
-
-#endif
 }
 
 template <int mmq_y>
@@ -7199,9 +6840,7 @@ load_tiles_q5_K(const void *__restrict__ vx, int *__restrict__ x_ql,
 
         const block_q5_K * bxi = bx0 + i*blocks_per_row + kbxd;
 
-#if QK_K == 256
         x_dm[i * (WARP_SIZE/QI5_K) + i / QI5_K + kbxd] = bxi->dm;
-#endif
     }
 
 #pragma unroll
@@ -7381,7 +7020,6 @@ vec_dot_iq2_xxs_q8_1(const void *__restrict__ vbq,
                      const block_q8_1 *__restrict__ bq8_1, const int &iqs,
                      const uint64_t *iq2xxs_grid, const uint8_t *ksigns_iq2xs,
                      const uint8_t *kmask_iq2xs) {
-#if QK_K == 256
     const block_iq2_xxs * bq2 = (const block_iq2_xxs *) vbq;
 
 #if QR2_XXS == 8
@@ -7422,10 +7060,6 @@ vec_dot_iq2_xxs_q8_1(const void *__restrict__ vbq,
     }
     return d * (sumi1 + sumi2);
 #endif
-#else
-    assert(false);
-    return 0.f;
-#endif
 }
 
 static __dpct_inline__ float
@@ -7434,7 +7068,6 @@ vec_dot_iq2_xs_q8_1(const void *__restrict__ vbq,
                     const uint64_t *iq2xs_grid, const uint64_t *ksigns64) {
 #if DPCT_COMPATIBILITY_TEMP >=                                                 \
     MIN_CC_DP4A // lowest compute capability for integer intrinsics
-#if QK_K == 256
     const block_iq2_xs * bq2 = (const block_iq2_xs *) vbq;
 
     const int ib32 = iqs;
@@ -7472,16 +7105,11 @@ vec_dot_iq2_xs_q8_1(const void *__restrict__ vbq,
     assert(false);
     return 0.f;
 #endif
-#else
-    assert(false);
-    return 0.f;
-#endif
 }
 
 static __dpct_inline__ float
 vec_dot_iq2_s_q8_1(const void *__restrict__ vbq,
                    const block_q8_1 *__restrict__ bq8_1, const int &iqs) {
-#if QK_K == 256
     const block_iq2_s * bq2 = (const block_iq2_s *) vbq;
 
     const int ib32 = iqs;
@@ -7525,9 +7153,6 @@ vec_dot_iq2_s_q8_1(const void *__restrict__ vbq,
     }
     const float d = (float)bq2->d * bq8_1[ib32].ds[0] * 0.25f;
     return d * ((0.5f + ls1) * sumi1 + (0.5f + ls2) * sumi2);
-#else
-    assert(false);
-#endif
 }
 
 static __dpct_inline__ float
@@ -7536,7 +7161,6 @@ vec_dot_iq3_xxs_q8_1(const void *__restrict__ vbq,
                      const uint32_t *iq3xxs_grid, const uint64_t *ksigns64) {
 #if DPCT_COMPATIBILITY_TEMP >=                                                 \
     MIN_CC_DP4A // lowest compute capability for integer intrinsics
-#if QK_K == 256
     const block_iq3_xxs * bq2 = (const block_iq3_xxs *) vbq;
 
     const int ib32 = iqs;
@@ -7564,17 +7188,12 @@ vec_dot_iq3_xxs_q8_1(const void *__restrict__ vbq,
     assert(false);
     return 0.f;
 #endif
-#else
-    assert(false);
-    return 0.f;
-#endif
 }
 
 static __dpct_inline__ float
 vec_dot_iq3_s_q8_1(const void *__restrict__ vbq,
                    const block_q8_1 *__restrict__ bq8_1, const int &iqs,
                    const uint32_t *iq3s_grid) {
-#if QK_K == 256
     const block_iq3_s * bq2 = (const block_iq3_s *) vbq;
 
     const int ib32 = iqs;
@@ -7603,16 +7222,12 @@ vec_dot_iq3_s_q8_1(const void *__restrict__ vbq,
         (1 + 2 * ((bq2->scales[ib32 / 2] >> 4 * (ib32 % 2)) & 0xf)) *
         bq8_1[ib32].ds[0];
     return d * sumi;
-#else
-    assert(false);
-#endif
 }
 
 static __dpct_inline__ float
 vec_dot_iq1_s_q8_1(const void *__restrict__ vbq,
                    const block_q8_1 *__restrict__ bq8_1, const int &iqs,
                    const uint32_t *iq1s_grid_gpu) {
-#if QK_K == 256
     const block_iq1_s * bq1 = (const block_iq1_s *) vbq;
 
     const int ib32 = iqs;
@@ -7631,15 +7246,11 @@ vec_dot_iq1_s_q8_1(const void *__restrict__ vbq,
     const float d = d1q * bq8_1[ib32].ds[0];
     const float m = d1q * bq8_1[ib32].ds[1];
     return d * sumi + m * delta;
-#else
-    assert(false);
-#endif
 }
 
 static __dpct_inline__ float
 vec_dot_iq1_m_q8_1(const void *__restrict__ vbq,
                    const block_q8_1 *__restrict__ bq8_1, const int &iqs) {
-#if QK_K == 256
     const block_iq1_m * bq1 = (const block_iq1_m *) vbq;
 
     const int ib32 = iqs;
@@ -7664,9 +7275,6 @@ vec_dot_iq1_m_q8_1(const void *__restrict__ vbq,
     scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
     const float d = (float)scale.f16 * bq8_1[ib32].ds[0];
     return d * ((sumi[0] + sumf[0]) * (2*((sc[ib32/2] >> 6*(ib32%2)) & 0x7) + 1) + (sumi[1] + sumf[1]) * (2*((sc[ib32/2] >> (6*(ib32%2)+3)) & 0x7) + 1));
-#else
-    assert(false);
-#endif
 }
 
 static __dpct_inline__ void get_int_from_table_16(const uint32_t &q4,
@@ -7714,7 +7322,6 @@ static __dpct_inline__ float
 vec_dot_iq4_xs_q8_1(const void *__restrict__ vbq,
                     const block_q8_1 *__restrict__ bq8_1, const int &iqs) {
 
-#if QK_K == 256
     const block_iq4_xs * bq4 = (const block_iq4_xs *) vbq;
     const uint8_t * values = (const uint8_t *)kvalues_iq4nl;
 
@@ -7732,9 +7339,6 @@ vec_dot_iq4_xs_q8_1(const void *__restrict__ vbq,
         sumi2 = dpct::dp4a(v2, q8[j + 4], sumi2);
     }
     return d * (sumi1 + sumi2);
-#else
-    assert(false);
-#endif
 }
 
 template <int qk, int qr, int qi, bool need_sum, typename block_q_t, int mmq_x,
@@ -10085,18 +9689,17 @@ static void concat_f32_sycl(const float *x, const float *y, float *dst,
         });
 }
 
-static void upscale_f32_sycl(const float *x, float *dst, const int ne00,
-                             const int ne01, const int ne02,
-                             const int scale_factor, dpct::queue_ptr stream) {
-    int ne0 = (ne00 * scale_factor);
-    int num_blocks = (ne0 + SYCL_UPSCALE_BLOCK_SIZE - 1) / SYCL_UPSCALE_BLOCK_SIZE;
-    sycl::range<3> gridDim(ne02, (ne01 * scale_factor), num_blocks);
+static void upscale_f32_sycl(const float *x, float *dst, const int nb00, const int nb01,
+                             const int nb02, const int nb03, const int ne10, const int ne11,
+                             const int ne12, const int ne13, const float sf0, const float sf1,
+                             const float sf2, const float sf3, dpct::queue_ptr stream) {
+    int dst_size = ne10 * ne11 * ne12 * ne13;
+    int num_blocks = (dst_size + SYCL_UPSCALE_BLOCK_SIZE - 1) / SYCL_UPSCALE_BLOCK_SIZE;
+    sycl::range<1> gridDim(num_blocks * SYCL_UPSCALE_BLOCK_SIZE);
     stream->parallel_for(
-        sycl::nd_range<3>(gridDim *
-                              sycl::range<3>(1, 1, SYCL_UPSCALE_BLOCK_SIZE),
-                          sycl::range<3>(1, 1, SYCL_UPSCALE_BLOCK_SIZE)),
-        [=](sycl::nd_item<3> item_ct1) {
-            upscale_f32(x, dst, ne00, ne00 * ne01, scale_factor, item_ct1);
+        sycl::nd_range<1>(gridDim, sycl::range<1>(SYCL_UPSCALE_BLOCK_SIZE)),
+        [=](sycl::nd_item<1> item_ct1) {
+            upscale_f32(x, dst, nb00, nb01, nb02, nb03, ne10, ne11, ne12, ne13, sf0, sf1, sf2, sf3, item_ct1);
         });
 }
 
@@ -10198,7 +9801,6 @@ template <typename dst_t>
 static void dequantize_row_q2_K_sycl(const void *vx, dst_t *y, const int k,
                                      dpct::queue_ptr stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     {
         dpct::has_capability_or_fail(stream->get_device(),
                                      {sycl::aspect::fp16});
@@ -10210,27 +9812,12 @@ static void dequantize_row_q2_K_sycl(const void *vx, dst_t *y, const int k,
                                  dequantize_block_q2_K(vx, y, item_ct1);
                              });
     }
-#else
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-
-        stream->parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
-                                                   sycl::range<3>(1, 1, 32),
-                                               sycl::range<3>(1, 1, 32)),
-                             [=](sycl::nd_item<3> item_ct1) {
-                                 dequantize_block_q2_K(vx, y, item_ct1);
-                             });
-    }
-
-#endif
 }
 
 template <typename dst_t>
 static void dequantize_row_q3_K_sycl(const void *vx, dst_t *y, const int k,
                                      dpct::queue_ptr stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     {
         dpct::has_capability_or_fail(stream->get_device(),
                                      {sycl::aspect::fp16});
@@ -10242,19 +9829,6 @@ static void dequantize_row_q3_K_sycl(const void *vx, dst_t *y, const int k,
                                  dequantize_block_q3_K(vx, y, item_ct1);
                              });
     }
-#else
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-
-        stream->parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
-                                                   sycl::range<3>(1, 1, 32),
-                                               sycl::range<3>(1, 1, 32)),
-                             [=](sycl::nd_item<3> item_ct1) {
-                                 dequantize_block_q3_K(vx, y, item_ct1);
-                             });
-    }
-#endif
 }
 
 template <typename dst_t>
@@ -10315,7 +9889,6 @@ template <typename dst_t>
 static void dequantize_row_q5_K_sycl(const void *vx, dst_t *y, const int k,
                                      dpct::queue_ptr stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     {
         dpct::has_capability_or_fail(stream->get_device(),
                                      {sycl::aspect::fp16});
@@ -10327,27 +9900,12 @@ static void dequantize_row_q5_K_sycl(const void *vx, dst_t *y, const int k,
                                  dequantize_block_q5_K(vx, y, item_ct1);
                              });
     }
-#else
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-
-        stream->parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
-                                                   sycl::range<3>(1, 1, 32),
-                                               sycl::range<3>(1, 1, 32)),
-                             [=](sycl::nd_item<3> item_ct1) {
-                                 dequantize_block_q5_K(vx, y, item_ct1);
-                             });
-    }
-
-#endif
 }
 
 template <typename dst_t>
 static void dequantize_row_q6_K_sycl(const void *vx, dst_t *y, const int k,
                                      dpct::queue_ptr stream) {
     const int nb = k / QK_K;
-#if QK_K == 256
     {
         dpct::has_capability_or_fail(stream->get_device(),
                                      {sycl::aspect::fp16});
@@ -10359,20 +9917,6 @@ static void dequantize_row_q6_K_sycl(const void *vx, dst_t *y, const int k,
                                  dequantize_block_q6_K(vx, y, item_ct1);
                              });
     }
-#else
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
-
-        stream->parallel_for(sycl::nd_range<3>(sycl::range<3>(1, 1, nb) *
-                                                   sycl::range<3>(1, 1, 32),
-                                               sycl::range<3>(1, 1, 32)),
-                             [=](sycl::nd_item<3> item_ct1) {
-                                 dequantize_block_q6_K(vx, y, item_ct1);
-                             });
-    }
-
-#endif
 }
 
 template <typename dst_t>
@@ -10524,9 +10068,6 @@ template <typename dst_t>
 static void dequantize_row_iq4_xs_sycl(const void *vx, dst_t *y, const int k,
                                        dpct::queue_ptr stream) {
     const int nb = (k + QK_K - 1) / QK_K;
-#if QK_K == 64
-    dequantize_row_iq4_nl_sycl(vx, y, k, stream);
-#else
       {
             dpct::has_capability_or_fail(stream->get_device(),
                                          {sycl::aspect::fp16});
@@ -10541,7 +10082,6 @@ static void dequantize_row_iq4_xs_sycl(const void *vx, dst_t *y, const int k,
                       });
             });
       }
-#endif
 }
 
 
@@ -12046,8 +11586,6 @@ static void ggml_mul_mat_q3_K_q8_1_sycl(const void *vx, const void *vy,
                                         const int nrows_y, const int nrows_dst,
                                         dpct::queue_ptr stream) try {
 
-#if QK_K == 256
-
     int id;
     SYCL_CHECK(
         CHECK_TRY_ERROR(id = get_current_device_id()));
@@ -12162,7 +11700,6 @@ static void ggml_mul_mat_q3_K_q8_1_sycl(const void *vx, const void *vy,
             });
         }
     }
-#endif
 }
 catch (sycl::exception const &exc) {
   std::cerr << exc.what() << "Exception caught at file:" << __FILE__
@@ -13985,15 +13522,15 @@ inline void ggml_sycl_op_upscale(const ggml_tensor *src0,
 
     GGML_ASSERT(src0->type == GGML_TYPE_F32);
     GGML_ASSERT(dst->type == GGML_TYPE_F32);
-    GGML_ASSERT(src0->ne[3] == 1 && dst->ne[3] == 1); // just 3D tensors
 
-#pragma message("TODO: generalize upscale operator")
-#pragma message("      https://github.com/ggerganov/ggml/pull/814")
-    GGML_ASSERT(false && "TODO: generalize upscale operator");
+    const float sf0 = (float)dst->ne[0]/src0->ne[0];
+    const float sf1 = (float)dst->ne[1]/src0->ne[1];
+    const float sf2 = (float)dst->ne[2]/src0->ne[2];
+    const float sf3 = (float)dst->ne[3]/src0->ne[3];
 
-    const int scale_factor = dst->op_params[0];
-
-    upscale_f32_sycl(src0_dd, dst_dd, src0->ne[0], src0->ne[1], src0->ne[2], scale_factor, main_stream);
+    upscale_f32_sycl(src0_dd, dst_dd, src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3],
+                     dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3], sf0, sf1, sf2, sf3,
+                     main_stream);
 
     (void) src1;
     (void) dst;
@@ -14449,6 +13986,9 @@ inline void ggml_sycl_op_rope(const ggml_tensor *src0, const ggml_tensor *src1,
                               ggml_tensor *dst, const float *src0_dd,
                               const float *src1_dd, float *dst_dd,
                               const dpct::queue_ptr &main_stream) {
+#pragma message("TODO: implement phi3 frequency factors support")
+#pragma message("      https://github.com/ggerganov/llama.cpp/pull/7225")
+    GGML_ASSERT(dst->src[2] == nullptr && "phi3 frequency factors not implemented yet");
 
     GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);
     GGML_ASSERT( dst->type == GGML_TYPE_F32 ||  dst->type == GGML_TYPE_F16);
diff --git a/ggml-vulkan-shaders.hpp b/ggml-vulkan-shaders.hpp
index d3a2fcf38..e8cb5f52c 100644
--- a/ggml-vulkan-shaders.hpp
+++ b/ggml-vulkan-shaders.hpp
@@ -363,320 +363,349 @@ const uint64_t add_f32_len = 4276;
 
 unsigned char argsort_f32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x2b,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x41,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
 0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
 0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,
 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x13,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,
-0x33,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x04,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x10,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x11,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x13,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,
+0x32,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,0x12,0x01,0x00,0x00,
+0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
+0x00,0x04,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x23,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2a,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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+0x30,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x89,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x8a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x8a,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x8a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
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+0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
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+0x48,0x00,0x05,0x00,0x10,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
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+0xd5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe7,0x00,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
+0x44,0x00,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
+0xec,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,
+0xee,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
+0xed,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x88,0x00,0x00,0x00,
+0xef,0x00,0x00,0x00,0xee,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x0d,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
+0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
+0xf3,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xf5,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
+0x41,0x00,0x06,0x00,0x93,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
+0x8c,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x88,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
+0xf6,0x00,0x00,0x00,0xba,0x00,0x05,0x00,0x37,0x00,0x00,0x00,
+0xf8,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0xd5,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xd5,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x37,0x00,0x00,0x00,
+0x3f,0x01,0x00,0x00,0xe6,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,
+0xf8,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xcf,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xcf,0x00,0x00,0x00,
+0xf5,0x00,0x07,0x00,0x37,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
+0xcd,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,
+0xd5,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xc6,0x00,0x00,0x00,
+0xf8,0x00,0x02,0x00,0xc6,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
+0x37,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xc3,0x00,0x00,0x00,
+0xbc,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,
+0xf7,0x00,0x03,0x00,0xfd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0xfb,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
+0xfd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfc,0x00,0x00,0x00,
+0x41,0x00,0x05,0x00,0x15,0x00,0x00,0x00,0x32,0x01,0x00,0x00,
+0x13,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x0d,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x32,0x01,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x37,0x01,0x00,0x00,
+0xbe,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x32,0x01,0x00,0x00,
+0x37,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0xbe,0x00,0x00,0x00,
+0x33,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,
+0xf8,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x6c,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x6c,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x65,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x65,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x45,0x00,0x00,0x00,
+0x45,0x00,0x00,0x00,0x46,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x57,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x57,0x00,0x00,0x00,
+0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
+0x3d,0x01,0x00,0x00,0x45,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x54,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x56,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x4b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x4b,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x07,0x01,0x00,0x00,0x3c,0x01,0x00,0x00,0x45,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x48,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x4a,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0x37,0x00,0x00,0x00,
+0x0c,0x01,0x00,0x00,0x2f,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
+0xf7,0x00,0x03,0x00,0x0e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
+0x0e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x0d,0x01,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
+0x41,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x0d,0x00,0x00,0x00,0x19,0x01,0x00,0x00,0x44,0x00,0x00,0x00,
+0x41,0x00,0x06,0x00,0x1a,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,
+0x12,0x01,0x00,0x00,0x3e,0x00,0x00,0x00,0x16,0x01,0x00,0x00,
+0x3e,0x00,0x03,0x00,0x1b,0x01,0x00,0x00,0x19,0x01,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x0e,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x0e,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x1d,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x1d,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
+0x38,0x00,0x01,0x00,
 };
-const uint64_t argsort_f32_len = 3752;
+const uint64_t argsort_f32_len = 4096;
 
 unsigned char clamp_f32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
@@ -11994,7 +12023,7 @@ const uint64_t matmul_f16_len = 10316;
 
 unsigned char matmul_f16_aligned_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xf5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x08,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
 0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
@@ -12002,9 +12031,9 @@ unsigned char matmul_f16_aligned_data[] = {
 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
 0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
 0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x51,0x01,0x00,0x00,
-0x55,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
+0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
+0x05,0x01,0x00,0x00,0x63,0x01,0x00,0x00,0x69,0x01,0x00,0x00,
+0x68,0x02,0x00,0x00,0xb1,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
 0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
@@ -12047,37 +12076,40 @@ unsigned char matmul_f16_aligned_data[] = {
 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x05,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x07,0x01,0x00,0x00,
+0x47,0x00,0x04,0x00,0x02,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x03,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x03,0x01,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x07,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x21,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x22,0x01,0x00,0x00,
+0x05,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x3b,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3c,0x01,0x00,0x00,
 0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4e,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,
+0x66,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x67,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x67,0x01,0x00,0x00,
 0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x01,0x00,0x00,
+0x67,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x67,0x01,0x00,0x00,
 0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x4f,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x51,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x51,0x01,0x00,0x00,
+0x47,0x00,0x03,0x00,0x67,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x69,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x69,0x01,0x00,0x00,
 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x55,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x9b,0x02,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x9c,0x02,0x00,0x00,
+0x68,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xae,0x02,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xaf,0x02,0x00,0x00,
 0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x9c,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x9c,0x02,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x9e,0x02,0x00,0x00,
+0xaf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xaf,0x02,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb1,0x02,0x00,0x00,
 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x9e,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0xb1,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
 0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
 0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
 0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
@@ -12128,16 +12160,16 @@ unsigned char matmul_f16_aligned_data[] = {
 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
 0x86,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x6e,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
 0x06,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
 0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
 0x15,0x00,0x00,0x00,0x82,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
 0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
 0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
@@ -12180,727 +12212,756 @@ unsigned char matmul_f16_aligned_data[] = {
 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,
 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
 0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0xf7,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
 0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xfb,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xfb,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
+0x16,0x00,0x03,0x00,0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
 0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x04,0x01,0x00,0x00,0xf7,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x05,0x01,0x00,0x00,0x04,0x01,0x00,0x00,
-0x20,0x00,0x04,0x00,0x06,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x06,0x01,0x00,0x00,
-0x07,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x15,0x01,0x00,0x00,0x04,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x1b,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xf7,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x22,0x01,0x00,0x00,
-0x21,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x51,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0x84,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x86,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
+0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
+0x1c,0x00,0x04,0x00,0xfc,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
+0xfb,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xfd,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0xfd,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x17,0x00,0x04,0x00,0x00,0x01,0x00,0x00,0xf9,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x18,0x00,0x04,0x00,0x01,0x01,0x00,0x00,
+0x00,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0x02,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x1e,0x00,0x03,0x00,
+0x03,0x01,0x00,0x00,0x02,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
+0x04,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x03,0x01,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x05,0x01,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x07,0x01,0x00,0x00,
+0x0c,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x0a,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x19,0x01,0x00,0x00,
+0x03,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x20,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x27,0x01,0x00,0x00,0x05,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x2e,0x01,0x00,0x00,
+0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x35,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
+0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,
+0x3b,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
+0x51,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
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 0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
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 0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
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-0x48,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x04,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x4c,0x01,0x00,0x00,0xf7,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x18,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,
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-0xd7,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xd8,0x01,0x00,0x00,
-0xf7,0x00,0x00,0x00,0xd7,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
-0xd9,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0xd8,0x01,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xe2,0x01,0x00,0x00,
-0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xea,0x01,0x00,0x00,
-0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x19,0x02,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x60,0x01,0x00,0x00,
+0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x5f,0x01,0x00,0x00,
+0x1c,0x00,0x04,0x00,0x61,0x01,0x00,0x00,0xf9,0x00,0x00,0x00,
+0x60,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x62,0x01,0x00,0x00,
+0x04,0x00,0x00,0x00,0x61,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x62,0x01,0x00,0x00,0x63,0x01,0x00,0x00,0x04,0x00,0x00,0x00,
+0x1d,0x00,0x03,0x00,0x66,0x01,0x00,0x00,0x01,0x01,0x00,0x00,
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+0x97,0x02,0x00,0x00,0x98,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x97,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x9f,0x02,0x00,0x00,0x84,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
+0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,
+0x9f,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
+0xa4,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xa4,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
+0xdb,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
+0xa8,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xa9,0x02,0x00,0x00,
+0xa8,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
+0xaa,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xa4,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
+0xab,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0x97,0x02,0x00,0x00,
+0xaa,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
+0xad,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0xab,0x02,0x00,0x00,0xac,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0xac,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xb5,0x02,0x00,0x00,0x8c,0x02,0x00,0x00,
+0xdb,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
+0xb7,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xb6,0x02,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,
+0xb7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xb9,0x02,0x00,0x00,0xb5,0x02,0x00,0x00,0xb8,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xba,0x02,0x00,0x00,
+0x6c,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0xba,0x02,0x00,0x00,
+0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xbe,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,
+0xd8,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xc2,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,
+0xdb,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xc4,0x02,0x00,0x00,0xc2,0x02,0x00,0x00,0xc3,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,
+0xd9,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xc7,0x02,0x00,0x00,0xc4,0x02,0x00,0x00,
+0xc6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xc9,0x02,0x00,0x00,0xc7,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
+0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0xca,0x02,0x00,0x00,
+0xca,0x00,0x00,0x00,0xc9,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
+0xc4,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0xca,0x02,0x00,0x00,
+0x41,0x00,0x06,0x00,0xcc,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,
+0xb1,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0xbe,0x02,0x00,0x00,
+0x3e,0x00,0x03,0x00,0xcd,0x02,0x00,0x00,0xcb,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0xad,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xad,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xcf,0x02,0x00,0x00,0xdd,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x96,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x98,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x91,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x91,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd1,0x02,0x00,0x00,
+0xdb,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x8e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x90,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x79,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xd3,0x02,0x00,0x00,0xd9,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x76,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x78,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x71,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xd5,0x02,0x00,0x00,0xd8,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x6e,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x70,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
+0x38,0x00,0x01,0x00,
 };
-const uint64_t matmul_f16_aligned_len = 10812;
+const uint64_t matmul_f16_aligned_len = 11200;
 
 unsigned char matmul_f16_aligned_fp32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0xd8,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
 0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
 0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
@@ -12908,8 +12969,8 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
 0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x49,0x01,0x00,0x00,
-0x50,0x01,0x00,0x00,0x39,0x02,0x00,0x00,0x82,0x02,0x00,0x00,
+0xfd,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,
+0x50,0x01,0x00,0x00,0x38,0x02,0x00,0x00,0x81,0x02,0x00,0x00,
 0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
@@ -12952,17 +13013,17 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x01,0x01,0x00,0x00,
+0x06,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x05,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x07,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x07,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x21,0x01,0x00,0x00,
+0x02,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x04,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x22,0x01,0x00,0x00,
 0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x22,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x23,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
 0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4e,0x01,0x00,0x00,
 0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
@@ -12971,15 +13032,15 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x01,0x00,0x00,
 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0x50,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x39,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7f,0x02,0x00,0x00,
+0x47,0x00,0x04,0x00,0x38,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7e,0x02,0x00,0x00,
 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x80,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x80,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
+0x7f,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x7f,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x80,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x82,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x82,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
+0x7f,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x81,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x81,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
 0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
 0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
 0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
@@ -13030,16 +13091,16 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
 0x68,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x62,0x00,0x00,0x00,
 0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x73,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x79,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
 0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
 0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
 0x87,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
@@ -13083,99 +13144,97 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
 0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
+0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
 0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xf9,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xfa,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xff,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x03,0x01,0x00,0x00,
-0x10,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x04,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0x1e,0x00,0x03,0x00,0x05,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x06,0x01,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x06,0x01,0x00,0x00,0x07,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x16,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,0x80,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x22,0x01,0x00,0x00,
-0x21,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x51,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0x84,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x86,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x47,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,
-0x46,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x48,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x48,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x04,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x4c,0x01,0x00,0x00,0x03,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x4d,0x01,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x1e,0x00,0x03,0x00,0x4e,0x01,0x00,0x00,
-0x4d,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x4f,0x01,0x00,0x00,0x50,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x65,0x01,0x00,0x00,
-0x03,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x6c,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x22,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x6c,0x01,0x00,0x00,
-0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x6e,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x01,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x71,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x72,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
+0xf9,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
+0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0xfa,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
+0xf9,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xfb,0x00,0x00,0x00,
+0xc4,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0xfc,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0xfc,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xff,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x00,0x01,0x00,0x00,
+0xff,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0x01,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x1e,0x00,0x03,0x00,
+0x02,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
+0x03,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x04,0x01,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x06,0x01,0x00,0x00,
+0x0c,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x0a,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,
+0x03,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x22,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,
+0x09,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,
+0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x51,0x00,0x00,0x00,
+0x23,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,0x84,0x00,0x00,0x00,
+0x24,0x01,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
+0x25,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x80,0x00,0x00,0x00,
 0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x75,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x90,0x01,0x00,0x00,0x84,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x46,0x01,0x00,0x00,0x80,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x84,0x00,0x00,0x00,
+0xa7,0x00,0x00,0x00,0x46,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,
+0x48,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x47,0x01,0x00,0x00,
+0x20,0x00,0x04,0x00,0x49,0x01,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x49,0x01,0x00,0x00,
+0x4a,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0x4d,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x1e,0x00,0x03,0x00,
+0x4e,0x01,0x00,0x00,0x4d,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
+0x4f,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,0x50,0x01,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0x6b,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0x6c,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x6b,0x01,0x00,0x00,
+0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0x6d,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x6c,0x01,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x70,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x71,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x74,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,0x84,0x00,0x00,0x00,
 0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0x91,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x90,0x01,0x00,0x00,
-0x20,0x00,0x04,0x00,0x92,0x01,0x00,0x00,0x07,0x00,0x00,0x00,
-0x91,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xa2,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
+0x90,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,
+0x20,0x00,0x04,0x00,0x91,0x01,0x00,0x00,0x07,0x00,0x00,0x00,
+0x90,0x01,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0xa1,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
 0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xbd,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xbe,0x01,0x00,0x00,
-0xc4,0x00,0x00,0x00,0xbd,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
-0xbf,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0xbe,0x01,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc8,0x01,0x00,0x00,
+0xbc,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
+0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xbd,0x01,0x00,0x00,
+0xc4,0x00,0x00,0x00,0xbc,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
+0xbe,0x01,0x00,0x00,0x07,0x00,0x00,0x00,0xbd,0x01,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc7,0x01,0x00,0x00,
 0x86,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xd0,0x01,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xcf,0x01,0x00,0x00,
 0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xff,0x01,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfe,0x01,0x00,0x00,
 0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x31,0x02,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x30,0x02,0x00,0x00,
 0x0d,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x39,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x7f,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x80,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,0x20,0x00,0x04,0x00,
-0x81,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x80,0x02,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x81,0x02,0x00,0x00,0x82,0x02,0x00,0x00,
+0x38,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0x7e,0x02,0x00,0x00,0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
+0x7f,0x02,0x00,0x00,0x7e,0x02,0x00,0x00,0x20,0x00,0x04,0x00,
+0x80,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0x7f,0x02,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x80,0x02,0x00,0x00,0x81,0x02,0x00,0x00,
 0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x87,0x02,0x00,0x00,0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0x84,0x00,0x00,0x00,
+0x86,0x02,0x00,0x00,0x05,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x93,0x02,0x00,0x00,0x84,0x00,0x00,0x00,
 0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x9d,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
+0x9c,0x02,0x00,0x00,0x0c,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
 0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
 0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
 0x05,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xc9,0x00,0x00,0x00,
 0xca,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x92,0x01,0x00,0x00,0x93,0x01,0x00,0x00,0x07,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0xbf,0x01,0x00,0x00,0xc0,0x01,0x00,0x00,
+0x91,0x01,0x00,0x00,0x92,0x01,0x00,0x00,0x07,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0xbe,0x01,0x00,0x00,0xbf,0x01,0x00,0x00,
 0x07,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
 0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
@@ -13232,9 +13291,9 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0x65,0x00,0x00,0x00,0x5e,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
 0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
 0x5e,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x70,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
+0x6f,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x75,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
 0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
 0x4f,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
 0x06,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
@@ -13267,7 +13326,7 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0x9b,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
 0x9e,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
 0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,
-0x9e,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
+0x9e,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
 0x17,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
 0xa2,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
 0xa4,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
@@ -13283,479 +13342,481 @@ unsigned char matmul_f16_aligned_fp32_data[] = {
 0xac,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
 0xaf,0x00,0x00,0x00,0xad,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
 0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0xaf,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xaf,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
 0xb2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xb2,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,
+0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,
 0x3f,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,
 0xb3,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xc3,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0xc1,0x00,0x00,0x00,
+0xc3,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,0xc1,0x00,0x00,0x00,
 0xf6,0x00,0x04,0x00,0xb4,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
 0xb3,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
 0xb3,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0xce,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,
+0xce,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0xa6,0x02,0x00,0x00,
 0x3e,0x00,0x03,0x00,0xce,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
 0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xa6,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
 0xb2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xb4,0x00,0x00,0x00,
 0xf9,0x00,0x02,0x00,0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
 0xd4,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xc0,0x02,0x00,0x00,0xb0,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
-0x77,0x01,0x00,0x00,0xd7,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0x9f,0x00,0x00,0x00,
-0xb4,0x00,0x00,0x00,0x74,0x01,0x00,0x00,0xd7,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,
-0x85,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0x22,0x02,0x00,0x00,
+0xbf,0x02,0x00,0x00,0xb0,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
+0x76,0x01,0x00,0x00,0xd7,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
+0x06,0x00,0x00,0x00,0xbb,0x02,0x00,0x00,0x9f,0x00,0x00,0x00,
+0xb4,0x00,0x00,0x00,0x73,0x01,0x00,0x00,0xd7,0x00,0x00,0x00,
+0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,
+0x85,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0x21,0x02,0x00,0x00,
 0xd7,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xdb,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,0x8f,0x00,0x00,0x00,
+0xdb,0x00,0x00,0x00,0xa7,0x02,0x00,0x00,0x8f,0x00,0x00,0x00,
 0xf6,0x00,0x04,0x00,0xd6,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xdb,0x00,0x00,0x00,
 0xd5,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
 0xd5,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,
 0xf8,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0x27,0x01,0x00,0x00,0xe0,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
+0xd5,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0xde,0x00,0x00,0x00,
 0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x38,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xdf,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0xb7,0x02,0x00,0x00,0x38,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
+0xdf,0x00,0x00,0x00,0xde,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0xfa,0x00,0x04,0x00,0xe3,0x00,0x00,0x00,0xde,0x00,0x00,0x00,
 0xdf,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xee,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xec,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xed,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0xa8,0x02,0x00,0x00,0x6f,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xee,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xee,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc2,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0xde,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf6,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf4,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,
-0x18,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0xb8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0xfe,0x00,0x00,0x00,
-0xff,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x02,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0e,0x01,0x00,0x00,
-0xfe,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,0xbc,0x02,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x11,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x12,0x01,0x00,0x00,0x13,0x01,0x00,0x00,
-0x07,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x11,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x14,0x01,0x00,0x00,
-0x13,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x14,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x01,0x00,0x00,0x17,0x01,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x02,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x17,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x18,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,0x74,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,0x1c,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x6f,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x01,0x00,0x00,0x20,0x01,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x20,0x01,0x00,0x00,
-0xcc,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xe0,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xe0,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x27,0x01,0x00,0x00,
-0xb8,0x02,0x00,0x00,0x25,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
+0x75,0x00,0x00,0x00,0xb7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,
+0x9a,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xec,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
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+0xf9,0x00,0x02,0x00,0x49,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x49,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xa3,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x46,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x48,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x41,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xa5,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x40,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
 0x38,0x00,0x01,0x00,
 };
 const uint64_t matmul_f16_aligned_fp32_len = 10288;
@@ -14628,7 +14689,7 @@ const uint64_t matmul_f16_f32_len = 10332;
 
 unsigned char matmul_f16_f32_aligned_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xfd,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x12,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
 0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
 0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
@@ -14636,9 +14697,9 @@ unsigned char matmul_f16_f32_aligned_data[] = {
 0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
 0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
 0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x07,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x51,0x01,0x00,0x00,
-0x5e,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
+0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
+0x05,0x01,0x00,0x00,0x63,0x01,0x00,0x00,0x6b,0x01,0x00,0x00,
+0x73,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
 0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
@@ -14681,37 +14742,40 @@ unsigned char matmul_f16_f32_aligned_data[] = {
 0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x05,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x07,0x01,0x00,0x00,
+0x47,0x00,0x04,0x00,0x02,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x03,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x03,0x01,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x07,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x21,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x22,0x01,0x00,0x00,
+0x05,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x3b,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3c,0x01,0x00,0x00,
 0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x4e,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,
+0x68,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x69,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x69,0x01,0x00,0x00,
 0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x4f,0x01,0x00,0x00,
+0x69,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x69,0x01,0x00,0x00,
 0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x4f,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x51,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x51,0x01,0x00,0x00,
+0x47,0x00,0x03,0x00,0x69,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x6b,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6b,0x01,0x00,0x00,
 0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x5e,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa4,0x02,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xa5,0x02,0x00,0x00,
+0x73,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xb9,0x02,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xba,0x02,0x00,0x00,
 0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xa5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xa5,0x02,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x02,0x00,0x00,
+0xba,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xba,0x02,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbc,0x02,0x00,0x00,
 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa7,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0xbc,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
 0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
 0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
 0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
@@ -14762,16 +14826,16 @@ unsigned char matmul_f16_f32_aligned_data[] = {
 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
 0x86,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
 0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x6e,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x73,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x78,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x6e,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
 0x06,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
 0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
 0x15,0x00,0x00,0x00,0x82,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
 0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
 0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
@@ -14814,733 +14878,765 @@ unsigned char matmul_f16_f32_aligned_data[] = {
 0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,
 0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
 0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0xf7,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,
 0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xfb,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xfb,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
+0x16,0x00,0x03,0x00,0xf9,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
 0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x04,0x01,0x00,0x00,0xf7,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x05,0x01,0x00,0x00,0x04,0x01,0x00,0x00,
-0x20,0x00,0x04,0x00,0x06,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x05,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x06,0x01,0x00,0x00,
-0x07,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x15,0x01,0x00,0x00,0x04,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x1b,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xf7,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x22,0x01,0x00,0x00,
-0x21,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x51,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0x84,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
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+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,
+0xe7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x9c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xdb,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
+0xe2,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
 0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
 };
-const uint64_t matmul_f16_f32_aligned_len = 10940;
+const uint64_t matmul_f16_f32_aligned_len = 11360;
 
 unsigned char matmul_f16_f32_aligned_fp32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
@@ -15552,8 +15648,8 @@ unsigned char matmul_f16_f32_aligned_fp32_data[] = {
 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
 0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfb,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x49,0x01,0x00,0x00,
-0x50,0x01,0x00,0x00,0x36,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
+0xfd,0x00,0x00,0x00,0x04,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,
+0x51,0x01,0x00,0x00,0x36,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
 0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
@@ -15596,25 +15692,25 @@ unsigned char matmul_f16_f32_aligned_fp32_data[] = {
 0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x01,0x01,0x00,0x00,
+0x06,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x02,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x05,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x07,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x07,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x21,0x01,0x00,0x00,
+0x02,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x04,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x22,0x01,0x00,0x00,
 0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x22,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4e,0x01,0x00,0x00,
+0x23,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x4e,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,
 0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x4e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4e,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x01,0x00,0x00,
+0x4f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4f,0x01,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x51,0x01,0x00,0x00,
 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x50,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x51,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0x36,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
 0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7c,0x02,0x00,0x00,
 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
@@ -15674,16 +15770,16 @@ unsigned char matmul_f16_f32_aligned_fp32_data[] = {
 0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
 0x68,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x62,0x00,0x00,0x00,
 0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x73,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x6d,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x79,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
 0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,
 0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
 0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
 0x87,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
@@ -15727,677 +15823,678 @@ unsigned char matmul_f16_f32_aligned_fp32_data[] = {
 0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
 0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
+0xf4,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
 0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xf9,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xfa,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xff,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x03,0x01,0x00,0x00,
-0x10,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x04,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0x1e,0x00,0x03,0x00,0x05,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x06,0x01,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x06,0x01,0x00,0x00,0x07,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x16,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,0x80,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,0x22,0x01,0x00,0x00,
-0x21,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x51,0x00,0x00,0x00,0x22,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0x84,0x00,0x00,0x00,0x23,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x86,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x46,0x01,0x00,0x00,
-0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x47,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,
-0x46,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x48,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x48,0x01,0x00,0x00,0x49,0x01,0x00,0x00,0x04,0x00,0x00,0x00,
-0x17,0x00,0x04,0x00,0x4c,0x01,0x00,0x00,0xc4,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x4d,0x01,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x1e,0x00,0x03,0x00,0x4e,0x01,0x00,0x00,
-0x4d,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x4f,0x01,0x00,0x00,0x50,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x52,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x63,0x01,0x00,0x00,0x03,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x69,0x01,0x00,0x00,0x51,0x00,0x00,0x00,
-0x22,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x6a,0x01,0x00,0x00,0x84,0x00,0x00,0x00,
-0x69,0x01,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x6b,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6a,0x01,0x00,0x00,0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x6e,0x01,0x00,0x00,0x08,0x01,0x00,0x00,
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+0xc4,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
+0x41,0x00,0x06,0x00,0x53,0x01,0x00,0x00,0x9a,0x02,0x00,0x00,
+0x7f,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
+0x3e,0x00,0x03,0x00,0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
+0xa8,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x47,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xa0,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x46,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
+0x38,0x00,0x01,0x00,
 };
-const uint64_t matmul_f16_f32_aligned_fp32_len = 10224;
+const uint64_t matmul_f16_f32_aligned_fp32_len = 10240;
 
 unsigned char matmul_f16_f32_fp32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
@@ -18987,7 +19084,7 @@ const uint64_t matmul_f32_len = 10324;
 
 unsigned char matmul_f32_aligned_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xfd,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x17,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
 0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
 0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
@@ -18995,8 +19092,8 @@ unsigned char matmul_f32_aligned_data[] = {
 0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
 0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
-0xfc,0x00,0x00,0x00,0x07,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,
-0x52,0x01,0x00,0x00,0x5e,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
+0xfe,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x6b,0x01,0x00,0x00,
+0x71,0x01,0x00,0x00,0x78,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,
 0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
@@ -19039,37 +19136,4514 @@ unsigned char matmul_f32_aligned_data[] = {
 0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
 0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x04,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x05,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x05,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x07,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x07,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x22,0x01,0x00,0x00,
+0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x02,0x01,0x00,0x00,
+0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x03,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x05,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x05,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x43,0x01,0x00,0x00,
 0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x23,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4f,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x50,0x01,0x00,0x00,
+0x44,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x6e,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x6f,0x01,0x00,0x00,
 0x00,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x50,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x50,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x6f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x6f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x50,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x50,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x52,0x01,0x00,0x00,
+0x6f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x6f,0x01,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x71,0x01,0x00,0x00,
 0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x52,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x5e,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa4,0x02,0x00,0x00,
+0x71,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x78,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbe,0x02,0x00,0x00,
 0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xa5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xa5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
+0xbf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0xbf,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xa5,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa7,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa7,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
+0xbf,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xc1,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xc1,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
+0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x16,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x0a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x28,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x15,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x38,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x3f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x0a,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x54,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x55,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x38,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x38,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x62,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
+0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0x64,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x62,0x00,0x00,0x00,
+0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0x68,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x62,0x00,0x00,0x00,
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+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,
+0xd0,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,
+0xd3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xd6,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd7,0x02,0x00,0x00,
+0xd4,0x02,0x00,0x00,0xd6,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,0xd7,0x02,0x00,0x00,
+0xec,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
+0xda,0x02,0x00,0x00,0xca,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,
+0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xdb,0x02,0x00,0x00,
+0xda,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x07,0x01,0x00,0x00,
+0xdc,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
+0xce,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xdc,0x02,0x00,0x00,
+0xdb,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0xbd,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xa9,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa9,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xde,0x02,0x00,0x00,
+0xec,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xa6,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa8,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xa1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xe0,0x02,0x00,0x00,0xea,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x9e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xa0,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x89,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x89,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xe2,0x02,0x00,0x00,0xe8,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x86,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x88,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x81,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe4,0x02,0x00,0x00,
+0xe7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x7e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x80,0x02,0x00,0x00,
+0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
+};
+const uint64_t matmul_f32_aligned_len = 11432;
+
+unsigned char matmul_f32_aligned_fp32_data[] = {
+0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
+0xce,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
+0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
+0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
+0x4d,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x03,0x01,0x00,0x00,
+0x45,0x01,0x00,0x00,0x4b,0x01,0x00,0x00,0x2f,0x02,0x00,0x00,
+0x78,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
+0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x00,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x01,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x01,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x01,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x03,0x01,0x00,0x00,
+0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x1d,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x1e,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x48,0x01,0x00,0x00,
+0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x49,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x49,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x49,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x4b,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x4b,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x2f,0x02,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x75,0x02,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x76,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
+0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x76,0x02,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x76,0x02,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x78,0x02,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x78,0x02,0x00,0x00,
+0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
+0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
+0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x13,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x22,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x15,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x35,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
+0x3e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x50,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x55,0x00,0x00,0x00,
+0x86,0x00,0x00,0x00,0x38,0x00,0x00,0x00,0x54,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x59,0x00,0x00,0x00,
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+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x47,0x02,0x00,0x00,
+0x9f,0x02,0x00,0x00,0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x48,0x02,0x00,0x00,0x1e,0x02,0x00,0x00,
+0x47,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x4a,0x02,0x00,0x00,0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4b,0x02,0x00,0x00,
+0x48,0x02,0x00,0x00,0x4a,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x4f,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,
+0xbe,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x50,0x02,0x00,0x00,0x24,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x52,0x02,0x00,0x00,
+0x69,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x53,0x02,0x00,0x00,0x50,0x02,0x00,0x00,
+0x52,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x55,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x55,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
+0x06,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
+0x3e,0x02,0x00,0x00,0x97,0x02,0x00,0x00,0x58,0x02,0x00,0x00,
+0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x5b,0x02,0x00,0x00,
+0xa1,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
+0x57,0x02,0x00,0x00,0x58,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0x5b,0x02,0x00,0x00,0x56,0x02,0x00,0x00,
+0x57,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x56,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x5d,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
+0xa3,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x56,0x02,0x00,0x00,
+0x95,0x02,0x00,0x00,0x60,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
+0xc2,0x00,0x00,0x00,0x63,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
+0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x5f,0x02,0x00,0x00,
+0x60,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0x63,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,0x5f,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x66,0x02,0x00,0x00,0x4b,0x02,0x00,0x00,
+0xa3,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
+0x69,0x02,0x00,0x00,0x66,0x02,0x00,0x00,0x37,0x00,0x00,0x00,
+0xf7,0x00,0x03,0x00,0x6b,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0x69,0x02,0x00,0x00,0x6a,0x02,0x00,0x00,
+0x6b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6a,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6e,0x02,0x00,0x00,
+0x53,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
+0x17,0x00,0x00,0x00,0x6f,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
+0xd0,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x70,0x02,0x00,0x00,0x6f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
+0xc2,0x00,0x00,0x00,0x71,0x02,0x00,0x00,0x6e,0x02,0x00,0x00,
+0x70,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
+0xc2,0x00,0x00,0x00,0x72,0x02,0x00,0x00,0x69,0x02,0x00,0x00,
+0x5e,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0x6a,0x02,0x00,0x00,
+0xf7,0x00,0x03,0x00,0x74,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0x72,0x02,0x00,0x00,0x73,0x02,0x00,0x00,
+0x74,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x73,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7c,0x02,0x00,0x00,
+0x53,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
+0x17,0x00,0x00,0x00,0x7e,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
+0x7d,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x7f,0x02,0x00,0x00,0x7e,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x80,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,
+0x7f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x81,0x02,0x00,0x00,0x33,0x02,0x00,0x00,0x80,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x83,0x02,0x00,0x00,
+0x81,0x02,0x00,0x00,0x4b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x85,0x02,0x00,0x00,0x83,0x02,0x00,0x00,
+0xa3,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x87,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,
+0x87,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x8b,0x02,0x00,0x00,0x89,0x02,0x00,0x00,
+0x8a,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x8d,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
+0x8b,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
+0xa3,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
+0x91,0x02,0x00,0x00,0xca,0x00,0x00,0x00,0x90,0x02,0x00,0x00,
+0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
+0x91,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x05,0x01,0x00,0x00,
+0x93,0x02,0x00,0x00,0x78,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
+0x85,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x93,0x02,0x00,0x00,
+0x92,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x74,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x74,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x60,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x60,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,
+0xa3,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x5d,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x58,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x58,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x97,0x02,0x00,0x00,0xa1,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x55,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x57,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x40,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x40,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3d,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x38,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x38,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x02,0x00,0x00,
+0x9e,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x35,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x37,0x02,0x00,0x00,
+0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
+};
+const uint64_t matmul_f32_aligned_fp32_len = 10124;
+
+unsigned char matmul_f32_f16_data[] = {
+0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
+0xd9,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
+0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
+0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
+0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
+0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
+0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
+0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
+0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
+0x06,0x01,0x00,0x00,0x47,0x01,0x00,0x00,0x52,0x01,0x00,0x00,
+0x3a,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
+0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb8,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xbb,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x04,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
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+0x9e,0x02,0x00,0x00,0x9d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x7f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7f,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x6b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x6b,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xa0,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x68,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x6a,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x63,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xac,0x02,0x00,0x00,
+0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x60,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x62,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x4b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4b,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa4,0x02,0x00,0x00,
+0xaa,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x48,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x4a,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x43,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x43,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xa6,0x02,0x00,0x00,0xa9,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x40,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x42,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
+
+};
+const uint64_t matmul_f32_f16_len = 10332;
+
+unsigned char matmul_f32_f16_aligned_data[] = {
+0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
+0x12,0x03,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x09,0x00,0x00,0x00,
+0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,0x0b,0x00,0x06,0x00,
+0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,
+0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,
+0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,
+0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,
+0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
+0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0xfe,0x00,0x00,0x00,
+0x05,0x01,0x00,0x00,0x6b,0x01,0x00,0x00,0x73,0x01,0x00,0x00,
+0x73,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x10,0x00,0x06,0x00,
+0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x12,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x38,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x63,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xb9,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x02,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x03,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x10,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x03,0x01,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x05,0x01,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x05,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x43,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x44,0x01,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x70,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x71,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x05,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x71,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x71,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x71,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x71,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x73,0x01,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x73,0x01,0x00,0x00,
+0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x73,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xb9,0x02,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xba,0x02,0x00,0x00,
+0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0xba,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xba,0x02,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xbc,0x02,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xbc,0x02,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
+0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x10,0x00,
+0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x12,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
+0x14,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
+0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x17,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x15,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x2e,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x15,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
+0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x3a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x0a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
+0x4d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x50,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x54,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0x55,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
+0x54,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
+0x59,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
+0x54,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x61,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x62,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x54,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
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+0xce,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xd1,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd2,0x02,0x00,0x00,
+0xcf,0x02,0x00,0x00,0xd1,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,
+0xe7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
+0xd5,0x02,0x00,0x00,0xca,0x00,0x00,0x00,0xd4,0x02,0x00,0x00,
+0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0xd6,0x02,0x00,0x00,
+0xd5,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x07,0x01,0x00,0x00,
+0xd7,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
+0xc9,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0xd7,0x02,0x00,0x00,
+0xd6,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0xb8,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xa4,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa4,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd9,0x02,0x00,0x00,
+0xe7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xa1,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x9c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x9c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xdb,0x02,0x00,0x00,0xe5,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x99,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x9b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x84,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xdd,0x02,0x00,0x00,0xe3,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x81,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x83,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x7c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7c,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xdf,0x02,0x00,0x00,
+0xe2,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x79,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
+0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
+};
+const uint64_t matmul_f32_f16_aligned_len = 11360;
+
+unsigned char matmul_f32_f16_aligned_fp32_data[] = {
+0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
+0xd5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
+0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
+0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
+0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
+0xfd,0x00,0x00,0x00,0x03,0x01,0x00,0x00,0x45,0x01,0x00,0x00,
+0x4d,0x01,0x00,0x00,0x36,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
+0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa7,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xb9,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xbc,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x00,0x01,0x00,0x00,
+0x06,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x01,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x01,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x01,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x03,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x03,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1d,0x01,0x00,0x00,
+0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x1e,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x4a,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4b,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x4b,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4b,0x01,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x4d,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x36,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7c,0x02,0x00,0x00,
+0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x7d,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x7f,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x7f,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
+0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x1e,0x00,0x10,0x00,0x12,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x13,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x12,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x13,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x15,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x16,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x17,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x0a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
+0x28,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x15,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x38,0x00,0x00,0x00,0x40,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x3f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x0a,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x50,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x54,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x55,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x38,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
+0x06,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
+0x38,0x00,0x00,0x00,0x54,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
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+0xa6,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x3d,0x02,0x00,0x00,
+0xa0,0x02,0x00,0x00,0x47,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
+0xc2,0x00,0x00,0x00,0x4a,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
+0x61,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x46,0x02,0x00,0x00,
+0x47,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0x4a,0x02,0x00,0x00,0x45,0x02,0x00,0x00,0x46,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x45,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x4e,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
+0x62,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x4f,0x02,0x00,0x00,0x25,0x02,0x00,0x00,0x4e,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x51,0x02,0x00,0x00,
+0x65,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x52,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,
+0x51,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x56,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xc5,0x01,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00,
+0x2b,0x02,0x00,0x00,0x56,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x59,0x02,0x00,0x00,0x69,0x00,0x00,0x00,
+0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x5a,0x02,0x00,0x00,0x57,0x02,0x00,0x00,0x59,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x5c,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
+0xa8,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,0x45,0x02,0x00,0x00,
+0x9e,0x02,0x00,0x00,0x5f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
+0xc2,0x00,0x00,0x00,0x62,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
+0xbc,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x5e,0x02,0x00,0x00,
+0x5f,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0x62,0x02,0x00,0x00,0x5d,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x5d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
+0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,
+0x3f,0x00,0x00,0x00,0x5d,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,
+0x67,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
+0x6a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
+0xf6,0x00,0x04,0x00,0x66,0x02,0x00,0x00,0x67,0x02,0x00,0x00,
+0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x6a,0x02,0x00,0x00,
+0x65,0x02,0x00,0x00,0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x65,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x6d,0x02,0x00,0x00,0x52,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
+0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0x70,0x02,0x00,0x00,
+0x6d,0x02,0x00,0x00,0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
+0x72,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0x70,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0x72,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x75,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
+0xa8,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
+0x76,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,
+0x76,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
+0x78,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x72,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,
+0x79,0x02,0x00,0x00,0x70,0x02,0x00,0x00,0x65,0x02,0x00,0x00,
+0x78,0x02,0x00,0x00,0x71,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,
+0x7b,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0x79,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x83,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,
+0xa8,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
+0x85,0x02,0x00,0x00,0x14,0x00,0x00,0x00,0x84,0x02,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x86,0x02,0x00,0x00,
+0x85,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x87,0x02,0x00,0x00,0x83,0x02,0x00,0x00,0x86,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,
+0x3a,0x02,0x00,0x00,0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x8a,0x02,0x00,0x00,0x88,0x02,0x00,0x00,
+0x52,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x8c,0x02,0x00,0x00,0x8a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,
+0xa5,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,
+0xa8,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x92,0x02,0x00,0x00,0x90,0x02,0x00,0x00,0x91,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,
+0xa6,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
+0x94,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x97,0x02,0x00,0x00,0x95,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
+0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,0x98,0x02,0x00,0x00,
+0xca,0x00,0x00,0x00,0x97,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
+0xc4,0x00,0x00,0x00,0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,
+0x41,0x00,0x06,0x00,0x05,0x01,0x00,0x00,0x9a,0x02,0x00,0x00,
+0x7f,0x02,0x00,0x00,0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
+0x3e,0x00,0x03,0x00,0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x7b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x9c,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x5f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,
+0xa8,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x47,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xa0,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x46,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xa2,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
+0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,
+0x38,0x00,0x01,0x00,
+};
+const uint64_t matmul_f32_f16_aligned_fp32_len = 10240;
+
+unsigned char matmul_f32_f16_fp32_data[] = {
+0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
+0xd5,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
+0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
+0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
+0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,
+0xfa,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x44,0x01,0x00,0x00,
+0x50,0x01,0x00,0x00,0x36,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
+0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x24,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x12,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x12,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x12,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x38,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x3e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1a,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x4d,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x50,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x54,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x61,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x63,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xb8,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xbb,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x02,0x01,0x00,0x00,
+0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x03,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x03,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x05,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x05,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x1e,0x01,0x00,0x00,
+0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x1f,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x4e,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x4e,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x4e,0x01,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x50,0x01,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x50,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x36,0x02,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x7c,0x02,0x00,0x00,
+0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
+0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x7d,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x7d,0x02,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x7f,0x02,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x7f,0x02,0x00,0x00,0x21,0x00,0x00,0x00,
 0x02,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
 0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
 0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
@@ -19124,156 +23698,146 @@ unsigned char matmul_f32_aligned_data[] = {
 0x06,0x00,0x00,0x00,0x6e,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
 0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
 0x06,0x00,0x00,0x00,0x73,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x79,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0x87,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x15,0x00,0x00,0x00,0x92,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0x98,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,
-0xa2,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0x40,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xb8,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xb9,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0x54,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0x50,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x32,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0xbd,0x00,0x00,0x00,0x61,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x86,0x00,0x00,0x00,0xba,0x00,0x00,0x00,0xbe,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,
-0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x14,0x00,0x02,0x00,0xc2,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0xc4,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0xc5,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0xc6,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0xc5,0x00,0x00,0x00,0xbf,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0xc6,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0xc8,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xc9,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0xc8,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xcd,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0xc4,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x15,0x00,0x00,0x00,0xd0,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0xf7,0x00,0x00,0x00,
-0x10,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0xf9,0x00,0x00,0x00,0x84,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0xf8,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,0xfa,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0xfb,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0xfb,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x04,0x01,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x05,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0x20,0x00,0x04,0x00,0x06,0x01,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x06,0x01,0x00,0x00,0x07,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x12,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x16,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,0x80,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0xf7,0x00,0x00,0x00,0x20,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x32,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x22,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x33,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,0x3a,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x24,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x25,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x26,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x41,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x46,0x01,0x00,0x00,0x80,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x46,0x01,0x00,0x00,0x1c,0x00,0x04,0x00,0x48,0x01,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
-0x49,0x01,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x01,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x49,0x01,0x00,0x00,0x4a,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x4d,0x01,0x00,0x00,
-0xc4,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x18,0x00,0x04,0x00,
-0x4e,0x01,0x00,0x00,0x4d,0x01,0x00,0x00,0x02,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x4f,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x50,0x01,0x00,0x00,0x4f,0x01,0x00,0x00,
-0x20,0x00,0x04,0x00,0x51,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x50,0x01,0x00,0x00,0x3b,0x00,0x04,0x00,0x51,0x01,0x00,0x00,
-0x52,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x67,0x01,0x00,0x00,0x03,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x6f,0x01,0x00,0x00,
-0x04,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x77,0x01,0x00,0x00,0x05,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x7f,0x01,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x87,0x01,0x00,0x00,
-0x07,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x8e,0x01,0x00,0x00,0x51,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
-0x00,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x8f,0x01,0x00,0x00,0x84,0x00,0x00,0x00,0x8e,0x01,0x00,0x00,
-0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x90,0x01,0x00,0x00,0x86,0x00,0x00,0x00,0x8f,0x01,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x93,0x01,0x00,0x00,0x08,0x01,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x94,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
 0x6d,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0x97,0x01,0x00,0x00,0x86,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x34,0x00,0x06,0x00,
-0x06,0x00,0x00,0x00,0xb2,0x01,0x00,0x00,0x84,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0x63,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0xb3,0x01,0x00,0x00,0xf7,0x00,0x00,0x00,0xb2,0x01,0x00,0x00,
-0x20,0x00,0x04,0x00,0xb4,0x01,0x00,0x00,0x07,0x00,0x00,0x00,
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-0xca,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xb4,0x01,0x00,0x00,0xb5,0x01,0x00,0x00,0x07,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0xe2,0x01,0x00,0x00,0xe3,0x01,0x00,0x00,
+0x05,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xc8,0x00,0x00,0x00,
+0xc9,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x8f,0x01,0x00,0x00,0x90,0x01,0x00,0x00,0x07,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0xbc,0x01,0x00,0x00,0xbd,0x01,0x00,0x00,
 0x07,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,
 0x0e,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
 0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
@@ -19333,1425 +23897,530 @@ unsigned char matmul_f32_aligned_data[] = {
 0x06,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
 0x6e,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
 0x74,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
-0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7a,0x00,0x00,0x00,
-0x4f,0x00,0x00,0x00,0x79,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
-0x7e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x82,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0x83,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x85,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x84,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x87,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x89,0x00,0x00,0x00,0x88,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
+0x89,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x79,0x00,0x00,0x00,
+0x4f,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0x86,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x4f,0x00,0x00,0x00,
+0x7d,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
+0x82,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x81,0x00,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
+0x82,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x84,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x83,0x00,0x00,0x00,
+0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
+0x14,0x00,0x00,0x00,0x86,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x88,0x00,0x00,0x00,0x87,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
 0x48,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,0x8b,0x00,0x00,0x00,
-0x84,0x00,0x00,0x00,0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x8e,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0x92,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x94,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x95,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x94,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x43,0x00,0x00,0x00,0x38,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x99,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x98,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,0x99,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x95,0x00,0x00,0x00,
-0x9b,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9e,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x00,0x00,0x00,
-0x9e,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
-0xa2,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x0f,0x00,0x00,0x00,
-0xa4,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xab,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xac,0x00,0x00,0x00,
-0xa8,0x00,0x00,0x00,0xab,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xad,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0xac,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xaf,0x00,0x00,0x00,0xad,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb0,0x00,0x00,0x00,
-0xaf,0x00,0x00,0x00,0x78,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xb2,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xc3,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,0xc1,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xb4,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
-0xb3,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xb3,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0xce,0x00,0x00,0x00,0xca,0x00,0x00,0x00,0xcb,0x02,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xce,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xd1,0x00,0x00,0x00,
-0xcb,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xb2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xb4,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0xd4,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd4,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0xe4,0x02,0x00,0x00,0xb0,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
-0x99,0x01,0x00,0x00,0xd7,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xe0,0x02,0x00,0x00,0x9f,0x00,0x00,0x00,
-0xb4,0x00,0x00,0x00,0x96,0x01,0x00,0x00,0xd7,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xcc,0x02,0x00,0x00,
-0x85,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,0x47,0x02,0x00,0x00,
-0xd7,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xdb,0x00,0x00,0x00,0xcc,0x02,0x00,0x00,0x8f,0x00,0x00,0x00,
-0xf6,0x00,0x04,0x00,0xd6,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xdb,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0xd6,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xd5,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
-0xd5,0x00,0x00,0x00,0x28,0x01,0x00,0x00,0xe0,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,
-0xdc,0x02,0x00,0x00,0x38,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0xdf,0x00,0x00,0x00,0xe0,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xe3,0x00,0x00,0x00,0xde,0x00,0x00,0x00,
-0xdf,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xde,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x74,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0xe7,0x00,0x00,0x00,
-0xdc,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc2,0x00,0x00,0x00,
-0xec,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xee,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xec,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xee,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xed,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0xcc,0x02,0x00,0x00,0x6f,0x00,0x00,0x00,0xb0,0x00,0x05,0x00,
-0xc2,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
-0x8f,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0xee,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0xee,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0xc2,0x00,0x00,0x00,0xf4,0x00,0x00,0x00,0xec,0x00,0x00,0x00,
-0xde,0x00,0x00,0x00,0xf3,0x00,0x00,0x00,0xed,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0xf6,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0xf4,0x00,0x00,0x00,0xf5,0x00,0x00,0x00,
-0x18,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0xf5,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xff,0x00,0x00,0x00,
-0x74,0x00,0x00,0x00,0xdc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00,0xff,0x00,0x00,0x00,
-0x00,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x0e,0x01,0x00,0x00,
-0xff,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,0xe0,0x02,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x11,0x01,0x00,0x00,0x0f,0x01,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0x12,0x01,0x00,0x00,0x13,0x01,0x00,0x00,
-0x07,0x01,0x00,0x00,0x35,0x00,0x00,0x00,0x11,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x13,0x01,0x00,0x00,0x73,0x00,0x04,0x00,0xf7,0x00,0x00,0x00,
-0x15,0x01,0x00,0x00,0x14,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x01,0x00,0x00,0x17,0x01,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x17,0x01,0x00,0x00,
-0x15,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0xf6,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x18,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x1b,0x01,0x00,0x00,0x74,0x00,0x00,0x00,
-0xdc,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x1b,0x01,0x00,0x00,0x1c,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x1f,0x01,0x00,0x00,
-0x1d,0x01,0x00,0x00,0x6f,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x16,0x01,0x00,0x00,0x21,0x01,0x00,0x00,0xfc,0x00,0x00,0x00,
-0x1f,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,0x21,0x01,0x00,0x00,
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-0x9d,0x02,0x00,0x00,0x9f,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x9a,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x9a,0x02,0x00,0x00,
-0xf5,0x00,0x07,0x00,0xc2,0x00,0x00,0x00,0xa1,0x02,0x00,0x00,
-0x98,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,0xa0,0x02,0x00,0x00,
-0x99,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0xa3,0x02,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xa1,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0xa2,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xab,0x02,0x00,0x00,0x82,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0xad,0x02,0x00,0x00,
-0x14,0x00,0x00,0x00,0xac,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xae,0x02,0x00,0x00,0xad,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xaf,0x02,0x00,0x00,
-0xab,0x02,0x00,0x00,0xae,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb0,0x02,0x00,0x00,0x62,0x02,0x00,0x00,
-0xaf,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb2,0x02,0x00,0x00,0xb0,0x02,0x00,0x00,0x7a,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,
-0xb2,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xb6,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,
-0xbc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xb6,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xba,0x02,0x00,0x00,
-0xb8,0x02,0x00,0x00,0xb9,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xbc,0x02,0x00,0x00,0xce,0x02,0x00,0x00,
+0x52,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,0x51,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x56,0x02,0x00,0x00,
+0xa5,0x02,0x00,0x00,0xc5,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x57,0x02,0x00,0x00,0x2b,0x02,0x00,0x00,
+0x56,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x59,0x02,0x00,0x00,0x69,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x5a,0x02,0x00,0x00,
+0x57,0x02,0x00,0x00,0x59,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,
+0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0xa8,0x02,0x00,0x00,
+0x3f,0x00,0x00,0x00,0x45,0x02,0x00,0x00,0x9e,0x02,0x00,0x00,
+0x5f,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,
+0x62,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,0xbb,0x00,0x00,0x00,
+0xf6,0x00,0x04,0x00,0x5e,0x02,0x00,0x00,0x5f,0x02,0x00,0x00,
+0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x62,0x02,0x00,0x00,
+0x5d,0x02,0x00,0x00,0x5e,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x5d,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0xf5,0x00,0x07,0x00,
+0x06,0x00,0x00,0x00,0xaa,0x02,0x00,0x00,0x3f,0x00,0x00,0x00,
+0x5d,0x02,0x00,0x00,0x9c,0x02,0x00,0x00,0x67,0x02,0x00,0x00,
+0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x6a,0x02,0x00,0x00,
+0xaa,0x02,0x00,0x00,0x63,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
+0x66,0x02,0x00,0x00,0x67,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0x6a,0x02,0x00,0x00,0x65,0x02,0x00,0x00,
+0x66,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x65,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x6d,0x02,0x00,0x00,
+0x52,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xb0,0x00,0x05,0x00,
+0xc1,0x00,0x00,0x00,0x70,0x02,0x00,0x00,0x6d,0x02,0x00,0x00,
+0x37,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x72,0x02,0x00,0x00,
+0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x70,0x02,0x00,0x00,
+0x71,0x02,0x00,0x00,0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x71,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x75,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
+0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x76,0x02,0x00,0x00,
+0x14,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x77,0x02,0x00,0x00,0x76,0x02,0x00,0x00,
+0xb0,0x00,0x05,0x00,0xc1,0x00,0x00,0x00,0x78,0x02,0x00,0x00,
+0x75,0x02,0x00,0x00,0x77,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x72,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x72,0x02,0x00,0x00,
+0xf5,0x00,0x07,0x00,0xc1,0x00,0x00,0x00,0x79,0x02,0x00,0x00,
+0x70,0x02,0x00,0x00,0x65,0x02,0x00,0x00,0x78,0x02,0x00,0x00,
+0x71,0x02,0x00,0x00,0xf7,0x00,0x03,0x00,0x7b,0x02,0x00,0x00,
+0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x79,0x02,0x00,0x00,
+0x7a,0x02,0x00,0x00,0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x7a,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x83,0x02,0x00,0x00,0x5a,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
+0x41,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x85,0x02,0x00,0x00,
+0x14,0x00,0x00,0x00,0x84,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x86,0x02,0x00,0x00,0x85,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,
+0x83,0x02,0x00,0x00,0x86,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x88,0x02,0x00,0x00,0x3a,0x02,0x00,0x00,
+0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x8a,0x02,0x00,0x00,0x88,0x02,0x00,0x00,0x52,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,
+0x8a,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x8e,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,
+0xbb,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x90,0x02,0x00,0x00,0x8e,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
+0x90,0x02,0x00,0x00,0x91,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0xa6,0x02,0x00,0x00,
 0x63,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xbd,0x02,0x00,0x00,0xba,0x02,0x00,0x00,0xbc,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xbf,0x02,0x00,0x00,
-0xbd,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0xcd,0x00,0x00,0x00,0xc0,0x02,0x00,0x00,0xca,0x00,0x00,0x00,
-0xbf,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,
-0xc1,0x02,0x00,0x00,0xc0,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
-0x12,0x01,0x00,0x00,0xc2,0x02,0x00,0x00,0xa7,0x02,0x00,0x00,
-0x35,0x00,0x00,0x00,0xb4,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
-0xc2,0x02,0x00,0x00,0xc1,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0xa3,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0xa3,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xc4,0x02,0x00,0x00,0xd2,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x8c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x8e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x87,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x87,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0xc6,0x02,0x00,0x00,0xd0,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x84,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x86,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6f,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xc8,0x02,0x00,0x00,
-0xce,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x6c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x6e,0x02,0x00,0x00,
+0x95,0x02,0x00,0x00,0x92,0x02,0x00,0x00,0x94,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x97,0x02,0x00,0x00,
+0x95,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
+0xcc,0x00,0x00,0x00,0x98,0x02,0x00,0x00,0xc9,0x00,0x00,0x00,
+0x97,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0xc3,0x00,0x00,0x00,
+0x99,0x02,0x00,0x00,0x98,0x02,0x00,0x00,0x41,0x00,0x06,0x00,
+0x10,0x01,0x00,0x00,0x9a,0x02,0x00,0x00,0x7f,0x02,0x00,0x00,
+0x35,0x00,0x00,0x00,0x8c,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,
+0x9a,0x02,0x00,0x00,0x99,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x7b,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x7b,0x02,0x00,0x00,
 0xf9,0x00,0x02,0x00,0x67,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
 0x67,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0xca,0x02,0x00,0x00,0xcd,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
+0x9c,0x02,0x00,0x00,0xaa,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
 0xf9,0x00,0x02,0x00,0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x66,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
+0x66,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x5f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x9e,0x02,0x00,0x00,0xa8,0x02,0x00,0x00,
+0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x5e,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x47,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x47,0x02,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xa0,0x02,0x00,0x00,
+0xa6,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x44,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x46,0x02,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x3f,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x3f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xa2,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xcf,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x3e,0x02,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
 
 };
-const uint64_t matmul_f32_aligned_len = 10932;
-
-unsigned char matmul_f32_aligned_fp32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0xd2,0x02,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0f,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0x06,0x01,0x00,0x00,
-0x47,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,0x33,0x02,0x00,0x00,
-0x7c,0x02,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
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-0xc2,0x00,0x00,0x00,0x76,0x02,0x00,0x00,0x6d,0x02,0x00,0x00,
-0x62,0x02,0x00,0x00,0x75,0x02,0x00,0x00,0x6e,0x02,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x78,0x02,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x76,0x02,0x00,0x00,0x77,0x02,0x00,0x00,
-0x78,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x77,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x80,0x02,0x00,0x00,
-0x57,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0x41,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x82,0x02,0x00,0x00,0x14,0x00,0x00,0x00,
-0x81,0x02,0x00,0x00,0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x83,0x02,0x00,0x00,0x82,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x84,0x02,0x00,0x00,0x80,0x02,0x00,0x00,
-0x83,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x85,0x02,0x00,0x00,0x37,0x02,0x00,0x00,0x84,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x87,0x02,0x00,0x00,
-0x85,0x02,0x00,0x00,0x4f,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x89,0x02,0x00,0x00,0x87,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x8b,0x02,0x00,0x00,0xa2,0x02,0x00,0x00,0xbc,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x8d,0x02,0x00,0x00,
-0x8b,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x8f,0x02,0x00,0x00,0x8d,0x02,0x00,0x00,
-0x8e,0x02,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x91,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,0x63,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x92,0x02,0x00,0x00,
-0x8f,0x02,0x00,0x00,0x91,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x94,0x02,0x00,0x00,0x92,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0x41,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0x95,0x02,0x00,0x00,0xca,0x00,0x00,0x00,0x94,0x02,0x00,0x00,
-0x3d,0x00,0x04,0x00,0xc4,0x00,0x00,0x00,0x96,0x02,0x00,0x00,
-0x95,0x02,0x00,0x00,0x41,0x00,0x06,0x00,0x11,0x01,0x00,0x00,
-0x97,0x02,0x00,0x00,0x7c,0x02,0x00,0x00,0x35,0x00,0x00,0x00,
-0x89,0x02,0x00,0x00,0x3e,0x00,0x03,0x00,0x97,0x02,0x00,0x00,
-0x96,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x78,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x78,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x64,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x64,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x99,0x02,0x00,0x00,
-0xa7,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x61,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x63,0x02,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x5c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5c,0x02,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x9b,0x02,0x00,0x00,0xa5,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x59,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x5b,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,0x44,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x44,0x02,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x9d,0x02,0x00,0x00,0xa3,0x02,0x00,0x00,
-0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x41,0x02,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x43,0x02,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x3c,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3c,0x02,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x9f,0x02,0x00,0x00,
-0xa2,0x02,0x00,0x00,0xd0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x39,0x02,0x00,0x00,0xf8,0x00,0x02,0x00,0x3b,0x02,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t matmul_f32_aligned_fp32_len = 10172;
+const uint64_t matmul_f32_f16_fp32_len = 10260;
 
 unsigned char matmul_f32_fp32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
@@ -75213,342 +78882,15 @@ const uint64_t rope_f32_len = 3072;
 
 unsigned char rope_neox_f16_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x5f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x75,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
 0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
 0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
 0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
 0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
 0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
 0x68,0x00,0x00,0x00,0x98,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0xcf,0x00,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x29,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x2a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x2a,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x2a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x2a,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x2a,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x68,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x95,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x96,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x96,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x96,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x98,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x98,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x9b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x9c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x9c,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x9c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x9e,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x9e,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xcc,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xcd,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x16,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
-0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x07,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x1b,0x00,0x00,0x00,0x6f,0x12,0x83,0x3a,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x00,0x00,0x80,0x3f,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
-0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
-0x1e,0x00,0x0c,0x00,0x2a,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x2a,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x2d,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x2f,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x2d,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0x39,0x00,0x00,0x00,
-0x05,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x3c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0x41,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,
-0x42,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x2d,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0xcd,0xcc,0xcc,0x3d,0x17,0x00,0x04,0x00,0x66,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x67,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x67,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
-0x69,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x6a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x73,0x00,0x00,0x00,
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-0x0c,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x57,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x56,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x58,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0x57,0x01,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x33,0x01,0x00,0x00,
-0x58,0x01,0x00,0x00,0x29,0x01,0x00,0x00,0x83,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x57,0x01,0x00,0x00,
-0x1f,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0x36,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x5d,0x01,0x00,0x00,0x29,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x39,0x01,0x00,0x00,
-0xe2,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,
-0x06,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
-0x32,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x36,0x01,0x00,0x00,
-0x39,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0xd8,0x00,0x00,0x00,
-0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x3e,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x3e,0x01,0x00,0x00,0x1f,0x00,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x23,0x01,0x00,0x00,
-0x40,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x43,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x43,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x5a,0x01,0x00,0x00,0x23,0x01,0x00,0x00,
-0x87,0x00,0x00,0x00,0x42,0x01,0x00,0x00,0x2b,0x01,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x59,0x01,0x00,0x00,
-0x26,0x01,0x00,0x00,0x87,0x00,0x00,0x00,0x3a,0x01,0x00,0x00,
-0x2b,0x01,0x00,0x00,0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,
-0x45,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
-0x59,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x47,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,
-0x0c,0x00,0x06,0x00,0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0d,0x00,0x00,0x00,0x59,0x01,0x00,0x00,
-0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4b,0x01,0x00,0x00,
-0x49,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xa1,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x42,0x00,0x00,0x00,0xb9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x94,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0xf1,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0xf7,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0xb9,0x00,0x00,0x00,0xf7,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xa1,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
-0x42,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x94,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
-0x73,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,
-0xfa,0x00,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x03,0x01,0x00,0x00,0xfb,0x00,0x00,0x00,0x4b,0x01,0x00,0x00,
-0x7f,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x5e,0x01,0x00,0x00,
-0x03,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0x04,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xf2,0x00,0x00,0x00,0x47,0x01,0x00,0x00,0x5e,0x01,0x00,0x00,
-0x73,0x00,0x04,0x00,0x94,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
-0x04,0x01,0x00,0x00,0x41,0x00,0x06,0x00,0xa1,0x00,0x00,0x00,
-0x06,0x01,0x00,0x00,0x98,0x00,0x00,0x00,0x42,0x00,0x00,0x00,
-0xb9,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x06,0x01,0x00,0x00,
-0x05,0x01,0x00,0x00,0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x11,0x01,0x00,0x00,0xfb,0x00,0x00,0x00,0x47,0x01,0x00,0x00,
-0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0x12,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xf2,0x00,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x11,0x01,0x00,0x00,0x73,0x00,0x04,0x00,
-0x94,0x00,0x00,0x00,0x13,0x01,0x00,0x00,0x12,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xa1,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
-0x98,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x14,0x01,0x00,0x00,0x13,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x17,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x17,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-
-};
-const uint64_t rope_neox_f16_len = 3876;
-
-unsigned char rope_neox_f32_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x5a,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
-0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
-0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0a,0x00,0x05,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x97,0x00,0x00,0x00,
-0x9d,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
+0xcf,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,0x10,0x00,0x06,0x00,
 0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
 0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
@@ -75568,51 +78910,61 @@ unsigned char rope_neox_f32_data[] = {
 0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
 0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
 0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x2a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x68,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x94,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x95,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x95,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x95,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x97,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x9a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x9b,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x9b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x9b,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x9d,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xcb,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xcc,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xce,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xce,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x11,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x2a,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x2a,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x68,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x95,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x96,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x96,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x96,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x98,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x98,0x00,0x00,0x00,
+0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x9b,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x9c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x9c,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x9c,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x9e,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x9e,0x00,0x00,0x00,
+0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xcc,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xcd,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0xcd,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xcf,0x00,0x00,0x00,
+0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xdc,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0xdd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xdd,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0xdd,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xdf,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xdf,0x00,0x00,0x00,
+0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x2b,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,
+0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
+0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
+0x07,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x1b,0x00,0x00,0x00,0x6f,0x12,0x83,0x3a,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x00,0x00,0x80,0x3f,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
 0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x6f,0x12,0x83,0x3a,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
-0x00,0x00,0x80,0x3f,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x07,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x28,0x00,0x00,0x00,0x1e,0x00,0x0c,0x00,0x2a,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,
+0x28,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x1c,0x00,0x04,0x00,
+0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x28,0x00,0x00,0x00,
+0x1e,0x00,0x0d,0x00,0x2a,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,
 0x09,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
 0x2b,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
 0x15,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
@@ -75637,228 +78989,614 @@ unsigned char rope_neox_f32_data[] = {
 0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
 0x6f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
 0x73,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x94,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x95,0x00,0x00,0x00,0x94,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x96,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x95,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x96,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x9a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x9b,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x9c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x9c,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xa0,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x2d,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0xc0,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xcb,0x00,0x00,0x00,
-0x2d,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xcc,0x00,0x00,0x00,
-0xcb,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xcd,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x16,0x00,0x03,0x00,0x94,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
+0x1d,0x00,0x03,0x00,0x95,0x00,0x00,0x00,0x94,0x00,0x00,0x00,
+0x1e,0x00,0x03,0x00,0x96,0x00,0x00,0x00,0x95,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x97,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x96,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x97,0x00,0x00,0x00,
+0x98,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0x9b,0x00,0x00,0x00,0x94,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
+0x9c,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x9d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x9c,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,0x9e,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xa1,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x94,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x2d,0x00,0x00,0x00,0xbc,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0xc1,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xcc,0x00,0x00,0x00,
+0x2d,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xcd,0x00,0x00,0x00,
+0xcc,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xce,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0xce,0x00,0x00,0x00,0xcf,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0xd1,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
 0x2d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,
-0xd9,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x07,0x00,0x00,0x00,0x10,0x01,0x00,0x00,0x00,0x01,0x00,0x00,
-0x2c,0x00,0x06,0x00,0x66,0x00,0x00,0x00,0x11,0x01,0x00,0x00,
-0x69,0x00,0x00,0x00,0x10,0x01,0x00,0x00,0x69,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x57,0x01,0x00,0x00,
-0x00,0x00,0x00,0x3f,0x36,0x00,0x05,0x00,0x02,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x12,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0xfb,0x00,0x03,0x00,
-0x6f,0x00,0x00,0x00,0x13,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x13,0x01,0x00,0x00,0x41,0x00,0x05,0x00,0x6a,0x00,0x00,0x00,
-0x6b,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x6b,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x6a,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x68,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x07,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x70,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x73,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x07,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x74,0x00,0x00,0x00,
-0xae,0x00,0x05,0x00,0x3c,0x00,0x00,0x00,0x76,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x78,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x76,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x78,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x77,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x12,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x78,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x73,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,
-0x2c,0x00,0x00,0x00,0x45,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x07,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,0x7c,0x00,0x00,0x00,
-0x86,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x6d,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,0x89,0x00,0x05,0x00,
-0x07,0x00,0x00,0x00,0x83,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x7d,0x00,0x00,0x00,0xac,0x00,0x05,0x00,0x3c,0x00,0x00,0x00,
-0x85,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
-0xf7,0x00,0x03,0x00,0x87,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x85,0x00,0x00,0x00,0x86,0x00,0x00,0x00,
-0x87,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x86,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,
-0x71,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
-0x07,0x00,0x00,0x00,0x90,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,
-0x7d,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0x91,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,0x90,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x91,0x00,0x00,0x00,0x83,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xa0,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x42,0x00,0x00,0x00,0x93,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,0xa1,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xa0,0x00,0x00,0x00,0xa3,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0x93,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xa3,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x93,0x00,0x00,0x00,0x69,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
-0xa0,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
-0x42,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,0xa8,0x00,0x00,0x00,
-0x41,0x00,0x06,0x00,0xa0,0x00,0x00,0x00,0xaa,0x00,0x00,0x00,
-0x97,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0xaa,0x00,0x00,0x00,0xa9,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x12,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x87,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
-0xb0,0x00,0x00,0x00,0x71,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x84,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0xb4,0x00,0x00,0x00,
+0xd5,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0xdc,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
+0xdd,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0xde,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0xde,0x00,0x00,0x00,0xdf,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xe2,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x2d,0x00,0x00,0x00,0xed,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,
+0x00,0x01,0x00,0x00,0x2c,0x00,0x06,0x00,0x66,0x00,0x00,0x00,
+0x2b,0x01,0x00,0x00,0x69,0x00,0x00,0x00,0x2a,0x01,0x00,0x00,
+0x69,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x72,0x01,0x00,0x00,0x00,0x00,0x00,0x3f,0x36,0x00,0x05,0x00,
+0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
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+0x28,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x2c,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x2c,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,
+0x38,0x00,0x01,0x00,
+};
+const uint64_t rope_neox_f16_len = 4300;
+
+unsigned char rope_neox_f32_data[] = {
+0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
+0x6f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
+0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
+0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x0f,0x00,0x0b,0x00,0x05,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
+0x2c,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x97,0x00,0x00,0x00,
+0x9d,0x00,0x00,0x00,0xce,0x00,0x00,0x00,0xde,0x00,0x00,0x00,
+0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x2a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x2a,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x2a,0x00,0x00,0x00,0x08,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x2c,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x30,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x2a,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x2a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x68,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x94,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x95,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x95,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x95,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x97,0x00,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x97,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x9a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0x9b,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x9b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x9b,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x9d,0x00,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x9d,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xcb,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xcc,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0xcc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xcc,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xce,0x00,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xce,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0xdb,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,0xdc,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0xdc,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0xdc,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xde,0x00,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0xde,0x00,0x00,0x00,0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x25,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
+0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x16,0x00,0x03,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x15,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
+0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x6f,0x12,0x83,0x3a,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,
+0x00,0x00,0x80,0x3f,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x07,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x1c,0x00,0x04,0x00,0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x28,0x00,0x00,0x00,0x1e,0x00,0x0d,0x00,0x2a,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x2b,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x2b,0x00,0x00,0x00,0x2c,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x2d,0x00,0x00,0x00,0x2e,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x2f,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,
+0x33,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x2d,0x00,0x00,0x00,0x39,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
+0x14,0x00,0x02,0x00,0x3c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x2d,0x00,0x00,0x00,0x41,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0x42,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,
+0x45,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,0xcd,0xcc,0xcc,0x3d,
+0x17,0x00,0x04,0x00,0x66,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x67,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x67,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x69,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x6a,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x07,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x73,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
+0x07,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x94,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x95,0x00,0x00,0x00,
+0x94,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x96,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x95,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x96,0x00,0x00,0x00,0x97,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x1d,0x00,0x03,0x00,0x9a,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x1e,0x00,0x03,0x00,0x9b,0x00,0x00,0x00,0x9a,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x9c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x9b,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x9c,0x00,0x00,0x00,
+0x9d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0xa0,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,0xbb,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x2d,0x00,0x00,0x00,
+0xc0,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0xcb,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
+0xcc,0x00,0x00,0x00,0xcb,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0xcd,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0xcc,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0xcd,0x00,0x00,0x00,0xce,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xd0,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x2d,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x2d,0x00,0x00,0x00,0xd4,0x00,0x00,0x00,0x0a,0x00,0x00,0x00,
+0x1d,0x00,0x03,0x00,0xdb,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x1e,0x00,0x03,0x00,0xdc,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0xdd,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0xdc,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xdd,0x00,0x00,0x00,
+0xde,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x2d,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,0x08,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x07,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
+0x00,0x01,0x00,0x00,0x2c,0x00,0x06,0x00,0x66,0x00,0x00,0x00,
+0x25,0x01,0x00,0x00,0x69,0x00,0x00,0x00,0x24,0x01,0x00,0x00,
+0x69,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x6c,0x01,0x00,0x00,0x00,0x00,0x00,0x3f,0x36,0x00,0x05,0x00,
+0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
+0xf7,0x00,0x03,0x00,0x26,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0xfb,0x00,0x03,0x00,0x6f,0x00,0x00,0x00,0x27,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x27,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
+0x6a,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,0x68,0x00,0x00,0x00,
+0x69,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x07,0x00,0x00,0x00,
+0x6c,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,0x84,0x00,0x05,0x00,
+0x07,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
+0x17,0x00,0x00,0x00,0x41,0x00,0x05,0x00,0x6a,0x00,0x00,0x00,
+0x70,0x00,0x00,0x00,0x68,0x00,0x00,0x00,0x6f,0x00,0x00,0x00,
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+0x52,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x52,0x01,0x00,0x00,
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+0x32,0x01,0x00,0x00,0xda,0x00,0x00,0x00,0x51,0x01,0x00,0x00,
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+0x41,0x00,0x06,0x00,0xa0,0x00,0x00,0x00,0x03,0x01,0x00,0x00,
 0x9d,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,
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-0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0x01,0x01,0x00,0x00,
-0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0xf0,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x59,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0xa0,0x00,0x00,0x00,0x02,0x01,0x00,0x00,0x97,0x00,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
+0x03,0x01,0x00,0x00,0x86,0x00,0x05,0x00,0x07,0x00,0x00,0x00,
+0x09,0x01,0x00,0x00,0x7d,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x07,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,
+0xb8,0x00,0x00,0x00,0x09,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
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+0x42,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,
+0x85,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x14,0x01,0x00,0x00,
+0x0c,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,0x7f,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x6e,0x01,0x00,0x00,0x14,0x01,0x00,0x00,
+0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,0x15,0x01,0x00,0x00,
+0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x04,0x01,0x00,0x00,
+0x56,0x01,0x00,0x00,0x6e,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
+0xa0,0x00,0x00,0x00,0x16,0x01,0x00,0x00,0x97,0x00,0x00,0x00,
 0x42,0x00,0x00,0x00,0xb8,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,
-0x02,0x01,0x00,0x00,0x01,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x0d,0x01,0x00,0x00,0xf8,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0xf0,0x00,0x00,0x00,0x46,0x01,0x00,0x00,0x0d,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0xa0,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
-0x97,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0xf6,0x00,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x0f,0x01,0x00,0x00,0x0e,0x01,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x12,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x12,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
+0x16,0x01,0x00,0x00,0x15,0x01,0x00,0x00,0x85,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x21,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,
+0x56,0x01,0x00,0x00,0x0c,0x00,0x08,0x00,0x06,0x00,0x00,0x00,
+0x22,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
+0x04,0x01,0x00,0x00,0x5a,0x01,0x00,0x00,0x21,0x01,0x00,0x00,
+0x41,0x00,0x06,0x00,0xa0,0x00,0x00,0x00,0x23,0x01,0x00,0x00,
+0x97,0x00,0x00,0x00,0x42,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,
+0x3e,0x00,0x03,0x00,0x23,0x01,0x00,0x00,0x22,0x01,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x26,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x26,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
 
 };
-const uint64_t rope_neox_f32_len = 3792;
+const uint64_t rope_neox_f32_len = 4200;
 
 unsigned char scale_f32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
@@ -76253,430 +79991,15 @@ const uint64_t silu_f32_len = 1264;
 
 unsigned char soft_max_f32_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x5c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x6f,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
 0x01,0x00,0x00,0x00,0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,
 0x47,0x4c,0x53,0x4c,0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,
 0x00,0x00,0x00,0x00,0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x0f,0x00,0x0d,0x00,0x05,0x00,0x00,0x00,
+0x01,0x00,0x00,0x00,0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00,
 0x04,0x00,0x00,0x00,0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,
 0x0b,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x5c,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,
-0xa3,0x00,0x00,0x00,0x09,0x01,0x00,0x00,0x10,0x00,0x06,0x00,
-0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x08,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x14,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x07,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x1c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x72,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x73,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x73,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x73,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x75,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x75,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x89,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0x8a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x8a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0x8a,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,
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-0xa0,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x04,0x00,0xa1,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0xa1,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x03,0x00,0xa1,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa3,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa3,0x00,0x00,0x00,
-0x21,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x06,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x07,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x07,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x09,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x09,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
-0x03,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x45,0x01,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
-0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
-0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
-0x16,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x1e,0x00,0x0a,0x00,
-0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x18,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x17,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x18,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x15,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,
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-0x37,0x01,0x00,0x00,0x30,0x01,0x00,0x00,0x31,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x30,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x3b,0x01,0x00,0x00,0x13,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x3d,0x01,0x00,0x00,0x3b,0x01,0x00,0x00,0x4c,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x7c,0x00,0x00,0x00,0x3f,0x01,0x00,0x00,
-0x09,0x01,0x00,0x00,0x6a,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x40,0x01,0x00,0x00,
-0x3f,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x41,0x01,0x00,0x00,0x40,0x01,0x00,0x00,0x2c,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x3f,0x01,0x00,0x00,0x41,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x44,0x01,0x00,0x00,
-0x4c,0x01,0x00,0x00,0x59,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x2f,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x31,0x01,0x00,0x00,
-0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
-};
-const uint64_t soft_max_f32_len = 4916;
-
-unsigned char soft_max_f32_f16_data[] = {
-0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
-0x61,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
-0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
-0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
-0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
-0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x0f,0x00,0x0d,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x11,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x75,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
+0x77,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,0xa2,0x00,0x00,0x00,
+0x0c,0x01,0x00,0x00,0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,
 0x11,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,
 0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,
 0x0b,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
@@ -76692,55 +80015,45 @@ unsigned char soft_max_f32_f16_data[] = {
 0x10,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,
 0x05,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x14,0x00,0x00,0x00,
 0x48,0x00,0x05,0x00,0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x17,0x00,0x00,0x00,0x07,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x1c,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x17,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x72,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x73,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x73,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x23,0x00,0x00,0x00,0x18,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
+0x17,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x74,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x75,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x75,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x75,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x77,0x00,0x00,0x00,
+0x21,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x8c,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x04,0x00,0x8d,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x18,0x00,0x00,0x00,0x48,0x00,0x05,0x00,0x8d,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x03,0x00,0x8d,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x8f,0x00,0x00,0x00,0x22,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8f,0x00,0x00,0x00,
+0x21,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x09,0x01,0x00,0x00,0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x48,0x00,0x05,0x00,0x0a,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x73,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x75,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x75,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x8a,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0x8b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0x8b,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0x8b,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x8d,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x8d,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0xa3,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x48,0x00,0x04,0x00,
-0xa4,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x18,0x00,0x00,0x00,
-0x48,0x00,0x05,0x00,0xa4,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x23,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,
-0xa4,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0xa6,0x00,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0xa6,0x00,0x00,0x00,0x21,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0b,0x01,0x00,0x00,
-0x06,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
-0x0c,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x47,0x00,0x03,0x00,0x0c,0x01,0x00,0x00,
-0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x0e,0x01,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
-0x0e,0x01,0x00,0x00,0x21,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x47,0x00,0x04,0x00,0x4a,0x01,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,0x02,0x00,0x00,0x00,
-0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
-0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,0x09,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,0x16,0x00,0x00,0x00,
-0x20,0x00,0x00,0x00,0x1e,0x00,0x0a,0x00,0x17,0x00,0x00,0x00,
-0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
+0x0a,0x01,0x00,0x00,0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,
+0x0c,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x0c,0x01,0x00,0x00,0x21,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x52,0x01,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x13,0x00,0x02,0x00,
+0x02,0x00,0x00,0x00,0x21,0x00,0x03,0x00,0x03,0x00,0x00,0x00,
+0x02,0x00,0x00,0x00,0x15,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x20,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x17,0x00,0x04,0x00,
+0x09,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x09,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x0d,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x06,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x0a,0x00,0x00,0x00,
+0x11,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x16,0x00,0x03,0x00,
+0x16,0x00,0x00,0x00,0x20,0x00,0x00,0x00,0x1e,0x00,0x09,0x00,
+0x17,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
 0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
 0x16,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
 0x18,0x00,0x00,0x00,0x09,0x00,0x00,0x00,0x17,0x00,0x00,0x00,
@@ -76750,56 +80063,49 @@ unsigned char soft_max_f32_f16_data[] = {
 0x1a,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
 0x20,0x00,0x04,0x00,0x1c,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
 0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x22,0x00,0x00,0x00,0x00,0x00,0x80,0x3f,0x2b,0x00,0x04,0x00,
+0x1a,0x00,0x00,0x00,0x23,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
 0x20,0x00,0x04,0x00,0x24,0x00,0x00,0x00,0x09,0x00,0x00,0x00,
-0x16,0x00,0x00,0x00,0x14,0x00,0x02,0x00,0x27,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x32,0x00,0x00,0x00,
-0x07,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x39,0x00,0x00,0x00,0x05,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x06,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
-0x4d,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x59,0x00,0x00,0x00,0x00,0x02,0x00,0x00,
-0x1c,0x00,0x04,0x00,0x5a,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
-0x59,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x5b,0x00,0x00,0x00,
-0x04,0x00,0x00,0x00,0x5a,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0x5b,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x60,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x16,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
+0x27,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x14,0x00,0x02,0x00,
+0x28,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
+0x33,0x00,0x00,0x00,0x06,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x1a,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
+0x05,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x4b,0x00,0x00,0x00,0x01,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x4e,0x00,0x00,0x00,0x02,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0x74,0x00,0x00,0x00,
+0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0x75,0x00,0x00,0x00,
+0x74,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x76,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x75,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
+0x76,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0x7e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
 0x16,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0x6a,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x72,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x73,0x00,0x00,0x00,0x72,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x74,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x73,0x00,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x74,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0x7c,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,
-0x1a,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0x03,0x00,0x00,0x00,
-0x16,0x00,0x03,0x00,0x89,0x00,0x00,0x00,0x10,0x00,0x00,0x00,
-0x1d,0x00,0x03,0x00,0x8a,0x00,0x00,0x00,0x89,0x00,0x00,0x00,
-0x1e,0x00,0x03,0x00,0x8b,0x00,0x00,0x00,0x8a,0x00,0x00,0x00,
-0x20,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x8b,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0x8c,0x00,0x00,0x00,
-0x8d,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
-0x94,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x89,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,0x9b,0x00,0x00,0x00,
-0x02,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,0xa3,0x00,0x00,0x00,
-0x89,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,0xa4,0x00,0x00,0x00,
-0xa3,0x00,0x00,0x00,0x20,0x00,0x04,0x00,0xa5,0x00,0x00,0x00,
-0x0c,0x00,0x00,0x00,0xa4,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,
-0xa5,0x00,0x00,0x00,0xa6,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,
-0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xb3,0x00,0x00,0x00,
+0x81,0x00,0x00,0x00,0x02,0x00,0x00,0x00,0x1d,0x00,0x03,0x00,
+0x8c,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
+0x8d,0x00,0x00,0x00,0x8c,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0x8e,0x00,0x00,0x00,0x0c,0x00,0x00,0x00,0x8d,0x00,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x8e,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x9d,0x00,0x00,0x00,0x00,0x02,0x00,0x00,0x1c,0x00,0x04,0x00,
+0xa0,0x00,0x00,0x00,0x16,0x00,0x00,0x00,0x9d,0x00,0x00,0x00,
+0x20,0x00,0x04,0x00,0xa1,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0xa0,0x00,0x00,0x00,0x3b,0x00,0x04,0x00,0xa1,0x00,0x00,0x00,
+0xa2,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x20,0x00,0x04,0x00,
+0xa5,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x16,0x00,0x00,0x00,
+0x2b,0x00,0x04,0x00,0x06,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,
 0x08,0x01,0x00,0x00,0x2b,0x00,0x04,0x00,0x1a,0x00,0x00,0x00,
-0xb6,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x1d,0x00,0x03,0x00,
-0x0b,0x01,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
-0x0c,0x01,0x00,0x00,0x0b,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
-0x0d,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x0c,0x01,0x00,0x00,
-0x3b,0x00,0x04,0x00,0x0d,0x01,0x00,0x00,0x0e,0x01,0x00,0x00,
+0xaa,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x1d,0x00,0x03,0x00,
+0x09,0x01,0x00,0x00,0x16,0x00,0x00,0x00,0x1e,0x00,0x03,0x00,
+0x0a,0x01,0x00,0x00,0x09,0x01,0x00,0x00,0x20,0x00,0x04,0x00,
+0x0b,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,
+0x3b,0x00,0x04,0x00,0x0b,0x01,0x00,0x00,0x0c,0x01,0x00,0x00,
 0x0c,0x00,0x00,0x00,0x2c,0x00,0x06,0x00,0x09,0x00,0x00,0x00,
-0x4a,0x01,0x00,0x00,0x59,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,
-0x4a,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x60,0x01,0x00,0x00,0x00,0x00,0x80,0xff,0x36,0x00,0x05,0x00,
+0x52,0x01,0x00,0x00,0x9d,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,
+0x4b,0x00,0x00,0x00,0x2b,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
+0x6e,0x01,0x00,0x00,0x00,0x00,0x80,0xff,0x36,0x00,0x05,0x00,
 0x02,0x00,0x00,0x00,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
 0x03,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x05,0x00,0x00,0x00,
 0x41,0x00,0x05,0x00,0x0d,0x00,0x00,0x00,0x0e,0x00,0x00,0x00,
@@ -76816,275 +80122,693 @@ unsigned char soft_max_f32_f16_data[] = {
 0x24,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
 0x23,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
 0x26,0x00,0x00,0x00,0x25,0x00,0x00,0x00,0xba,0x00,0x05,0x00,
-0x27,0x00,0x00,0x00,0x28,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
-0x22,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x2a,0x00,0x00,0x00,
-0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x28,0x00,0x00,0x00,
-0x29,0x00,0x00,0x00,0x2a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x29,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x2f,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x32,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0x33,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x27,0x00,0x00,0x00,0x35,0x00,0x00,0x00,
-0x2f,0x00,0x00,0x00,0x34,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x38,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x35,0x00,0x00,0x00,0x37,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x37,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x24,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
-0x39,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x3b,0x00,0x00,0x00,0x3a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x38,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x3c,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x24,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x3d,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x3f,0x00,0x00,0x00,0x3e,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x38,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x38,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x16,0x00,0x00,0x00,
-0x4b,0x01,0x00,0x00,0x3b,0x00,0x00,0x00,0x37,0x00,0x00,0x00,
-0x3f,0x00,0x00,0x00,0x3c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
-0x48,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x35,0x00,0x00,0x00,0x47,0x00,0x00,0x00,0x4c,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x47,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x4b,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,
-0x4a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x48,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x4c,0x00,0x00,0x00,0x82,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x51,0x00,0x00,0x00,0x2f,0x00,0x00,0x00,
-0x34,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0x4d,0x00,0x00,0x00,0x51,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x52,0x00,0x00,0x00,0x4a,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x48,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x48,0x00,0x00,0x00,
-0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,
-0x4b,0x00,0x00,0x00,0x47,0x00,0x00,0x00,0x53,0x00,0x00,0x00,
-0x4c,0x00,0x00,0x00,0x70,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
-0x57,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,0x0c,0x00,0x07,0x00,
-0x16,0x00,0x00,0x00,0x58,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0x1a,0x00,0x00,0x00,0x4b,0x01,0x00,0x00,0x57,0x00,0x00,0x00,
-0xf9,0x00,0x02,0x00,0x2a,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x2a,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x16,0x00,0x00,0x00,
-0x59,0x01,0x00,0x00,0x22,0x00,0x00,0x00,0x05,0x00,0x00,0x00,
-0x58,0x00,0x00,0x00,0x48,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
-0x60,0x00,0x00,0x00,0x61,0x00,0x00,0x00,0x5c,0x00,0x00,0x00,
-0x0f,0x00,0x00,0x00,0x3e,0x00,0x03,0x00,0x61,0x00,0x00,0x00,
-0x60,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x64,0x00,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x64,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,
-0x06,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,
-0x2a,0x00,0x00,0x00,0xb2,0x00,0x00,0x00,0x67,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x6a,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x06,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,0x6b,0x00,0x00,0x00,
-0xb0,0x00,0x05,0x00,0x27,0x00,0x00,0x00,0x6d,0x00,0x00,0x00,
-0x4d,0x01,0x00,0x00,0x6c,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
-0x66,0x00,0x00,0x00,0x67,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
-0xfa,0x00,0x04,0x00,0x6d,0x00,0x00,0x00,0x65,0x00,0x00,0x00,
-0x66,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0x65,0x00,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x71,0x00,0x00,0x00,
-0x61,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x79,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x6c,0x00,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,
-0x79,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
-0x7c,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,0x75,0x00,0x00,0x00,
-0x6a,0x00,0x00,0x00,0x7b,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x7e,0x00,0x00,0x00,0x7d,0x00,0x00,0x00,
-0x41,0x00,0x05,0x00,0x24,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0x19,0x00,0x00,0x00,0x7f,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
-0x16,0x00,0x00,0x00,0x81,0x00,0x00,0x00,0x80,0x00,0x00,0x00,
-0xac,0x00,0x05,0x00,0x27,0x00,0x00,0x00,0x85,0x00,0x00,0x00,
+0x28,0x00,0x00,0x00,0x29,0x00,0x00,0x00,0x26,0x00,0x00,0x00,
+0x27,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x2b,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x29,0x00,0x00,0x00,
+0x2a,0x00,0x00,0x00,0x2b,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x2a,0x00,0x00,0x00,0x86,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x30,0x00,0x00,0x00,0x13,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
+0x41,0x00,0x05,0x00,0x1c,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
+0x19,0x00,0x00,0x00,0x33,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x06,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0x34,0x00,0x00,0x00,
+0xb0,0x00,0x05,0x00,0x28,0x00,0x00,0x00,0x36,0x00,0x00,0x00,
+0x30,0x00,0x00,0x00,0x35,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
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+0xcc,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xd7,0x00,0x00,0x00,0x5d,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,
+0xae,0x00,0x05,0x00,0x28,0x00,0x00,0x00,0xdb,0x00,0x00,0x00,
+0xd7,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,
+0xdd,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0xdb,0x00,0x00,0x00,0xdc,0x00,0x00,0x00,0xdd,0x00,0x00,0x00,
+0xf8,0x00,0x02,0x00,0xdc,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xcd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xdd,0x00,0x00,0x00,
+0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,
+0x13,0x00,0x00,0x00,0x66,0x00,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,0xe3,0x00,0x00,0x00,
+0xd7,0x00,0x00,0x00,0x41,0x00,0x06,0x00,0x7e,0x00,0x00,0x00,
+0xe8,0x00,0x00,0x00,0x77,0x00,0x00,0x00,0x64,0x00,0x00,0x00,
+0xe5,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
+0xe9,0x00,0x00,0x00,0xe8,0x00,0x00,0x00,0x41,0x00,0x05,0x00,
+0x24,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0x19,0x00,0x00,0x00,
+0x81,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,
+0xeb,0x00,0x00,0x00,0xea,0x00,0x00,0x00,0xac,0x00,0x05,0x00,
+0x28,0x00,0x00,0x00,0xef,0x00,0x00,0x00,0x1e,0x00,0x00,0x00,
+0x0c,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0xf2,0x00,0x00,0x00,
+0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0xef,0x00,0x00,0x00,
+0xf1,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xf1,0x00,0x00,0x00,0x84,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0xf7,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,
+0xf7,0x00,0x00,0x00,0xd7,0x00,0x00,0x00,0x41,0x00,0x06,0x00,
+0x7e,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,0x8f,0x00,0x00,0x00,
+0x64,0x00,0x00,0x00,0xf9,0x00,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x16,0x00,0x00,0x00,0xfb,0x00,0x00,0x00,0xfa,0x00,0x00,0x00,
+0x85,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,
+0x58,0x01,0x00,0x00,0xfb,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xf2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xfd,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0xf2,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xf2,0x00,0x00,0x00,0xf5,0x00,0x07,0x00,0x16,0x00,0x00,0x00,
+0x61,0x01,0x00,0x00,0xfc,0x00,0x00,0x00,0xf1,0x00,0x00,0x00,
+0x27,0x00,0x00,0x00,0xfd,0x00,0x00,0x00,0x0c,0x00,0x08,0x00,
+0x16,0x00,0x00,0x00,0xff,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x32,0x00,0x00,0x00,0xe9,0x00,0x00,0x00,0xeb,0x00,0x00,0x00,
+0x61,0x01,0x00,0x00,0x83,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
+0x01,0x01,0x00,0x00,0xff,0x00,0x00,0x00,0xc7,0x00,0x00,0x00,
+0x0c,0x00,0x06,0x00,0x16,0x00,0x00,0x00,0x02,0x01,0x00,0x00,
+0x01,0x00,0x00,0x00,0x1b,0x00,0x00,0x00,0x01,0x01,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x06,0x01,0x00,0x00,
+0xa6,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
+0x07,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0x02,0x01,0x00,0x00,
+0x3e,0x00,0x03,0x00,0xa6,0x00,0x00,0x00,0x07,0x01,0x00,0x00,
+0x41,0x00,0x06,0x00,0x7e,0x00,0x00,0x00,0x0f,0x01,0x00,0x00,
+0x0c,0x01,0x00,0x00,0x64,0x00,0x00,0x00,0xe5,0x00,0x00,0x00,
+0x3e,0x00,0x03,0x00,0x0f,0x01,0x00,0x00,0x02,0x01,0x00,0x00,
+0xf9,0x00,0x02,0x00,0xce,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xce,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x11,0x01,0x00,0x00,0x5d,0x01,0x00,0x00,0x9d,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0xcb,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,
+0xcd,0x00,0x00,0x00,0xe0,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,
+0x4e,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x13,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x13,0x01,0x00,0x00,
+0xf5,0x00,0x07,0x00,0x1a,0x00,0x00,0x00,0x65,0x01,0x00,0x00,
+0xaa,0x00,0x00,0x00,0xcd,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,
+0x16,0x01,0x00,0x00,0xad,0x00,0x05,0x00,0x28,0x00,0x00,0x00,
+0x19,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0x64,0x00,0x00,0x00,
+0xf6,0x00,0x04,0x00,0x15,0x01,0x00,0x00,0x16,0x01,0x00,0x00,
+0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x19,0x01,0x00,0x00,
+0x14,0x01,0x00,0x00,0x15,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x14,0x01,0x00,0x00,0x7c,0x00,0x04,0x00,0x06,0x00,0x00,0x00,
+0x1c,0x01,0x00,0x00,0x65,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,
+0x28,0x00,0x00,0x00,0x1d,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,
+0x1c,0x01,0x00,0x00,0xf7,0x00,0x03,0x00,0x1f,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x1d,0x01,0x00,0x00,
+0x1e,0x01,0x00,0x00,0x1f,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x1e,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x24,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,0x1c,0x01,0x00,0x00,
+0x41,0x00,0x05,0x00,0xa5,0x00,0x00,0x00,0x25,0x01,0x00,0x00,
+0xa2,0x00,0x00,0x00,0x24,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x16,0x00,0x00,0x00,0x26,0x01,0x00,0x00,0x25,0x01,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x28,0x01,0x00,0x00,
+0xa6,0x00,0x00,0x00,0x81,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
+0x29,0x01,0x00,0x00,0x28,0x01,0x00,0x00,0x26,0x01,0x00,0x00,
+0x3e,0x00,0x03,0x00,0xa6,0x00,0x00,0x00,0x29,0x01,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x1f,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x1f,0x01,0x00,0x00,0xe0,0x00,0x04,0x00,0x4e,0x00,0x00,0x00,
+0x4e,0x00,0x00,0x00,0xa7,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x16,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x16,0x01,0x00,0x00,
+0xc3,0x00,0x05,0x00,0x1a,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,
+0x65,0x01,0x00,0x00,0x1b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x13,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x15,0x01,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x2f,0x01,0x00,0x00,
+0xc6,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x31,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x31,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,
+0x06,0x00,0x00,0x00,0x66,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,
+0x15,0x01,0x00,0x00,0x51,0x01,0x00,0x00,0x34,0x01,0x00,0x00,
+0xb0,0x00,0x05,0x00,0x28,0x00,0x00,0x00,0x39,0x01,0x00,0x00,
+0x66,0x01,0x00,0x00,0x66,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,
+0x33,0x01,0x00,0x00,0x34,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0x39,0x01,0x00,0x00,0x32,0x01,0x00,0x00,
+0x33,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x32,0x01,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,
+0x66,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,0xae,0x00,0x05,0x00,
+0x28,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,
+0x66,0x00,0x00,0x00,0xf7,0x00,0x03,0x00,0x43,0x01,0x00,0x00,
+0x00,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,0x41,0x01,0x00,0x00,
+0x42,0x01,0x00,0x00,0x43,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x42,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,0x33,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x43,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x48,0x01,0x00,0x00,0x13,0x00,0x00,0x00,
+0x66,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x4a,0x01,0x00,0x00,0x48,0x01,0x00,0x00,0x3d,0x01,0x00,0x00,
+0x41,0x00,0x06,0x00,0x7e,0x00,0x00,0x00,0x4c,0x01,0x00,0x00,
+0x0c,0x01,0x00,0x00,0x64,0x00,0x00,0x00,0x4a,0x01,0x00,0x00,
+0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x4d,0x01,0x00,0x00,
+0x4c,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
+0x4e,0x01,0x00,0x00,0x4d,0x01,0x00,0x00,0x2f,0x01,0x00,0x00,
+0x3e,0x00,0x03,0x00,0x4c,0x01,0x00,0x00,0x4e,0x01,0x00,0x00,
 0xf9,0x00,0x02,0x00,0x34,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
-0x34,0x01,0x00,0x00,0xf5,0x00,0x07,0x00,0x06,0x00,0x00,0x00,
-0x51,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,0x17,0x01,0x00,0x00,
-0x49,0x01,0x00,0x00,0x35,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,
-0x27,0x00,0x00,0x00,0x3c,0x01,0x00,0x00,0x51,0x01,0x00,0x00,
-0x6c,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x36,0x01,0x00,0x00,
-0x35,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
-0x3c,0x01,0x00,0x00,0x35,0x01,0x00,0x00,0x36,0x01,0x00,0x00,
-0xf8,0x00,0x02,0x00,0x35,0x01,0x00,0x00,0x84,0x00,0x05,0x00,
-0x06,0x00,0x00,0x00,0x40,0x01,0x00,0x00,0x13,0x00,0x00,0x00,
-0x6c,0x00,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
-0x42,0x01,0x00,0x00,0x40,0x01,0x00,0x00,0x51,0x01,0x00,0x00,
-0x41,0x00,0x06,0x00,0x7c,0x00,0x00,0x00,0x44,0x01,0x00,0x00,
-0x0e,0x01,0x00,0x00,0x6a,0x00,0x00,0x00,0x42,0x01,0x00,0x00,
-0x3d,0x00,0x04,0x00,0x16,0x00,0x00,0x00,0x45,0x01,0x00,0x00,
-0x44,0x01,0x00,0x00,0x88,0x00,0x05,0x00,0x16,0x00,0x00,0x00,
-0x46,0x01,0x00,0x00,0x45,0x01,0x00,0x00,0x31,0x01,0x00,0x00,
-0x3e,0x00,0x03,0x00,0x44,0x01,0x00,0x00,0x46,0x01,0x00,0x00,
-0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x49,0x01,0x00,0x00,
-0x51,0x01,0x00,0x00,0x59,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
-0x34,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x36,0x01,0x00,0x00,
+0x34,0x01,0x00,0x00,0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,
+0x51,0x01,0x00,0x00,0x66,0x01,0x00,0x00,0x9d,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x31,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
+0x33,0x01,0x00,0x00,0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
+
+};
+const uint64_t soft_max_f32_len = 4836;
+
+unsigned char soft_max_f32_f16_data[] = {
+0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
+0x73,0x01,0x00,0x00,0x00,0x00,0x00,0x00,0x11,0x00,0x02,0x00,
+0x01,0x00,0x00,0x00,0x11,0x00,0x02,0x00,0x51,0x11,0x00,0x00,
+0x0b,0x00,0x06,0x00,0x01,0x00,0x00,0x00,0x47,0x4c,0x53,0x4c,
+0x2e,0x73,0x74,0x64,0x2e,0x34,0x35,0x30,0x00,0x00,0x00,0x00,
+0x0e,0x00,0x03,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x0f,0x00,0x0c,0x00,0x05,0x00,0x00,0x00,0x04,0x00,0x00,0x00,
+0x6d,0x61,0x69,0x6e,0x00,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x11,0x00,0x00,0x00,0x19,0x00,0x00,0x00,0x77,0x00,0x00,0x00,
+0x90,0x00,0x00,0x00,0xa5,0x00,0x00,0x00,0x10,0x01,0x00,0x00,
+0x10,0x00,0x06,0x00,0x04,0x00,0x00,0x00,0x11,0x00,0x00,0x00,
+0x00,0x02,0x00,0x00,0x01,0x00,0x00,0x00,0x01,0x00,0x00,0x00,
+0x47,0x00,0x04,0x00,0x0b,0x00,0x00,0x00,0x0b,0x00,0x00,0x00,
+0x1b,0x00,0x00,0x00,0x47,0x00,0x04,0x00,0x11,0x00,0x00,0x00,
+0x0b,0x00,0x00,0x00,0x1a,0x00,0x00,0x00,0x48,0x00,0x05,0x00,
+0x17,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x23,0x00,0x00,0x00,
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+0x83,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x05,0x01,0x00,0x00,
+0x03,0x01,0x00,0x00,0xca,0x00,0x00,0x00,0x0c,0x00,0x06,0x00,
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+0x1b,0x00,0x00,0x00,0x05,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x16,0x00,0x00,0x00,0x0a,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,
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+0x13,0x01,0x00,0x00,0x06,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
+0xd1,0x00,0x00,0x00,0xf8,0x00,0x02,0x00,0xd1,0x00,0x00,0x00,
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+0x19,0x01,0x00,0x00,0x1a,0x01,0x00,0x00,0x01,0x00,0x00,0x00,
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+0x21,0x01,0x00,0x00,0x0f,0x00,0x00,0x00,0x20,0x01,0x00,0x00,
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+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x28,0x01,0x00,0x00,
+0x0f,0x00,0x00,0x00,0x20,0x01,0x00,0x00,0x41,0x00,0x05,0x00,
+0xa8,0x00,0x00,0x00,0x29,0x01,0x00,0x00,0xa5,0x00,0x00,0x00,
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+0x16,0x00,0x00,0x00,0x2c,0x01,0x00,0x00,0xa9,0x00,0x00,0x00,
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+0xaa,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x1a,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x1a,0x01,0x00,0x00,0xc3,0x00,0x05,0x00,
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+0x1b,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,0x17,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x19,0x01,0x00,0x00,0x3d,0x00,0x04,0x00,
+0x16,0x00,0x00,0x00,0x33,0x01,0x00,0x00,0xc9,0x00,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x35,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
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+0x6a,0x01,0x00,0x00,0x0c,0x00,0x00,0x00,0x19,0x01,0x00,0x00,
+0x55,0x01,0x00,0x00,0x38,0x01,0x00,0x00,0xb0,0x00,0x05,0x00,
+0x28,0x00,0x00,0x00,0x3d,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,
+0x66,0x00,0x00,0x00,0xf6,0x00,0x04,0x00,0x37,0x01,0x00,0x00,
+0x38,0x01,0x00,0x00,0x01,0x00,0x00,0x00,0xfa,0x00,0x04,0x00,
+0x3d,0x01,0x00,0x00,0x36,0x01,0x00,0x00,0x37,0x01,0x00,0x00,
+0xf8,0x00,0x02,0x00,0x36,0x01,0x00,0x00,0x80,0x00,0x05,0x00,
+0x06,0x00,0x00,0x00,0x41,0x01,0x00,0x00,0x6a,0x01,0x00,0x00,
+0x0f,0x00,0x00,0x00,0xae,0x00,0x05,0x00,0x28,0x00,0x00,0x00,
+0x45,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x66,0x00,0x00,0x00,
+0xf7,0x00,0x03,0x00,0x47,0x01,0x00,0x00,0x00,0x00,0x00,0x00,
+0xfa,0x00,0x04,0x00,0x45,0x01,0x00,0x00,0x46,0x01,0x00,0x00,
+0x47,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x46,0x01,0x00,0x00,
+0xf9,0x00,0x02,0x00,0x37,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,
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+0x4c,0x01,0x00,0x00,0x13,0x00,0x00,0x00,0x66,0x00,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x4e,0x01,0x00,0x00,
+0x4c,0x01,0x00,0x00,0x41,0x01,0x00,0x00,0x41,0x00,0x06,0x00,
+0x7e,0x00,0x00,0x00,0x50,0x01,0x00,0x00,0x10,0x01,0x00,0x00,
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+0x16,0x00,0x00,0x00,0x51,0x01,0x00,0x00,0x50,0x01,0x00,0x00,
+0x88,0x00,0x05,0x00,0x16,0x00,0x00,0x00,0x52,0x01,0x00,0x00,
+0x51,0x01,0x00,0x00,0x33,0x01,0x00,0x00,0x3e,0x00,0x03,0x00,
+0x50,0x01,0x00,0x00,0x52,0x01,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x38,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x38,0x01,0x00,0x00,
+0x80,0x00,0x05,0x00,0x06,0x00,0x00,0x00,0x55,0x01,0x00,0x00,
+0x6a,0x01,0x00,0x00,0xa0,0x00,0x00,0x00,0xf9,0x00,0x02,0x00,
+0x35,0x01,0x00,0x00,0xf8,0x00,0x02,0x00,0x37,0x01,0x00,0x00,
 0xfd,0x00,0x01,0x00,0x38,0x00,0x01,0x00,
 };
-const uint64_t soft_max_f32_f16_len = 5000;
+const uint64_t soft_max_f32_f16_len = 4904;
 
 unsigned char split_k_reduce_data[] = {
 0x03,0x02,0x23,0x07,0x00,0x05,0x01,0x00,0x0b,0x00,0x0d,0x00,
diff --git a/ggml-vulkan.cpp b/ggml-vulkan.cpp
index b9449be03..79ce1479f 100644
--- a/ggml-vulkan.cpp
+++ b/ggml-vulkan.cpp
@@ -114,6 +114,7 @@ struct vk_device {
     size_t idx;
 
     vk_matmul_pipeline pipeline_matmul_f32;
+    vk_matmul_pipeline pipeline_matmul_f32_f16;
     vk_matmul_pipeline pipeline_matmul_f16;
     vk_matmul_pipeline pipeline_matmul_f16_f32;
     vk_pipeline pipeline_matmul_split_k_reduce;
@@ -289,12 +290,12 @@ struct vk_op_rope_neox_push_constants {
     float corr_dims[4];
     float theta_scale;
     float inv_ndims;
+    uint32_t has_freq_facs;
 };
 
 struct vk_op_soft_max_push_constants {
     uint32_t KX;
     uint32_t KY;
-    uint32_t KZ;
     float scale;
     float max_bias;
     float m0;
@@ -304,7 +305,8 @@ struct vk_op_soft_max_push_constants {
 
 struct vk_op_argsort_push_constants {
     uint32_t ncols;
-    bool ascending;
+    uint32_t ncols_pad;
+    int32_t order;
 };
 
 // Allow pre-recording command buffers
@@ -375,13 +377,12 @@ struct ggml_backend_vk_context {
     vk_context * compute_ctx;
     vk_context * transfer_ctx;
 
-    bool disable;
     bool initialized;
 
     size_t idx;
 };
 
-struct vk_instance {
+struct vk_instance_t {
     vk::Instance instance;
 
     std::vector<size_t> device_indices;
@@ -423,7 +424,7 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
 typedef void (*ggml_vk_func_t)(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
 
 static bool vk_instance_initialized = false;
-static vk_instance vk_instance;
+static vk_instance_t vk_instance;
 
 GGML_CALL static void ggml_backend_vk_free(ggml_backend_t backend);
 
@@ -1013,6 +1014,7 @@ static void ggml_vk_load_shaders(ggml_backend_vk_context * ctx) {
     uint32_t s_align =  32;
 
     ctx->device->pipeline_matmul_f32 = std::make_shared<vk_matmul_pipeline_struct>();
+    ctx->device->pipeline_matmul_f32_f16 = std::make_shared<vk_matmul_pipeline_struct>();
     ctx->device->pipeline_matmul_f16_f32 = std::make_shared<vk_matmul_pipeline_struct>();
     ctx->device->pipeline_matmul_f16 = std::make_shared<vk_matmul_pipeline_struct>();
     ctx->device->pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0] = std::make_shared<vk_matmul_pipeline_struct>();
@@ -1048,6 +1050,13 @@ static void ggml_vk_load_shaders(ggml_backend_vk_context * ctx) {
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align);
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_len, matmul_f32_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align);
 
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->l, "matmul_f32_f16_l", matmul_f32_f16_len, matmul_f32_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->m, "matmul_f32_f16_m", matmul_f32_f16_len, matmul_f32_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->s, "matmul_f32_f16_s", matmul_f32_f16_len, matmul_f32_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->a_l, "matmul_f32_f16_aligned_l", matmul_f32_f16_aligned_len, matmul_f32_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->a_m, "matmul_f32_f16_aligned_m", matmul_f32_f16_aligned_len, matmul_f32_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->a_s, "matmul_f32_f16_aligned_s", matmul_f32_f16_aligned_len, matmul_f32_f16_aligned_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align);
+
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1);
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1);
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_len, matmul_f16_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1);
@@ -1230,6 +1239,13 @@ static void ggml_vk_load_shaders(ggml_backend_vk_context * ctx) {
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_m, "matmul_f32_aligned_m", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align);
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32->a_s, "matmul_f32_aligned_s", matmul_f32_aligned_fp32_len, matmul_f32_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align);
 
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->l, "matmul_f32_f16_l", matmul_f32_f16_fp32_len, matmul_f32_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->m, "matmul_f32_f16_m", matmul_f32_f16_fp32_len, matmul_f32_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->s, "matmul_f32_f16_s", matmul_f32_f16_fp32_len, matmul_f32_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->a_l, "matmul_f32_f16_aligned_l", matmul_f32_f16_aligned_fp32_len, matmul_f32_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, l_align);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->a_m, "matmul_f32_f16_aligned_m", matmul_f32_f16_aligned_fp32_len, matmul_f32_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, m_align);
+        ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f32_f16->a_s, "matmul_f32_f16_aligned_s", matmul_f32_f16_aligned_fp32_len, matmul_f32_f16_aligned_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, s_align);
+
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->l, "matmul_f16_l", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), l_wg_denoms, warptile_l, 1);
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->m, "matmul_f16_m", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), m_wg_denoms, warptile_m, 1);
         ggml_vk_create_pipeline(ctx, ctx->device->pipeline_matmul_f16->s, "matmul_f16_s", matmul_f16_fp32_len, matmul_f16_fp32_data, "main", 3, sizeof(vk_mat_mat_push_constants), s_wg_denoms, warptile_s, 1);
@@ -1501,14 +1517,14 @@ static void ggml_vk_load_shaders(ggml_backend_vk_context * ctx) {
 
     ggml_vk_create_pipeline(ctx, ctx->device->pipeline_diag_mask_inf_f32, "diag_mask_inf_f32", diag_mask_inf_f32_len, diag_mask_inf_f32_data, "main", 2, sizeof(vk_op_diag_mask_push_constants), {512, 1, 1}, {}, 1);
 
-    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32, "soft_max_f32", soft_max_f32_len, soft_max_f32_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1);
-    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32_f16, "soft_max_f32_f16", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1);
+    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32, "soft_max_f32", soft_max_f32_len, soft_max_f32_data, "main", 3, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1);
+    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_soft_max_f32_f16, "soft_max_f32_f16", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 3, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, {}, 1);
 
     ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_f32, "rope_f32", rope_f32_len, rope_f32_data, "main", 3, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
     ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_f16, "rope_f16", rope_f16_len, rope_f16_data, "main", 3, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
 
-    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 3, sizeof(vk_op_rope_neox_push_constants), {1, 512, 1}, {}, 1);
-    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 3, sizeof(vk_op_rope_neox_push_constants), {1, 512, 1}, {}, 1);
+    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 4, sizeof(vk_op_rope_neox_push_constants), {1, 512, 1}, {}, 1);
+    ggml_vk_create_pipeline(ctx, ctx->device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 4, sizeof(vk_op_rope_neox_push_constants), {1, 512, 1}, {}, 1);
 
     ggml_vk_create_pipeline(ctx, ctx->device->pipeline_argsort_f32, "argsort_f32", argsort_f32_len, argsort_f32_data, "main", 2, sizeof(vk_op_argsort_push_constants), {1024, 1, 1}, {}, 1);
 }
@@ -1859,7 +1875,6 @@ static void ggml_vk_init(ggml_backend_vk_context * ctx, size_t idx) {
     ctx->compute_ctx = nullptr;
     ctx->transfer_ctx = nullptr;
 
-    ctx->disable = false;
     ctx->initialized = true;
 
     ctx->idx = idx;
@@ -1903,6 +1918,9 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte
     if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) {
         return ctx->device->pipeline_matmul_f32;
     }
+    if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F16) {
+        return ctx->device->pipeline_matmul_f32_f16;
+    }
     if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F32) {
         return ctx->device->pipeline_matmul_f16_f32;
     }
@@ -2722,7 +2740,7 @@ static void ggml_vk_matmul(
         uint32_t batch_stride_a, uint32_t batch_stride_b, uint32_t batch_stride_d,
         uint32_t expert_stride_b, uint32_t expert_stride_d, uint32_t idx, uint32_t nbi1, uint32_t n_as) {
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), c: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << split_k_buffer.buffer->buffer << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ")" << std::endl;
+    std::cerr << "ggml_vk_matmul(a: (" << a.buffer->buffer << ", " << a.offset << ", " << a.size << "), b: (" << b.buffer->buffer << ", " << b.offset << ", " << b.size << "), c: (" << d.buffer->buffer << ", " << d.offset << ", " << d.size << "), split_k: (" << (split_k_buffer.buffer != nullptr ? split_k_buffer.buffer->buffer : VK_NULL_HANDLE) << ", " << split_k_buffer.offset << ", " << split_k_buffer.size << "), m: " << m << ", n: " << n << ", k: " << k << ", stride_a: " << stride_a << ", stride_b: " << stride_b << ", stride_d: " << stride_d << ", split_k: " << split_k << ", batch: " << batch << ", ne02: " << ne02 << ", ne12: " << ne12 << ", broadcast2: " << broadcast2 << ", broadcast3: " << broadcast3 << ", batch_stride_a: " << batch_stride_a << ", batch_stride_b: " << batch_stride_b << ", batch_stride_d: " << batch_stride_d << ")" << std::endl;
 #endif
     ggml_vk_sync_buffers(subctx);
     if (split_k == 1) {
@@ -2792,7 +2810,7 @@ static vk_pipeline ggml_vk_get_cpy_pipeline(ggml_backend_vk_context * ctx, ggml_
 
 static void ggml_vk_cpy_to_contiguous(ggml_backend_vk_context * ctx, vk_context * subctx, vk_pipeline pipeline, const ggml_tensor * tensor, vk_subbuffer&& in, vk_subbuffer&& out) {
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_cpy_to_contiguous((" << tensor << ", type=" << tensor->type << ", backend=" << tensor->backend << ", ne0=" << tensor->ne[0] << ", ne1=" << tensor->ne[1] << ", ne2=" << tensor->ne[2] << ", ne3=" << tensor->ne[3] << ", nb0=" << tensor->nb[0] << ", nb1=" << tensor->nb[1] << ", nb2=" << tensor->nb[2] << ", nb3=" << tensor->nb[3] << "), ";
+    std::cerr << "ggml_vk_cpy_to_contiguous((" << tensor << ", type=" << tensor->type << ", ne0=" << tensor->ne[0] << ", ne1=" << tensor->ne[1] << ", ne2=" << tensor->ne[2] << ", ne3=" << tensor->ne[3] << ", nb0=" << tensor->nb[0] << ", nb1=" << tensor->nb[1] << ", nb2=" << tensor->nb[2] << ", nb3=" << tensor->nb[3] << "), ";
     std::cerr << "buffer in size=" << in.buffer->size << ", buffer out size=" << out.buffer->size << ")" << std::endl;
 #endif
     const int tensor_type_size = ggml_type_size(tensor->type);
@@ -2812,9 +2830,9 @@ static void ggml_vk_cpy_to_contiguous(ggml_backend_vk_context * ctx, vk_context
 
 static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_mul_mat_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
-    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
-    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
+    std::cerr << "ggml_vk_mul_mat_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
+    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
+    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
 #endif
     GGML_ASSERT(ggml_vk_dim01_contiguous(src0) || src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);  // NOLINT
     GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16);  // NOLINT
@@ -2982,19 +3000,13 @@ static void ggml_vk_mul_mat_q_f16(ggml_backend_vk_context * ctx, vk_context * su
         ne01, ne11, ne10, ne10, ne10, ne01, split_k, ne12*ne13, ne02, ne12, r2, r3, stride_batch_x, stride_batch_y, ne20*ne21,
         0, 0, 0, 0, 1
     );  // NOLINT
-
-    if (dst->backend == GGML_BACKEND_TYPE_CPU) {
-        // copy dst to host
-        float * d = (float *) ((char *) dst->data);
-        ggml_vk_buffer_read_async(ctx, subctx, d_D, 0, d, sizeof(float) * d_ne * ne12 * ne13);
-    }
 }
 
 static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_mul_mat_vec_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ",  backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
-    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ",  backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
-    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ",  backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
+    std::cerr << "ggml_vk_mul_mat_vec_q_f16((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
+    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
+    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
 #endif
     GGML_ASSERT(ggml_vk_dim01_contiguous(src0) || src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);  // NOLINT
     GGML_ASSERT(ggml_vk_dim01_contiguous(src1) || src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16);  // NOLINT
@@ -3147,12 +3159,11 @@ static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context
 
 static void ggml_vk_mul_mat_vec_p021_f16_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_mul_mat_p021_f16_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ",  backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
-    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ",  backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
-    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ",  backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
+    std::cerr << "ggml_vk_mul_mat_p021_f16_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
+    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
+    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
 #endif
     GGML_ASSERT(ggml_is_permuted(src0) && ggml_is_permuted(src1));
-    GGML_ASSERT(src0->backend == GGML_BACKEND_TYPE_GPU);
     GGML_ASSERT(src0->nb[0] <= src0->nb[1] && src0->nb[2] <= src0->nb[3]);  // NOLINT
     GGML_ASSERT(src1->nb[0] <= src1->nb[1] && src1->nb[2] <= src1->nb[3]);  // NOLINT
     GGML_ASSERT(src0->type == GGML_TYPE_F16);
@@ -3217,25 +3228,17 @@ static void ggml_vk_mul_mat_vec_p021_f16_f32(ggml_backend_vk_context * ctx, vk_c
     const std::array<uint32_t, 6> pc = { (uint32_t)ne00, (uint32_t)ne01, (uint32_t)ne02, (uint32_t)ne12, (uint32_t)(qy_shader_offset / ggml_type_size(src1->type)), (uint32_t)(d_shader_offset / ggml_type_size(dst->type)) };
     ggml_vk_sync_buffers(subctx);
     ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_mul_mat_vec_p021_f16_f32, { { d_Qx, qx_buf_offset, qx_sz }, { d_Qy, qy_buffer_offset, qy_sz + qy_shader_offset }, { d_D, d_buffer_offset, d_sz + d_shader_offset } }, 6 * sizeof(uint32_t), &pc, { 1, (uint32_t)ne01, (uint32_t)ne12 });
-
-    if (dst->backend == GGML_BACKEND_TYPE_CPU) {
-        // copy dst to host
-        float * d = (float *) dst->data;
-        ggml_vk_sync_buffers(subctx);
-        ggml_vk_buffer_read_async(ctx, subctx, d_D, d_buf_offset, d, sizeof(float) * d_ne);
-    }
 }
 
 static void ggml_vk_mul_mat_vec_nc_f16_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_mul_mat_nc_f16_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ",  backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
-    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ",  backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
-    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ",  backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
+    std::cerr << "ggml_vk_mul_mat_nc_f16_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
+    std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
+    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "),)" << std::endl;
 #endif
     GGML_ASSERT(!ggml_is_transposed(src0));
     GGML_ASSERT(!ggml_is_transposed(src1));
     GGML_ASSERT(!ggml_is_permuted(src0));
-    GGML_ASSERT(src0->backend == GGML_BACKEND_TYPE_GPU);
     GGML_ASSERT(src0->type == GGML_TYPE_F16);
     GGML_ASSERT(src1->type == GGML_TYPE_F32);
 
@@ -3302,26 +3305,6 @@ static void ggml_vk_mul_mat_vec_nc_f16_f32(ggml_backend_vk_context * ctx, vk_con
     const std::array<uint32_t, 7> pc = { (uint32_t)ne00, (uint32_t)ne01, row_stride_x, channel_stride_x, (uint32_t)(ne12 / ne02), (uint32_t)(qy_shader_offset / ggml_type_size(src1->type)), (uint32_t)(d_shader_offset / ggml_type_size(dst->type)) };
     ggml_vk_sync_buffers(subctx);
     ggml_vk_dispatch_pipeline(ctx, subctx, ctx->device->pipeline_mul_mat_vec_nc_f16_f32, { { d_Qx, qx_buf_offset, qx_sz }, { d_Qy, qy_buffer_offset, qy_sz + qy_shader_offset }, { d_D, d_buffer_offset, d_sz + d_shader_offset } }, 7 * sizeof(uint32_t), &pc, { 1, (uint32_t)ne01, (uint32_t)ne12 });
-
-    if (dst->backend == GGML_BACKEND_TYPE_CPU) {
-        // copy dst to host
-        float * d = (float *) dst->data;
-        ggml_vk_sync_buffers(subctx);
-        ggml_vk_buffer_read_async(ctx, subctx, d_D, d_buf_offset, d, sizeof(float) * d_ne);
-    }
-}
-
-static bool ggml_vk_can_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * dst) {
-    const uint64_t ne10 = src1->ne[0];
-
-    const uint64_t ne0 = dst->ne[0];
-    const uint64_t ne1 = dst->ne[1];
-
-    // TODO: find the optimal values for these
-    return (src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type)) &&
-           (src1->type == GGML_TYPE_F32 || src1->type == GGML_TYPE_F16 || ggml_is_quantized(src1->type)) &&
-           dst->type == GGML_TYPE_F32 &&
-           ((ne0 >= 32 && ne1 >= 32 && ne10 >= 32) || src0->backend == GGML_BACKEND_TYPE_GPU);
 }
 
 static void ggml_vk_mul_mat(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
@@ -3711,8 +3694,6 @@ static void ggml_vk_op_repeat(ggml_backend_vk_context * ctx, vk_context * subctx
     // TODO: support for transposed / permuted tensors
     GGML_ASSERT(nb0  == sizeof(float));
     GGML_ASSERT(nb00 == sizeof(float));
-    GGML_ASSERT(src0->backend == GGML_BACKEND_TYPE_GPU);
-    GGML_ASSERT(dst->backend == GGML_BACKEND_TYPE_GPU);
 
     ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) dst->extra;
     ggml_tensor_extra_gpu * extra_src0 = (ggml_tensor_extra_gpu *) src0->extra;
@@ -3834,7 +3815,7 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
         if (src0->type == GGML_TYPE_F32 && (src1 == nullptr || src1->type == GGML_TYPE_F32) && dst->type == GGML_TYPE_F32) {
             return ctx->device->pipeline_soft_max_f32;
         }
-        if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16 && src2->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F32) {
+        if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F32) {
             return ctx->device->pipeline_soft_max_f32_f16;
         }
         return nullptr;
@@ -3873,6 +3854,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
     default:
         return nullptr;
     }
+
+    GGML_UNUSED(src2);
 }
 
 static ggml_vk_func_t ggml_vk_op_get_func(ggml_op op) {
@@ -3902,14 +3885,14 @@ static bool ggml_vk_op_supports_incontiguous(ggml_op op) {
 template<typename PC>
 static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, ggml_op op, const PC&& pc) {
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_op_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", backend=" << src0->backend << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
+    std::cerr << "ggml_vk_op_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
     if (src1 != nullptr) {
-        std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", backend=" << src1->backend << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
+        std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
     }
     if (src2 != nullptr) {
-        std::cerr << "), (" << src2 << ", name=" << src2->name << ", type=" << src2->type << ", backend=" << src2->backend << ", ne0=" << src2->ne[0] << ", ne1=" << src2->ne[1] << ", ne2=" << src2->ne[2] << ", ne3=" << src2->ne[3] << ", nb0=" << src2->nb[0] << ", nb1=" << src2->nb[1] << ", nb2=" << src2->nb[2] << ", nb3=" << src2->nb[3];
+        std::cerr << "), (" << src2 << ", name=" << src2->name << ", type=" << src2->type << ", ne0=" << src2->ne[0] << ", ne1=" << src2->ne[1] << ", ne2=" << src2->ne[2] << ", ne3=" << src2->ne[3] << ", nb0=" << src2->nb[0] << ", nb1=" << src2->nb[1] << ", nb2=" << src2->nb[2] << ", nb3=" << src2->nb[3];
     }
-    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", backend=" << dst->backend << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "), " << ggml_op_name(op) << ")" << std::endl;
+    std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3] << "), " << ggml_op_name(op) << ")" << std::endl;
 #endif
     GGML_ASSERT(op == GGML_OP_GET_ROWS || (!ggml_is_quantized(src0->type) && (src1 == nullptr || !ggml_is_quantized(src1->type))));  // NOLINT
     GGML_ASSERT(op == GGML_OP_CPY || ggml_vk_dim01_contiguous(src0));  // NOLINT
@@ -3919,6 +3902,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
     const uint64_t ne02 = src0->ne[2];
     const uint64_t ne03 = src0->ne[3];
     const uint64_t ne0 = ne00 * ne01;
+
     const bool use_src1 = src1 != nullptr;
     const uint64_t ne10 = use_src1 ? src1->ne[0] : 0;
     const uint64_t ne11 = use_src1 ? src1->ne[1] : 0;
@@ -3926,11 +3910,13 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
     const uint64_t ne13 = use_src1 ? src1->ne[3] : 0;
     const uint64_t ne1 = ne10 * ne11;
     // const uint64_t nb10 = use_src1 ? src1->nb[0] : 0;
-    const uint64_t nb2  = dst->nb[2];
-    const uint64_t nb3  = dst->nb[3];
 
     const bool use_src2 = src2 != nullptr;
-    const uint64_t ne2 = use_src2 ? src2->ne[0] * src2->ne[1] : 0;
+    const uint64_t ne20 = use_src2 ? src2->ne[0] : 0;
+    const uint64_t ne21 = use_src2 ? src2->ne[1] : 0;
+    const uint64_t ne22 = use_src2 ? src2->ne[2] : 0;
+    const uint64_t ne23 = use_src2 ? src2->ne[3] : 0;
+    const uint64_t ne2 = ne20 * ne21;
 
     vk_pipeline pipeline = ggml_vk_op_get_pipeline(ctx, src0, src1, src2, dst, op);
     ggml_vk_func_t op_func;
@@ -3976,7 +3962,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
             src1_uma = d_Y != nullptr;
         }
         if (use_src2) {
-            ggml_vk_host_get(ctx, src1->data, d_Z, z_buf_offset);
+            ggml_vk_host_get(ctx, src2->data, d_Z, z_buf_offset);
             src2_uma = d_Z != nullptr;
         }
     }
@@ -3989,7 +3975,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
     vk_buffer d_D = extra->buffer_gpu.lock();
 
     // Workaround for tiny tensor inputs on ROPE
-    if (use_src1 && src1->backend == GGML_BACKEND_TYPE_GPU && y_sz > d_D->size) {
+    if (use_src1 && y_sz > d_D->size) {
         y_sz = VK_WHOLE_SIZE;
     }
 
@@ -4006,7 +3992,6 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
         y_buf_offset = extra_src1->offset;
         GGML_ASSERT(d_Y != nullptr);
     }
-
     if (use_src2 && !src2_uma) {
         d_Z = extra_src2->buffer_gpu.lock();
         z_buf_offset = extra_src2->offset;
@@ -4016,6 +4001,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
     if (op_supports_incontiguous) {
         x_sz = ggml_nbytes(src0);
         y_sz = use_src1 ? ggml_nbytes(src1) : 0;
+        z_sz = use_src2 ? ggml_nbytes(src2) : 0;
         d_sz = ggml_nbytes(dst);
 
         if (x_buf_offset + x_sz >= d_X->size) {
@@ -4024,6 +4010,9 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
         if (use_src1 && y_buf_offset + y_sz >= d_Y->size) {
             y_sz = VK_WHOLE_SIZE;
         }
+        if (use_src2 && z_buf_offset + z_sz >= d_Z->size) {
+            z_sz = VK_WHOLE_SIZE;
+        }
         if (d_buf_offset + d_sz >= d_D->size) {
             d_sz = VK_WHOLE_SIZE;
         }
@@ -4046,7 +4035,10 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
             elements = { (uint32_t)ggml_nrows(src0), (uint32_t)ne00, 1 };
             break;
         case GGML_OP_GET_ROWS:
-            elements = {  (uint32_t)ne00, (uint32_t)ne10, (uint32_t)(ne11 * ne12) };
+            elements = { (uint32_t)ne00, (uint32_t)ne10, (uint32_t)(ne11 * ne12) };
+            break;
+        case GGML_OP_ARGSORT:
+            elements = { (uint32_t)ne00, (uint32_t)ggml_nrows(src0), 1 };
             break;
         default:
             elements = { (uint32_t)ggml_nelements(src0), 1, 1 };
@@ -4060,13 +4052,16 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
             if (use_src1 && y_sz != VK_WHOLE_SIZE) {
                 y_sz *= ne12 * ne13;
             }
+            if (use_src2 && z_sz != VK_WHOLE_SIZE) {
+                z_sz *= ne22 * ne23;
+            }
             if (d_sz != VK_WHOLE_SIZE) {
                 d_sz *= ne02 * ne03;
             }
         }
 
         if (op == GGML_OP_SOFT_MAX) {
-            // Empty src1 and src2 are possible on soft_max, but the shader needs buffers
+            // Empty src1 is possible in soft_max, but the shader needs a buffer
             vk_subbuffer subbuf_y;
             if (use_src1) {
                 subbuf_y = { d_Y, y_buf_offset, y_sz };
@@ -4074,15 +4069,30 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
                 subbuf_y = { d_X, 0, d_X->size };
             }
 
-            vk_subbuffer subbuf_z;
-            if (use_src2) {
-                subbuf_z = { d_Z, z_buf_offset, z_sz };
-            } else {
-                subbuf_z = { d_X, 0, d_X->size };
-            }
-
             ggml_vk_sync_buffers(subctx);
-            ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, subbuf_y, subbuf_z, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
+            ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, subbuf_y, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
+        } else if (op == GGML_OP_ROPE) {
+            const int mode          = ((int32_t *) dst->op_params)[2];
+            const bool is_neox = mode & 2;
+
+            if (is_neox) {
+                // Empty src2 is possible in rope, but the shader needs a buffer
+                vk_subbuffer subbuf_z;
+                if (use_src2) {
+                    subbuf_z = { d_Z, z_buf_offset, z_sz };
+                } else {
+                    subbuf_z = { d_X, 0, d_X->size };
+                }
+
+                ggml_vk_sync_buffers(subctx);
+                ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz }, subbuf_z, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
+            } else {
+                ggml_vk_sync_buffers(subctx);
+                ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz }, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
+            }
+        } else if (use_src2) {
+            ggml_vk_sync_buffers(subctx);
+            ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz }, { d_Z, z_buf_offset, z_sz }, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
         } else if (use_src1) {
             ggml_vk_sync_buffers(subctx);
             ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, { d_Y, y_buf_offset, y_sz }, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
@@ -4090,22 +4100,16 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
             ggml_vk_sync_buffers(subctx);
             ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset, x_sz }, { d_D, d_buf_offset, d_sz } }, sizeof(PC), &pc, elements);
         }
-        if (dst->backend == GGML_BACKEND_TYPE_CPU && op == GGML_OP_CPY) {
-            ggml_vk_d2h_tensor_2d(ctx, subctx, d_D, 0, dst);
-        } else if(dst->backend == GGML_BACKEND_TYPE_CPU) {
-            // copy dst to host
-            float * d = (float *) dst->data;
-            ggml_vk_buffer_read_async(ctx, subctx, d_D, 0, d, d_sz);
-        }
     } else {
         GGML_ASSERT(op != GGML_OP_SOFT_MAX);
+        GGML_ASSERT(op != GGML_OP_ARGSORT);
+        GGML_ASSERT(!use_src2);
 
         ggml_pipeline_allocate_descriptor_sets(ctx, pipeline, ne02 * ne03);
 
         switch (dst->op) {
         case GGML_OP_NORM:
         case GGML_OP_RMS_NORM:
-        case GGML_OP_SOFT_MAX:
             elements = { (uint32_t)ne01, 1, 1 };
             break;
         case GGML_OP_DIAG_MASK_INF:
@@ -4135,10 +4139,6 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context * subctx, c
                     ggml_vk_sync_buffers(subctx);
                     ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { { d_X, x_buf_offset + x_offset, x_sz }, { d_D, d_buf_offset + d_offset, d_sz } }, sizeof(PC), &pc, elements);
                 }
-                if (dst->backend == GGML_BACKEND_TYPE_CPU) {
-                    // copy dst to host
-                    ggml_vk_buffer_read_async(ctx, subctx, d_D, d_buf_offset + d_offset, (char *) dst->data + i02*nb2 + i03*nb3, d_sz);
-                }
             }
         }
     }
@@ -4269,7 +4269,7 @@ static void ggml_vk_diag_mask_inf(ggml_backend_vk_context * ctx, vk_context * su
     ggml_vk_op_f32<vk_op_diag_mask_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_DIAG_MASK_INF, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0] });
 }
 
-static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
     float * op_params = (float *)dst->op_params;
 
     float scale = op_params[0];
@@ -4285,20 +4285,16 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context * subctx,
     const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
     const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
 
-#pragma message("TODO: src2 is no longer used in soft_max - should be removed and ALiBi calculation should be updated")
-#pragma message("ref:  https://github.com/ggerganov/llama.cpp/pull/7192")
-
-    ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_SOFT_MAX, {
+    ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SOFT_MAX, {
         ncols,
         src1 != nullptr ? nrows_y : (uint32_t)0,
-        src2 != nullptr ? (uint32_t)1 : (uint32_t)0,
         scale, max_bias,
         m0, m1,
         n_head_log2,
     });
 }
 
-static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
+static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
     const int n_dims        = ((int32_t *) dst->op_params)[1];
     const int mode          = ((int32_t *) dst->op_params)[2];
     // const int n_ctx         = ((int32_t *) dst->op_params)[3];
@@ -4321,15 +4317,40 @@ static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context * subctx, con
     if (is_neox) {
         const float theta_scale = powf(freq_base, -2.0f/n_dims);
         const float inv_ndims = -1.0f / n_dims;
-        ggml_vk_op_f32<vk_op_rope_neox_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ROPE, { (uint32_t)src0->ne[0], (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1], freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1], 0.0f, 0.0f}, theta_scale, inv_ndims });
+        ggml_vk_op_f32<vk_op_rope_neox_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_ROPE, {
+            (uint32_t)src0->ne[0], (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1],
+            freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1], 0.0f, 0.0f}, theta_scale, inv_ndims,
+            src2 != nullptr,
+        });
     } else {
-        ggml_vk_op_f32<vk_op_rope_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ROPE, { (uint32_t)src0->ne[0], freq_scale, (uint32_t)src0->ne[1], freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1], 0.0f, 0.0f} });
+        ggml_vk_op_f32<vk_op_rope_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_ROPE, {
+            (uint32_t)src0->ne[0], freq_scale, (uint32_t)src0->ne[1],
+            freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1], 0.0f, 0.0f}
+        });
     }
 }
 
 static void ggml_vk_argsort(ggml_backend_vk_context * ctx, vk_context * subctx, const ggml_tensor * src0, ggml_tensor * dst) {
     int32_t * op_params = (int32_t *)dst->op_params;
-    ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ARGSORT, { (uint32_t)src0->ne[0], ((ggml_sort_order) op_params[0]) == GGML_SORT_ORDER_ASC });
+
+    uint32_t ncols = src0->ne[0];
+
+    uint32_t ncols_pad = 1;
+    while (ncols_pad < ncols) {
+        ncols_pad *= 2;
+    }
+
+    GGML_ASSERT(ncols_pad <= 1024);
+
+    std::cerr << "ncols=" << ncols << " ncols_pad=" << ncols_pad << " ascending=" << op_params[0] << std::endl;
+
+    std::cerr << ((ggml_sort_order) op_params[0]) << " " << GGML_SORT_ORDER_ASC << std::endl;
+
+    ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ARGSORT, {
+        ncols,
+        ncols_pad,
+        op_params[0],
+    });
 }
 
 #ifdef GGML_VULKAN_RUN_TESTS
@@ -4381,6 +4402,9 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
         if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
             p = ctx->device->pipeline_matmul_f32->a_s;
             shname = "F32_ALIGNED_S";
+        } else if (std::is_same<float, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) {
+            p = ctx->device->pipeline_matmul_f32_f16->a_s;
+            shname = "F32_F16_ALIGNED_S";
         } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
             p = ctx->device->pipeline_matmul_f16_f32->a_s;
             shname = "F16_F32_ALIGNED_S";
@@ -4394,6 +4418,9 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
         if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
             p = ctx->device->pipeline_matmul_f32->a_m;
             shname = "F32_ALIGNED_M";
+        } else if (std::is_same<float, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) {
+            p = ctx->device->pipeline_matmul_f32_f16->a_m;
+            shname = "F32_F16_ALIGNED_M";
         } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
             p = ctx->device->pipeline_matmul_f16_f32->a_m;
             shname = "F16_F32_ALIGNED_M";
@@ -4407,6 +4434,9 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
         if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
             p = ctx->device->pipeline_matmul_f32->a_l;
             shname = "F32_ALIGNED_L";
+        } else if (std::is_same<float, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) {
+            p = ctx->device->pipeline_matmul_f32_f16->a_l;
+            shname = "F32_F16_ALIGNED_L";
         } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
             p = ctx->device->pipeline_matmul_f16_f32->a_l;
             shname = "F16_F32_ALIGNED_L";
@@ -4427,6 +4457,9 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
             if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
                 p = ctx->device->pipeline_matmul_f32->s;
                 shname = "F32_S";
+            } else if (std::is_same<float, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) {
+                p = ctx->device->pipeline_matmul_f32_f16->s;
+                shname = "F32_F16_S";
             } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
                 p = ctx->device->pipeline_matmul_f16_f32->s;
                 shname = "F16_F32_S";
@@ -4438,6 +4471,9 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
             if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
                 p = ctx->device->pipeline_matmul_f32->m;
                 shname = "F32_M";
+            } else if (std::is_same<float, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) {
+                p = ctx->device->pipeline_matmul_f32_f16->m;
+                shname = "F32_F16_M";
             } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
                 p = ctx->device->pipeline_matmul_f16_f32->m;
                 shname = "F16_F32_M";
@@ -4449,6 +4485,9 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
             if (std::is_same<float, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
                 p = ctx->device->pipeline_matmul_f32->l;
                 shname = "F32_L";
+            } else if (std::is_same<float, X_TYPE>() && std::is_same<ggml_fp16_t, Y_TYPE>()) {
+                p = ctx->device->pipeline_matmul_f32_f16->l;
+                shname = "F32_F16_L";
             } else if (std::is_same<ggml_fp16_t, X_TYPE>() && std::is_same<float, Y_TYPE>()) {
                 p = ctx->device->pipeline_matmul_f16_f32->l;
                 shname = "F16_F32_L";
@@ -4561,15 +4600,11 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t
     src1_ggml->data = y;
     tensor_ggml->data = d_chk;
 
-    ctx->disable = true;
-
     ggml_cgraph * cgraph = ggml_new_graph(ggml_ctx);
     ggml_build_forward_expand(cgraph, tensor_ggml);
 
     ggml_graph_compute_with_ctx(ggml_ctx, cgraph, 1);
 
-    ctx->disable = false;
-
     ggml_free(ggml_ctx);
 
     double avg_err = 0.0;
@@ -5049,15 +5084,11 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m,
     src1_ggml->data = y;
     tensor_ggml->data = d_chk;
 
-    ctx->disable = true;
-
     ggml_cgraph * cgraph = ggml_new_graph(ggml_ctx);
     ggml_build_forward_expand(cgraph, tensor_ggml);
 
     ggml_graph_compute_with_ctx(ggml_ctx, cgraph, 1);
 
-    ctx->disable = false;
-
     ggml_free(ggml_ctx);
 
     double avg_err = 0.0;
@@ -5134,12 +5165,12 @@ static void ggml_vk_preallocate_buffers_graph(ggml_backend_vk_context * ctx, ggm
 #ifdef GGML_VULKAN_DEBUG
     std::cerr << "ggml_vk_preallocate_buffers_graph(" << node << ")" << std::endl;
 #endif
-    if (ctx->disable || node->backend != GGML_BACKEND_TYPE_GPU) {
+    ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) node->extra;
+
+    if (extra == nullptr) {
         return;
     }
 
-    ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) node->extra;
-
     ggml_tensor * src0 = node->src[0];
     ggml_tensor * src1 = node->src[1];
 
@@ -5244,9 +5275,6 @@ static void ggml_vk_preallocate_buffers_graph(ggml_backend_vk_context * ctx, ggm
 }
 
 static void ggml_vk_preallocate_buffers(ggml_backend_vk_context * ctx) {
-    if (ctx->disable) {
-        return;
-    }
 #ifdef GGML_VULKAN_DEBUG
     std::cerr << "ggml_vk_preallocate_buffers(x_size: " << ctx->prealloc_size_x << " y_size: " << ctx->prealloc_size_y << " split_k_size: " << ctx->prealloc_size_split_k << ")" << std::endl;
 #endif
@@ -5420,7 +5448,9 @@ static void ggml_vk_preallocate_buffers(ggml_backend_vk_context * ctx) {
 }
 
 static void ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * node, bool last_node){
-    if (ctx->disable || node->backend != GGML_BACKEND_TYPE_GPU || ggml_is_empty(node)) {
+    ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) node->extra;
+
+    if (ggml_is_empty(node) || extra == nullptr) {
         return;
     }
 
@@ -5434,8 +5464,6 @@ static void ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
     const ggml_tensor * src1 = node->src[1];
     const ggml_tensor * src2 = node->src[2];
 
-    ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) node->extra;
-
     switch (node->op) {
     case GGML_OP_UNARY:
         switch (ggml_get_unary_op(node)) {
@@ -5547,11 +5575,11 @@ static void ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
 
         break;
     case GGML_OP_SOFT_MAX:
-        ggml_vk_soft_max(ctx, ctx->compute_ctx, src0, src1, src2, node);
+        ggml_vk_soft_max(ctx, ctx->compute_ctx, src0, src1, node);
 
         break;
     case GGML_OP_ROPE:
-        ggml_vk_rope(ctx, ctx->compute_ctx, src0, src1, node);
+        ggml_vk_rope(ctx, ctx->compute_ctx, src0, src1, src2, node);
 
         break;
     case GGML_OP_ARGSORT:
@@ -5580,7 +5608,7 @@ static void ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
     last_node = true;
 #endif
 
-    if (node->backend == GGML_BACKEND_TYPE_CPU || last_node) {
+    if (last_node) {
         ggml_vk_ctx_end(ctx->compute_ctx);
         ctx->compute_ctx->exit_tensor = node;
         ctx->compute_ctx = nullptr;
@@ -5588,10 +5616,6 @@ static void ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_tensor * nod
 }
 
 static bool ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_compute_params * params, ggml_tensor * tensor){
-    if (ctx->disable) {
-        return false;
-    }
-
     ggml_tensor_extra_gpu * extra = nullptr;
 
     switch (tensor->op) {
@@ -5650,7 +5674,7 @@ static bool ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_compute_
     }
 
 #ifdef GGML_VULKAN_DEBUG
-    std::cerr << "ggml_vk_compute_forward(" << tensor << ", name=" << tensor->name << ", op=" << ggml_op_name(tensor->op) << ", type=" << tensor->type << ", backend=" << tensor->backend << ", ne0=" << tensor->ne[0] << ", ne1=" << tensor->ne[1] << ", ne2=" << tensor->ne[2] << ", ne3=" << tensor->ne[3] << ", nb0=" << tensor->nb[0] << ", nb1=" << tensor->nb[1] << ", nb2=" << tensor->nb[2] << ", nb3=" << tensor->nb[3] << ", view_src=" << tensor->view_src << ", view_offs=" << tensor->view_offs << ")" << std::endl;
+    std::cerr << "ggml_vk_compute_forward(" << tensor << ", name=" << tensor->name << ", op=" << ggml_op_name(tensor->op) << ", type=" << tensor->type << ", ne0=" << tensor->ne[0] << ", ne1=" << tensor->ne[1] << ", ne2=" << tensor->ne[2] << ", ne3=" << tensor->ne[3] << ", nb0=" << tensor->nb[0] << ", nb1=" << tensor->nb[1] << ", nb2=" << tensor->nb[2] << ", nb3=" << tensor->nb[3] << ", view_src=" << tensor->view_src << ", view_offs=" << tensor->view_offs << ")" << std::endl;
 #endif
 
 #ifdef GGML_VULKAN_CHECK_RESULTS
@@ -5690,9 +5714,6 @@ static bool ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_compute_
 
 // Clean up after graph processing is done
 static void ggml_vk_graph_cleanup(ggml_backend_vk_context * ctx) {
-    if (ctx->disable) {
-        return;
-    }
 #ifdef GGML_VULKAN_DEBUG
     std::cerr << "ggml_vk_graph_cleanup()" << std::endl;
 #endif
@@ -5865,7 +5886,6 @@ GGML_CALL static void ggml_backend_vk_buffer_init_tensor(ggml_backend_buffer_t b
         extra->offset = (uint8_t *) tensor->data - (uint8_t *) vk_ptr_base;
     }
 
-    tensor->backend = GGML_BACKEND_TYPE_GPU;
     tensor->extra = extra;
 }
 
@@ -5873,8 +5893,6 @@ GGML_CALL static void ggml_backend_vk_buffer_set_tensor(ggml_backend_buffer_t bu
 #ifdef GGML_VULKAN_DEBUG
     std::cerr << "ggml_backend_vk_buffer_set_tensor(" << buffer << ", " << tensor << ", " << data << ", " << offset << ", " << size << ")" << std::endl;
 #endif
-    GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU);
-
     ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context;
 
     ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
@@ -5888,8 +5906,6 @@ GGML_CALL static void ggml_backend_vk_buffer_get_tensor(ggml_backend_buffer_t bu
 #ifdef GGML_VULKAN_DEBUG
     std::cerr << "ggml_backend_vk_buffer_get_tensor(" << buffer << ", " << tensor << ", " << data << ", " << offset << ", " << size << ")" << std::endl;
 #endif
-    GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU);
-
     ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context;
 
     ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
@@ -6032,6 +6048,7 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_host_buffer_type_alloc_bu
 #ifdef GGML_VULKAN_DEBUG
     std::cerr << "ggml_backend_vk_host_buffer_type_alloc_buffer(" << size << ")" << std::endl;
 #endif
+    size += 32;  // Behave like the CPU buffer type
     void * ptr = nullptr;
     try {
         ptr = ggml_vk_host_malloc(&vk_instance.contexts[0], size);
@@ -6119,7 +6136,6 @@ GGML_CALL static void ggml_backend_vk_set_tensor_async(ggml_backend_t backend, g
 #endif
     ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
     GGML_ASSERT((tensor->buffer->buft == ggml_backend_vk_buffer_type(ctx->idx) || tensor->buffer->buft == ggml_backend_vk_host_buffer_type()) && "unsupported buffer type");
-    GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU);
 
     ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
 
@@ -6140,7 +6156,6 @@ GGML_CALL static void ggml_backend_vk_get_tensor_async(ggml_backend_t backend, c
 #endif
     ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
     GGML_ASSERT((tensor->buffer->buft == ggml_backend_vk_buffer_type(ctx->idx) || tensor->buffer->buft == ggml_backend_vk_host_buffer_type()) && "unsupported buffer type");
-    GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_GPU);
 
     ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) tensor->extra;
 
@@ -6206,6 +6221,10 @@ GGML_CALL static void ggml_backend_vk_synchronize(ggml_backend_t backend) {
     ctx->transfer_ctx = nullptr;
 }
 
+static bool ggml_vk_is_empty(ggml_tensor * node) {
+    return ggml_is_empty(node) || node->op == GGML_OP_NONE || node->op == GGML_OP_RESHAPE || node->op == GGML_OP_TRANSPOSE || node->op == GGML_OP_VIEW || node->op == GGML_OP_PERMUTE;
+}
+
 GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
 #ifdef GGML_VULKAN_DEBUG
     std::cerr << "ggml_backend_vk_graph_compute(" << cgraph->n_nodes << " nodes)" << std::endl;
@@ -6220,7 +6239,7 @@ GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backen
     int last_node = cgraph->n_nodes - 1;
 
     // If the last op in the cgraph isn't backend GPU, the command buffer doesn't get closed properly
-    while (last_node > 0 && (cgraph->nodes[last_node]->backend != GGML_BACKEND_TYPE_GPU || ggml_is_empty(cgraph->nodes[last_node]))) {
+    while (last_node > 0 && ggml_vk_is_empty(cgraph->nodes[last_node])) {
         last_node -= 1;
     }
 
@@ -6234,7 +6253,7 @@ GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backen
     for (int i = 0; i < cgraph->n_nodes; i++) {
         ggml_tensor * node = cgraph->nodes[i];
 
-        if (ggml_is_empty(node) || node->op == GGML_OP_RESHAPE || node->op == GGML_OP_TRANSPOSE || node->op == GGML_OP_VIEW || node->op == GGML_OP_PERMUTE || node->op == GGML_OP_NONE) {
+        if (ggml_vk_is_empty(node)) {
             continue;
         }
 
@@ -6536,7 +6555,7 @@ static void ggml_vk_print_graph_origin(const ggml_tensor * tensor, std::vector<c
     for (int j = 0; j < level; j++) {
         std::cerr << " ";
     }
-    std::cerr << ggml_op_name(tensor->op) << " gpu=" << (tensor->extra != nullptr) << " backend=" << tensor->backend << std::endl;
+    std::cerr << ggml_op_name(tensor->op) << " gpu=" << (tensor->extra != nullptr) << std::endl;
 
     done.push_back(tensor);
 
@@ -6548,7 +6567,7 @@ static void ggml_vk_print_graph_origin(const ggml_tensor * tensor, std::vector<c
 }
 
 static void ggml_vk_print_tensor_area(const ggml_tensor * tensor, const void * data, int i0, int i1, int i2, int i3) {
-    if (tensor->type != GGML_TYPE_F32 && tensor->type != GGML_TYPE_F16) {
+    if (tensor->type != GGML_TYPE_F32 && tensor->type != GGML_TYPE_F16 && tensor->type != GGML_TYPE_I32) {
         return;
     }
     i0 = std::max(i0, 5);
@@ -6569,6 +6588,8 @@ static void ggml_vk_print_tensor_area(const ggml_tensor * tensor, const void * d
                     val = *(const float *) ((const char *) data + i3*tensor->nb[3] + i2*tensor->nb[2] + idx1*tensor->nb[1] + idx0*tensor->nb[0]);
                 } else if (tensor->type == GGML_TYPE_F16) {
                     val = ggml_fp16_to_fp32(*(const ggml_fp16_t *) ((const char *) data + i3*tensor->nb[3] + i2*tensor->nb[2] + idx1*tensor->nb[1] + idx0*tensor->nb[0]));
+                } else if (tensor->type == GGML_TYPE_I32) {
+                    val = *(const int32_t *) ((const char *) data + i3*tensor->nb[3] + i2*tensor->nb[2] + idx1*tensor->nb[1] + idx0*tensor->nb[0]);
                 } else {
                     GGML_ASSERT(false);
                 }
@@ -6584,7 +6605,7 @@ static void ggml_vk_print_tensor_area(const ggml_tensor * tensor, const void * d
 static void ggml_vk_print_tensor(ggml_backend_vk_context * ctx, const ggml_tensor * tensor, const char * name) {
     void * tensor_data = tensor->data;
 
-    if (tensor->backend == GGML_BACKEND_TYPE_GPU) {
+    if (ggml_backend_buffer_is_vk(tensor->buffer)) {
         const size_t tensor_size = ggml_nbytes(tensor);
         tensor_data = malloc(tensor_size);
 
@@ -6595,12 +6616,12 @@ static void ggml_vk_print_tensor(ggml_backend_vk_context * ctx, const ggml_tenso
     }
 
     std::cerr << "TENSOR CHECK " << name << " (" << tensor->name << "): " << ggml_op_name(tensor->op) << std::endl;
-    std::cerr << "tensor=" << tensor << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << std::endl;
+    std::cerr << "tensor=" << tensor << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << std::endl;
     if (tensor->src[0] != nullptr) {
-        std::cerr << "tensor->src[0]=" << tensor->src[0] << " name=" << tensor->src[0]->name << " op=" << ggml_op_name(tensor->src[0]->op) << " type=" << ggml_type_name(tensor->src[0]->type) << " backend=" << tensor->src[0]->backend << " ne0=" << tensor->src[0]->ne[0] << " nb0=" << tensor->src[0]->nb[0] << " ne1=" << tensor->src[0]->ne[1] << " nb1=" << tensor->src[0]->nb[1] << " ne2=" << tensor->src[0]->ne[2] << " nb2=" << tensor->src[0]->nb[2] << " ne3=" << tensor->src[0]->ne[3] << " nb3=" << tensor->src[0]->nb[3] << std::endl;
+        std::cerr << "tensor->src[0]=" << tensor->src[0] << " name=" << tensor->src[0]->name << " op=" << ggml_op_name(tensor->src[0]->op) << " type=" << ggml_type_name(tensor->src[0]->type) << " ne0=" << tensor->src[0]->ne[0] << " nb0=" << tensor->src[0]->nb[0] << " ne1=" << tensor->src[0]->ne[1] << " nb1=" << tensor->src[0]->nb[1] << " ne2=" << tensor->src[0]->ne[2] << " nb2=" << tensor->src[0]->nb[2] << " ne3=" << tensor->src[0]->ne[3] << " nb3=" << tensor->src[0]->nb[3] << std::endl;
     }
     if (tensor->src[1] != nullptr) {
-        std::cerr << "tensor->src[1]=" << tensor->src[1] << " name=" << tensor->src[1]->name << " op=" << ggml_op_name(tensor->src[1]->op) << " type=" << ggml_type_name(tensor->src[1]->type) << " backend=" << tensor->src[1]->backend << " ne0=" << tensor->src[1]->ne[0] << " nb0=" << tensor->src[1]->nb[0] << " ne1=" << tensor->src[1]->ne[1] << " nb1=" << tensor->src[1]->nb[1] << " ne2=" << tensor->src[1]->ne[2] << " nb2=" << tensor->src[1]->nb[2] << " ne3=" << tensor->src[1]->ne[3] << " nb3=" << tensor->src[1]->nb[3] << std::endl;
+        std::cerr << "tensor->src[1]=" << tensor->src[1] << " name=" << tensor->src[1]->name << " op=" << ggml_op_name(tensor->src[1]->op) << " type=" << ggml_type_name(tensor->src[1]->type) << " ne0=" << tensor->src[1]->ne[0] << " nb0=" << tensor->src[1]->nb[0] << " ne1=" << tensor->src[1]->ne[1] << " nb1=" << tensor->src[1]->nb[1] << " ne2=" << tensor->src[1]->ne[2] << " nb2=" << tensor->src[1]->nb[2] << " ne3=" << tensor->src[1]->ne[3] << " nb3=" << tensor->src[1]->nb[3] << std::endl;
     }
     std::cerr << std::endl << "Result:" << std::endl;
     ggml_vk_print_tensor_area(tensor, tensor_data, 5, 5, 0, 0);
@@ -6611,43 +6632,11 @@ static void ggml_vk_print_tensor(ggml_backend_vk_context * ctx, const ggml_tenso
     std::vector<const ggml_tensor *> done;
     ggml_vk_print_graph_origin(tensor, done);
 
-    if (tensor->backend == GGML_BACKEND_TYPE_GPU) {
+    if (ggml_backend_buffer_is_vk(tensor->buffer)) {
         free(tensor_data);
     }
 }
 
-static void ggml_vk_check_tensor(const std::string& name, const ggml_tensor * tensor) {
-    return;
-    GGML_ASSERT(tensor->backend == GGML_BACKEND_TYPE_CPU);
-    if (tensor->type != GGML_TYPE_F32 && tensor->type != GGML_TYPE_F16) {
-        return;
-    }
-    for (int i3 = 0; i3 < tensor->ne[3]; i3++) {
-        for (int i2 = 0; i2 < tensor->ne[2]; i2++) {
-            for (int i1 = 0; i1 < tensor->ne[1]; i1++) {
-                for (int i0 = 0; i0 < tensor->ne[0]; i0++) {
-                    float val = 0.0f;
-                    if (tensor->type == GGML_TYPE_F32) {
-                        val = *(float *) ((char *) tensor->data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0]);
-                    } else if (tensor->type == GGML_TYPE_F16) {
-                        val = ggml_fp16_to_fp32(*(ggml_fp16_t *) ((char *) tensor->data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0]));
-                    }
-                    if (std::isnan(val)) {
-                        std::cerr << "ERROR: TENSOR CHECK " << name << ": Invalid value in " << ggml_op_name(tensor->op) << " i3=" << i3 << " i2=" << i2 << " i1=" << i1 << " i0=" << i0 << " val=" << val << std::endl;
-                        std::cerr << "tensor=" << tensor << " tensor->type=" << ggml_type_name(tensor->type) << " tensor->backend: " << tensor->backend << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << std::endl;
-                        std::cerr << std::endl;
-                        ggml_vk_print_tensor_area(tensor, tensor->data, i0, i1, i2, i3);
-                        std::cerr << std::endl;
-                        std::vector<const ggml_tensor *> done;
-                        ggml_vk_print_graph_origin(tensor, done);
-                        GGML_ASSERT(false);
-                    }
-                }
-            }
-        }
-    }
-}
-
 void * comp_result;
 size_t comp_size;
 size_t comp_nb[GGML_MAX_DIMS];
@@ -6701,10 +6690,10 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
 
         src0_buffer = malloc(src0_size);
         src0_clone->data = src0_buffer;
-        if (src0->backend == GGML_BACKEND_TYPE_CPU) {
+        if (ggml_backend_buffer_is_host(src0->buffer)) {
             memcpy(src0_clone->data, src0->data, src0_size);
             memcpy(src0_clone->nb, src0->nb, sizeof(size_t) * GGML_MAX_DIMS);
-        } else if (src0->backend == GGML_BACKEND_TYPE_GPU) {
+        } else if (ggml_backend_buffer_is_vk(src0->buffer)) {
             ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) src0->extra;
             vk_buffer buffer_gpu = extra->buffer_gpu.lock();
             uint64_t offset = extra->offset;
@@ -6735,8 +6724,6 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
         if (vk_output_tensor > 0 && vk_output_tensor == check_counter) {
             ggml_vk_print_tensor(ctx, src0, "src0");
         }
-
-        ggml_vk_check_tensor(std::string(ggml_op_name(tensor->op)) + "->src0", src0_clone);
     }
     if (src1 != nullptr) {
         src1_clone = ggml_dup_tensor(ggml_ctx, src1);
@@ -6745,10 +6732,10 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
 
         src1_buffer = malloc(src1_size);
         src1_clone->data = src1_buffer;
-        if (src1->backend == GGML_BACKEND_TYPE_CPU) {
+        if (ggml_backend_buffer_is_host(src1->buffer)) {
             memcpy(src1_clone->data, src1->data, src1_size);
             memcpy(src1_clone->nb, src1->nb, sizeof(size_t) * GGML_MAX_DIMS);
-        } else if (src1->backend == GGML_BACKEND_TYPE_GPU) {
+        } else if (ggml_backend_buffer_is_vk(src1->buffer)) {
             ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) src1->extra;
             vk_buffer buffer_gpu = extra->buffer_gpu.lock();
             uint64_t offset = extra->offset;
@@ -6779,12 +6766,12 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
         if (vk_output_tensor > 0 && vk_output_tensor == check_counter) {
             ggml_vk_print_tensor(ctx, src1, "src1");
             std::cerr << "TENSOR CHECK: " << ggml_op_name(src1_clone->op) << " (check " << check_counter << ")" << std::endl;
-            std::cerr << "src1_clone=" << tensor << " src1_clone->backend: " << src1_clone->backend << " src1_clone->type: " << ggml_type_name(src1_clone->type) << " ne0=" << src1_clone->ne[0] << " nb0=" << src1_clone->nb[0] << " ne1=" << src1_clone->ne[1] << " nb1=" << src1_clone->nb[1] << " ne2=" << src1_clone->ne[2] << " nb2=" << src1_clone->nb[2] << " ne3=" << src1_clone->ne[3] << " nb3=" << src1_clone->nb[3] << std::endl;
+            std::cerr << "src1_clone=" << tensor << " src1_clone->type: " << ggml_type_name(src1_clone->type) << " ne0=" << src1_clone->ne[0] << " nb0=" << src1_clone->nb[0] << " ne1=" << src1_clone->ne[1] << " nb1=" << src1_clone->nb[1] << " ne2=" << src1_clone->ne[2] << " nb2=" << src1_clone->nb[2] << " ne3=" << src1_clone->ne[3] << " nb3=" << src1_clone->nb[3] << std::endl;
             if (src1->src[0] != nullptr) {
-                std::cerr << "src1->src[0]=" << src1->src[0] << " op=" << ggml_op_name(src1->src[0]->op) << " type=" << ggml_type_name(src1->src[0]->type) << " backend=" << src1->src[0]->backend << " ne0=" << src1->src[0]->ne[0] << " nb0=" << src1->src[0]->nb[0] << " ne1=" << src1->src[0]->ne[1] << " nb1=" << src1->src[0]->nb[1] << " ne2=" << src1->src[0]->ne[2] << " nb2=" << src1->src[0]->nb[2] << " ne3=" << src1->src[0]->ne[3] << " nb3=" << src1->src[0]->nb[3] << std::endl;
+                std::cerr << "src1->src[0]=" << src1->src[0] << " op=" << ggml_op_name(src1->src[0]->op) << " type=" << ggml_type_name(src1->src[0]->type) << " ne0=" << src1->src[0]->ne[0] << " nb0=" << src1->src[0]->nb[0] << " ne1=" << src1->src[0]->ne[1] << " nb1=" << src1->src[0]->nb[1] << " ne2=" << src1->src[0]->ne[2] << " nb2=" << src1->src[0]->nb[2] << " ne3=" << src1->src[0]->ne[3] << " nb3=" << src1->src[0]->nb[3] << std::endl;
             }
             if (src1->src[1] != nullptr) {
-                std::cerr << "src1->src[1]=" << src1->src[1] << " op=" << ggml_op_name(src1->src[1]->op) << " type=" << ggml_type_name(src1->src[1]->type) << " backend=" << src1->src[1]->backend << " ne0=" << src1->src[1]->ne[0] << " nb0=" << src1->src[1]->nb[0] << " ne1=" << src1->src[1]->ne[1] << " nb1=" << src1->src[1]->nb[1] << " ne2=" << src1->src[1]->ne[2] << " nb2=" << src1->src[1]->nb[2] << " ne3=" << src1->src[1]->ne[3] << " nb3=" << src1->src[1]->nb[3] << std::endl;
+                std::cerr << "src1->src[1]=" << src1->src[1] << " op=" << ggml_op_name(src1->src[1]->op) << " type=" << ggml_type_name(src1->src[1]->type) << " ne0=" << src1->src[1]->ne[0] << " nb0=" << src1->src[1]->nb[0] << " ne1=" << src1->src[1]->ne[1] << " nb1=" << src1->src[1]->nb[1] << " ne2=" << src1->src[1]->ne[2] << " nb2=" << src1->src[1]->nb[2] << " ne3=" << src1->src[1]->ne[3] << " nb3=" << src1->src[1]->nb[3] << std::endl;
             }
             std::cerr << std::endl << "Result:" << std::endl;
             ggml_vk_print_tensor_area(src1_clone, src1_clone->data, 5, 5, 0, 0);
@@ -6795,8 +6782,6 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
             std::vector<const ggml_tensor *> done;
             ggml_vk_print_graph_origin(src1_clone, done);
         }
-
-        ggml_vk_check_tensor(std::string(ggml_op_name(tensor->op)) + "->src1", src1_clone);
     }
     if (src2 != nullptr) {
         src2_clone = ggml_dup_tensor(ggml_ctx, src2);
@@ -6805,18 +6790,18 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
 
         src2_buffer = malloc(src2_size);
         src2_clone->data = src2_buffer;
-        if (src2->backend == GGML_BACKEND_TYPE_CPU) {
+        if (ggml_backend_buffer_is_host(src2->buffer)) {
             memcpy(src2_clone->data, src2->data, src2_size);
             memcpy(src2_clone->nb, src2->nb, sizeof(size_t) * GGML_MAX_DIMS);
-        } else if (src2->backend == GGML_BACKEND_TYPE_GPU) {
+        } else if (ggml_backend_buffer_is_vk(src2->buffer)) {
             ggml_tensor_extra_gpu * extra = (ggml_tensor_extra_gpu *) src2->extra;
-            vk_buffer buf = extra->buffer_gpu.lock();
+            vk_buffer buffer_gpu = extra->buffer_gpu.lock();
             uint64_t offset = extra->offset;
             if (!ggml_is_contiguous(src2) && ggml_vk_dim01_contiguous(src2)) {
                 for (int i3 = 0; i3 < src2->ne[3]; i3++) {
                     for (int i2 = 0; i2 < src2->ne[2]; i2++) {
                         const int idx = i3*src2->ne[2] + i2;
-                        ggml_vk_buffer_read(ctx, buf, offset + idx * src2->nb[2], ((char *)src2_clone->data + idx * src2_clone->nb[2]), src2->ne[1] * src2->nb[1]);
+                        ggml_vk_buffer_read(ctx, buffer_gpu, offset + idx * src2->nb[2], ((char *)src2_clone->data + idx * src2_clone->nb[2]), src2->ne[1] * src2->nb[1]);
                     }
                 }
 
@@ -6826,10 +6811,10 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
                     src2_clone->nb[i] = src2_clone->nb[i - 1]*src2_clone->ne[i - 1];
                 }
             } else {
-                if (offset + src2_size >= buf->size) {
-                    src2_size = buf->size - offset;
+                if (offset + src2_size >= buffer_gpu->size) {
+                    src2_size = buffer_gpu->size - offset;
                 }
-                ggml_vk_buffer_read(ctx, buf, offset, src2_clone->data, src2_size);
+                ggml_vk_buffer_read(ctx, buffer_gpu, offset, src2_clone->data, src2_size);
                 memcpy(src2_clone->nb, src2->nb, sizeof(size_t) * GGML_MAX_DIMS);
             }
         } else {
@@ -6839,12 +6824,12 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
         if (vk_output_tensor > 0 && vk_output_tensor == check_counter) {
             ggml_vk_print_tensor(ctx, src2, "src2");
             std::cerr << "TENSOR CHECK: " << ggml_op_name(src2_clone->op) << " (check " << check_counter << ")" << std::endl;
-            std::cerr << "src2_clone=" << tensor << " src2_clone->backend: " << src2_clone->backend << " src2_clone->type: " << ggml_type_name(src2_clone->type) << " ne0=" << src2_clone->ne[0] << " nb0=" << src2_clone->nb[0] << " ne1=" << src2_clone->ne[1] << " nb1=" << src2_clone->nb[1] << " ne2=" << src2_clone->ne[2] << " nb2=" << src2_clone->nb[2] << " ne3=" << src2_clone->ne[3] << " nb3=" << src2_clone->nb[3] << std::endl;
+            std::cerr << "src2_clone=" << tensor << " src2_clone->type: " << ggml_type_name(src2_clone->type) << " ne0=" << src2_clone->ne[0] << " nb0=" << src2_clone->nb[0] << " ne1=" << src2_clone->ne[1] << " nb1=" << src2_clone->nb[1] << " ne2=" << src2_clone->ne[2] << " nb2=" << src2_clone->nb[2] << " ne3=" << src2_clone->ne[3] << " nb3=" << src2_clone->nb[3] << std::endl;
             if (src2->src[0] != nullptr) {
-                std::cerr << "src2->src[0]=" << src2->src[0] << " op=" << ggml_op_name(src2->src[0]->op) << " type=" << ggml_type_name(src2->src[0]->type) << " backend=" << src2->src[0]->backend << " ne0=" << src2->src[0]->ne[0] << " nb0=" << src2->src[0]->nb[0] << " ne1=" << src2->src[0]->ne[1] << " nb1=" << src2->src[0]->nb[1] << " ne2=" << src2->src[0]->ne[2] << " nb2=" << src2->src[0]->nb[2] << " ne3=" << src2->src[0]->ne[3] << " nb3=" << src2->src[0]->nb[3] << std::endl;
+                std::cerr << "src2->src[0]=" << src2->src[0] << " op=" << ggml_op_name(src2->src[0]->op) << " type=" << ggml_type_name(src2->src[0]->type) << " ne0=" << src2->src[0]->ne[0] << " nb0=" << src2->src[0]->nb[0] << " ne1=" << src2->src[0]->ne[1] << " nb1=" << src2->src[0]->nb[1] << " ne2=" << src2->src[0]->ne[2] << " nb2=" << src2->src[0]->nb[2] << " ne3=" << src2->src[0]->ne[3] << " nb3=" << src2->src[0]->nb[3] << std::endl;
             }
             if (src2->src[1] != nullptr) {
-                std::cerr << "src2->src[1]=" << src2->src[1] << " op=" << ggml_op_name(src2->src[1]->op) << " type=" << ggml_type_name(src2->src[1]->type) << " backend=" << src2->src[1]->backend << " ne0=" << src2->src[1]->ne[0] << " nb0=" << src2->src[1]->nb[0] << " ne1=" << src2->src[1]->ne[1] << " nb1=" << src2->src[1]->nb[1] << " ne2=" << src2->src[1]->ne[2] << " nb2=" << src2->src[1]->nb[2] << " ne3=" << src2->src[1]->ne[3] << " nb3=" << src2->src[1]->nb[3] << std::endl;
+                std::cerr << "src2->src[1]=" << src2->src[1] << " op=" << ggml_op_name(src2->src[1]->op) << " type=" << ggml_type_name(src2->src[1]->type) << " ne0=" << src2->src[1]->ne[0] << " nb0=" << src2->src[1]->nb[0] << " ne1=" << src2->src[1]->ne[1] << " nb1=" << src2->src[1]->nb[1] << " ne2=" << src2->src[1]->ne[2] << " nb2=" << src2->src[1]->nb[2] << " ne3=" << src2->src[1]->ne[3] << " nb3=" << src2->src[1]->nb[3] << std::endl;
             }
             std::cerr << std::endl << "Result:" << std::endl;
             ggml_vk_print_tensor_area(src2_clone, src2_clone->data, 5, 5, 0, 0);
@@ -6855,8 +6840,6 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
             std::vector<const ggml_tensor *> done;
             ggml_vk_print_graph_origin(src2_clone, done);
         }
-
-        ggml_vk_check_tensor(std::string(ggml_op_name(tensor->op)) + "->src2", src2_clone);
     }
 
     if (tensor->op == GGML_OP_MUL_MAT) {
@@ -6877,7 +6860,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
         tensor_clone = ggml_rms_norm(ggml_ctx, src0_clone, *(float *)tensor->op_params);
     } else if (tensor->op == GGML_OP_SOFT_MAX) {
         if (src1 != nullptr) {
-            tensor_clone = ggml_soft_max_ext(ggml_ctx, src0_clone, src1_clone, src2_clone, ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]);
+            tensor_clone = ggml_soft_max_ext(ggml_ctx, src0_clone, src1_clone, ((float *)tensor->op_params)[0], ((float *)tensor->op_params)[1]);
         } else {
             tensor_clone = ggml_soft_max(ggml_ctx, src0_clone);
         }
@@ -6894,7 +6877,7 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
         float attn_factor     = ((float *)   tensor->op_params)[8];
         float beta_fast       = ((float *)   tensor->op_params)[9];
         float beta_slow       = ((float *)   tensor->op_params)[10];
-        tensor_clone = ggml_rope_custom(ggml_ctx, src0_clone, src1_clone, n_dims, mode, n_ggml_ctx, n_orig_ggml_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
+        tensor_clone = ggml_rope_ext(ggml_ctx, src0_clone, src1_clone, src2_clone, n_dims, mode, n_ggml_ctx, n_orig_ggml_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow);
     } else if (tensor->op == GGML_OP_UNARY) {
         switch (ggml_get_unary_op(tensor)) {
         case GGML_UNARY_OP_SILU:
@@ -6937,17 +6920,11 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
         GGML_ASSERT(false);
     }
 
-    // Disable vulkan here to avoid the hooks in ggml.c
-    ctx->disable = true;
-
     ggml_cgraph * cgraph = ggml_new_graph(ggml_ctx);
     ggml_build_forward_expand(cgraph, tensor_clone);
 
     ggml_graph_compute_with_ctx(ggml_ctx, cgraph, 8);
 
-    ctx->disable = false;
-
-    ggml_vk_check_tensor(ggml_op_name(tensor->op), tensor_clone);
     if (vk_output_tensor > 0 && vk_output_tensor == check_counter) {
         ggml_vk_print_tensor(ctx, tensor_clone, "tensor_clone");
     }
@@ -6964,9 +6941,6 @@ static void ggml_vk_check_results_0(ggml_backend_vk_context * ctx, ggml_compute_
     if (src1 != nullptr) {
         free(src1_buffer);
     }
-    if (src2 != nullptr) {
-        free(src2_buffer);
-    }
 
     ggml_free(ggml_ctx);
 }
@@ -6991,7 +6965,7 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
 
     void * tensor_data = tensor->data;
 
-    if (tensor->backend == GGML_BACKEND_TYPE_GPU) {
+    if (ggml_backend_buffer_is_vk(tensor->buffer)) {
         size_t tensor_size = ggml_nbytes(tensor);
         tensor_data = malloc(tensor_size);
 
@@ -7026,8 +7000,11 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
                         } else if (tensor->type == GGML_TYPE_F16) {
                             correct = ggml_fp16_to_fp32(*(ggml_fp16_t *) ((char *) comp_result + i3*comp_nb[3] + i2*comp_nb[2] + i1*comp_nb[1] + i0*comp_nb[0]));
                             result  = ggml_fp16_to_fp32(*(ggml_fp16_t *) ((char *) tensor_data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0]));
+                        } else if (tensor->type == GGML_TYPE_I32) {
+                            correct = *(int32_t *) ((char *) comp_result + i3*comp_nb[3] + i2*comp_nb[2] + i1*comp_nb[1] + i0*comp_nb[0]);
+                            result  = *(int32_t *) ((char *) tensor_data + i3*tensor->nb[3] + i2*tensor->nb[2] + i1*tensor->nb[1] + i0*tensor->nb[0]);
                         } else {
-                            std::cerr << "comp_size=" << comp_size << " but required is " << (i3*comp_nb[3] + i2*comp_nb[2] + i1*comp_nb[1] + i0*comp_nb[0]) << std::endl;
+                            std::cerr << "Results check not implemented for type " << ggml_type_name(tensor->type) << std::endl;
                         }
                     } else {
                         std::cerr << "Missing debug code for type " << ggml_type_name(tensor->type) << std::endl;
@@ -7036,12 +7013,12 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
 
                     if ((std::isnan(correct) != std::isnan(result)) || (std::isinf(correct) != std::isinf(result)) || !buffer_size_fit) {
                         std::cerr << "ERROR: Invalid value in " << ggml_op_name(tensor->op) << " i3=" << i3 << " i2=" << i2 << " i1=" << i1 << " i0=" << i0 << " result=" << result << " correct=" << correct << " avg_err=" << (avg_err / counter) << std::endl;
-                        std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl;
+                        std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl;
                         if (src0 != nullptr) {
-                            std::cerr << "src0=" << src0 << " src0->name=" << src0->name << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " backend=" << src0->backend << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl;
+                            std::cerr << "src0=" << src0 << " src0->name=" << src0->name << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl;
                         }
                         if (src1 != nullptr) {
-                            std::cerr << "src1=" << src1 << " src1->name=" << src1->name << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " backend=" << src1->backend << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl;
+                            std::cerr << "src1=" << src1 << " src1->name=" << src1->name << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl;
                         }
                         std::cerr << "First error: result=" << first_error_result << " correct=" << first_error_correct  << " i3=" << first_error[3] << " i2=" << first_error[2] << " i1=" << first_error[1] << " i0=" << first_error[0] << std::endl;
                         std::cerr << std::endl << "Result:" << std::endl;
@@ -7077,12 +7054,12 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
 
     if (vk_output_tensor > 0 && vk_output_tensor == check_counter) {
         std::cerr << "TENSOR CHECK: avg_err=" << avg_err << " in " << ggml_op_name(tensor->op) << " (check " << check_counter << ")" << std::endl;
-        std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl;
+        std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl;
         if (src0 != nullptr) {
-            std::cerr << "src0=" << src0 << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " backend=" << src0->backend << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl;
+            std::cerr << "src0=" << src0 << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl;
         }
         if (src1 != nullptr) {
-            std::cerr << "src1=" << src1 << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " backend=" << src1->backend << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl;
+            std::cerr << "src1=" << src1 << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl;
         }
         std::cerr << "First error: result=" << first_error_result << " correct=" << first_error_correct  << " i3=" << first_error[3] << " i2=" << first_error[2] << " i1=" << first_error[1] << " i0=" << first_error[0] << std::endl;
         std::cerr << std::endl << "Result:" << std::endl;
@@ -7101,12 +7078,12 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
 
     if (avg_err > 0.05 || std::isnan(avg_err)) {
         std::cerr << "ERROR: avg_err=" << avg_err << " in " << ggml_op_name(tensor->op) << " (check " << check_counter << ")" << std::endl;
-        std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->backend: " << tensor->backend << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl;
+        std::cerr << "tensor=" << tensor << " tensor->name=" << tensor->name << " tensor->type: " << ggml_type_name(tensor->type) << " ne0=" << tensor->ne[0] << " nb0=" << tensor->nb[0] << " ne1=" << tensor->ne[1] << " nb1=" << tensor->nb[1] << " ne2=" << tensor->ne[2] << " nb2=" << tensor->nb[2] << " ne3=" << tensor->ne[3] << " nb3=" << tensor->nb[3] << " offset=" << tensor->view_offs << std::endl;
         if (src0 != nullptr) {
-            std::cerr << "src0=" << src0 << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " backend=" << src0->backend << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl;
+            std::cerr << "src0=" << src0 << " op=" << ggml_op_name(src0->op) << " type=" << ggml_type_name(src0->type) << " ne0=" << src0->ne[0] << " nb0=" << src0->nb[0] << " ne1=" << src0->ne[1] << " nb1=" << src0->nb[1] << " ne2=" << src0->ne[2] << " nb2=" << src0->nb[2] << " ne3=" << src0->ne[3] << " nb3=" << src0->nb[3] << " offset=" << src0->view_offs << std::endl;
         }
         if (src1 != nullptr) {
-            std::cerr << "src1=" << src1 << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " backend=" << src1->backend << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl;
+            std::cerr << "src1=" << src1 << " op=" << ggml_op_name(src1->op) << " type=" << ggml_type_name(src1->type) << " ne0=" << src1->ne[0] << " nb0=" << src1->nb[0] << " ne1=" << src1->ne[1] << " nb1=" << src1->nb[1] << " ne2=" << src1->ne[2] << " nb2=" << src1->nb[2] << " ne3=" << src1->ne[3] << " nb3=" << src1->nb[3] << " offset=" << src1->view_offs << std::endl;
         }
         std::cerr << "First error: result=" << first_error_result << " correct=" << first_error_correct  << " i3=" << first_error[3] << " i2=" << first_error[2] << " i1=" << first_error[1] << " i0=" << first_error[0] << std::endl;
         std::cerr << std::endl << "Result:" << std::endl;
@@ -7118,14 +7095,14 @@ static void ggml_vk_check_results_1(ggml_backend_vk_context * ctx, ggml_compute_
         ggml_vk_print_graph_origin(tensor, done);
         GGML_ASSERT(false);
     } else {
-        std::cerr << check_counter << " " << tensor->name << " op=" << ggml_op_name(tensor->op) << " backend=" << tensor->backend << " avg_err=" << avg_err << std::endl;
+        std::cerr << check_counter << " " << tensor->name << " op=" << ggml_op_name(tensor->op) << " avg_err=" << avg_err << std::endl;
     }
 
     free(comp_result);
     comp_result = nullptr;
     comp_size = 0;
 
-    if (tensor->backend == GGML_BACKEND_TYPE_GPU) {
+    if (ggml_backend_buffer_is_vk(tensor->buffer)) {
         free(tensor_data);
     }
 }
diff --git a/ggml.c b/ggml.c
index 55152bce4..9e72b7a76 100644
--- a/ggml.c
+++ b/ggml.c
@@ -406,10 +406,10 @@ void ggml_fp32_to_bf16_row(const float * x, ggml_bf16_t * y, int64_t n) {
   int i = 0;
 #if defined(__AVX512BF16__)
   for (; i + 32 <= n; i += 32) {
-        _mm512_storeu_ps(
-            (__m512 *)(y + i),
-            (__m512)_mm512_cvtne2ps_pbh(_mm512_loadu_ps(x + i + 16),
-                                        _mm512_loadu_ps(x + i)));
+        _mm512_storeu_si512(
+            (__m512i *)(y + i),
+            m512i(_mm512_cvtne2ps_pbh(_mm512_loadu_ps(x + i + 16),
+                                _mm512_loadu_ps(x + i))));
   }
 #endif
     for (; i < n; i++) {
@@ -871,22 +871,14 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
     },
     [GGML_TYPE_IQ4_XS] = {
         .type_name                = "iq4_xs",
-#if QK_K == 64
-        .blck_size                = QK4_NL,
-#else
         .blck_size                = QK_K,
-#endif
         .type_size                = sizeof(block_iq4_xs),
         .is_quantized             = true,
         .to_float                 = (ggml_to_float_t) dequantize_row_iq4_xs,
         .from_float               = quantize_row_iq4_xs,
         .from_float_reference     = (ggml_from_float_t)quantize_row_iq4_xs_reference,
         .vec_dot                  = ggml_vec_dot_iq4_xs_q8_K,
-#if QK_K == 64
-        .vec_dot_type             = GGML_TYPE_Q8_0,
-#else
         .vec_dot_type             = GGML_TYPE_Q8_K,
-#endif
         .nrows                    = 1,
     },
     [GGML_TYPE_Q8_K] = {
@@ -1523,6 +1515,195 @@ static inline void __sse_f16x4_store(ggml_fp16_t *x, __m128 y) {
 #define GGML_F16_VEC_MUL             GGML_F32Cx4_MUL
 #define GGML_F16_VEC_REDUCE          GGML_F32Cx4_REDUCE
 
+#elif defined(__loongarch_asx)
+
+#define GGML_SIMD
+
+// F32 LASX
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  8
+
+#define GGML_F32x8         __m256
+#define GGML_F32x8_ZERO    (__m256)__lasx_xvldi(0)
+#define GGML_F32x8_SET1(x) (__m256)__lasx_xvreplfr2vr_s((x))
+#define GGML_F32x8_LOAD(x) (__m256)__lasx_xvld((x), 0)
+#define GGML_F32x8_STORE(x,y)   __lasx_xvst((y), (x), 0)
+#define GGML_F32x8_FMA(a, b, c) __lasx_xvfmadd_s(b, c, a)
+#define GGML_F32x8_ADD     __lasx_xvfadd_s
+#define GGML_F32x8_MUL     __lasx_xvfmul_s
+#define GGML_F32x8_REDUCE(res, x)                                 \
+do {                                                              \
+    int offset = GGML_F32_ARR >> 1;                               \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lasx_xvfadd_s(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lasx_xvfadd_s(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lasx_xvfadd_s(x[i], x[offset+i]);                  \
+    }                                                             \
+    float *tmp_p = (float *)&x[0]; \
+    res = tmp_p[0] + tmp_p[1] + tmp_p[2] + tmp_p[3] + tmp_p[4] + tmp_p[5] + tmp_p[6] + tmp_p[7];  \
+} while (0)
+// TODO: is this optimal ?
+
+#define GGML_F32_VEC        GGML_F32x8
+#define GGML_F32_VEC_ZERO   GGML_F32x8_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x8_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x8_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x8_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x8_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x8_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x8_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x8_REDUCE
+
+// F16 LASX
+
+#define GGML_F16_STEP 32
+#define GGML_F16_EPR  8
+
+// F16 arithmetic is not supported by AVX, so we use F32 instead
+
+#define GGML_F32Cx8             __m256
+#define GGML_F32Cx8_ZERO    (__m256)__lasx_xvldi(0)
+#define GGML_F32Cx8_SET1(x) (__m256)__lasx_xvreplgr2vr_w((x))
+
+static inline __m256 __lasx_f32cx8_load(ggml_fp16_t *x) {
+    float tmp[8];
+
+    for (int i = 0; i < 8; i++) {
+        tmp[i] = GGML_FP16_TO_FP32(x[i]);
+    }
+
+    return (__m256)__lasx_xvld(tmp, 0);
+}
+static inline void __lasx_f32cx8_store(ggml_fp16_t *x, __m256 y) {
+    float arr[8];
+
+    __lasx_xvst(y, arr, 0);
+
+    for (int i = 0; i < 8; i++)
+        x[i] = GGML_FP32_TO_FP16(arr[i]);
+}
+#define GGML_F32Cx8_LOAD(x)     __lasx_f32cx8_load(x)
+#define GGML_F32Cx8_STORE(x, y) __lasx_f32cx8_store(x, y)
+
+#define GGML_F32Cx8_FMA         GGML_F32x8_FMA
+#define GGML_F32Cx8_ADD         __lasx_xvfadd_s
+#define GGML_F32Cx8_MUL         __lasx_xvfmul_s
+#define GGML_F32Cx8_REDUCE      GGML_F32x8_REDUCE
+
+#define GGML_F16_VEC                GGML_F32Cx8
+#define GGML_F16_VEC_ZERO           GGML_F32Cx8_ZERO
+#define GGML_F16_VEC_SET1           GGML_F32Cx8_SET1
+#define GGML_F16_VEC_LOAD(p, i)     GGML_F32Cx8_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx8_STORE(p, r[i])
+#define GGML_F16_VEC_FMA            GGML_F32Cx8_FMA
+#define GGML_F16_VEC_ADD            GGML_F32Cx8_ADD
+#define GGML_F16_VEC_MUL            GGML_F32Cx8_MUL
+#define GGML_F16_VEC_REDUCE         GGML_F32Cx8_REDUCE
+
+#elif defined(__loongarch_sx)
+
+#define GGML_SIMD
+
+// F32 LSX
+
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  4
+
+#define GGML_F32x4         __m128
+#define GGML_F32x4_ZERO    __lsx_vldi(0)
+#define GGML_F32x4_SET1(x) __lsx_vinsgr2vr_w(__lsx_vldi(0),(x), 0)
+#define GGML_F32x4_LOAD(x) __lsx_vld((x), 0)
+#define GGML_F32x4_STORE((x),(y))   __lsx_vst((y), (x), 0)
+#define GGML_F32x4_FMA(a, b, c) __lsx_vfmadd_s(b, c, a)
+#define GGML_F32x4_ADD     __lsx_vfadd_s
+#define GGML_F32x4_MUL     __lsx_vfmul_s
+#define GGML_F32x4_REDUCE(res, x)                                 \
+{                                                                 \
+    int offset = GGML_F32_ARR >> 1;                               \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lsx_vfadd_s(x[i], x[offset+i]);                     \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lsx_vfadd_s(x[i], x[offset+i]);                     \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lsx_vfadd_s(x[i], x[offset+i]);                     \
+    }                                                             \
+    __m128i tmp = __lsx_vsrli_d((__m128i)x[0], 32); \
+    tmp = (__m128i)__lsx_vfadd_s((__m128)tmp, x[0]); \
+    tmp = __lsx_vpickev_w(__lsx_vldi(0), tmp); \
+    const __m128 t0 = __lsx_vshuf4i_w(tmp, 0x88); \
+    tmp = __lsx_vsrli_d((__m128i)t0, 32); \
+    tmp = (__m128i)__lsx_vfadd_s((__m128)tmp, t0); \
+    tmp = __lsx_vpickev_w(__lsx_vldi(0), tmp); \
+    res = (ggml_float) __lsx_vpickve2gr_w(__lsx_vshuf4i_w(tmp, 0x88), 0);        \
+}
+
+#define GGML_F32_VEC        GGML_F32x4
+#define GGML_F32_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x4_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x4_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
+
+// F16 LSX
+
+#define GGML_F16_STEP 32
+#define GGML_F16_EPR  4
+
+static inline __m128 __lsx_f16x4_load(ggml_fp16_t *x) {
+    float tmp[4];
+
+    tmp[0] = GGML_FP16_TO_FP32(x[0]);
+    tmp[1] = GGML_FP16_TO_FP32(x[1]);
+    tmp[2] = GGML_FP16_TO_FP32(x[2]);
+    tmp[3] = GGML_FP16_TO_FP32(x[3]);
+
+    return __lsx_vld(tmp, 0);
+}
+
+static inline void __lsx_f16x4_store(ggml_fp16_t *x, __m128 y) {
+    float arr[4];
+
+    __lsx_vst(y, arr, 0);
+
+    x[0] = GGML_FP32_TO_FP16(arr[0]);
+    x[1] = GGML_FP32_TO_FP16(arr[1]);
+    x[2] = GGML_FP32_TO_FP16(arr[2]);
+    x[3] = GGML_FP32_TO_FP16(arr[3]);
+}
+
+#define GGML_F32Cx4             __m128
+#define GGML_F32Cx4_ZERO        __lsx_vldi(0)
+#define GGML_F32Cx4_SET1(x)     __lsx_vinsgr2vr_w(__lsx_vldi(0),(x), 0)
+#define GGML_F32Cx4_LOAD(x)     __lsx_f16x4_load(x)
+#define GGML_F32Cx4_STORE(x, y) __lsx_f16x4_store(x, y)
+#define GGML_F32Cx4_FMA         GGML_F32x4_FMA
+#define GGML_F32Cx4_ADD         __lsx_vfadd_s
+#define GGML_F32Cx4_MUL         __lsx_vfmul_s
+#define GGML_F32Cx4_REDUCE      GGML_F32x4_REDUCE
+
+#define GGML_F16_VEC                 GGML_F32Cx4
+#define GGML_F16_VEC_ZERO            GGML_F32Cx4_ZERO
+#define GGML_F16_VEC_SET1            GGML_F32Cx4_SET1
+#define GGML_F16_VEC_LOAD(p, i)      GGML_F32Cx4_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i)  GGML_F32Cx4_STORE(p, r[i])
+#define GGML_F16_VEC_FMA             GGML_F32Cx4_FMA
+#define GGML_F16_VEC_ADD             GGML_F32Cx4_ADD
+#define GGML_F16_VEC_MUL             GGML_F32Cx4_MUL
+#define GGML_F16_VEC_REDUCE          GGML_F32Cx4_REDUCE
+
 #endif
 
 // GGML_F32_ARR / GGML_F16_ARR
@@ -1666,10 +1847,10 @@ static void ggml_vec_dot_bf16(int n, float * restrict s, size_t bs, ggml_bf16_t
     __m512 c1 = _mm512_setzero_ps();
     __m512 c2 = _mm512_setzero_ps();
     for (; i + 64 <= n; i += 64) {
-        c1 = _mm512_dpbf16_ps(c1, (__m512bh)_mm512_loadu_ps((const float *)(x + i)),
-                              (__m512bh)_mm512_loadu_ps((const float *)(y + i)));
-        c2 = _mm512_dpbf16_ps(c2, (__m512bh)_mm512_loadu_ps((const float *)(x + i + 32)),
-                              (__m512bh)_mm512_loadu_ps((const float *)(y + i + 32)));
+        c1 = _mm512_dpbf16_ps(c1, m512bh(_mm512_loadu_si512((x + i))),
+                             m512bh(_mm512_loadu_si512((y + i))));
+        c2 = _mm512_dpbf16_ps(c2, m512bh(_mm512_loadu_si512((x + i + 32))),
+                             m512bh(_mm512_loadu_si512((y + i + 32))));
     }
     sumf += (ggml_float)_mm512_reduce_add_ps(c1);
     sumf += (ggml_float)_mm512_reduce_add_ps(c2);
@@ -2076,7 +2257,7 @@ inline static float ggml_silu_f32(float x) {
     return x/(1.0f + expf(-x));
 }
 
-#if defined(__ARM_NEON)
+#if defined(__ARM_NEON) && defined(__aarch64__)
 
 // adapted from arm limited optimized routine
 // the maximum error is 1.45358 plus 0.5 ulps
@@ -2288,7 +2469,7 @@ static void ggml_vec_silu_f32(const int n, float * y, const float * x) {
     for (; i + 3 < n; i += 4) {
         _mm_storeu_ps(y + i, ggml_v_silu(_mm_loadu_ps(x + i)));
     }
-#elif defined(__ARM_NEON)
+#elif defined(__ARM_NEON) && defined(__aarch64__)
     for (; i + 3 < n; i += 4) {
         vst1q_f32(y + i, ggml_v_silu(vld1q_f32(x + i)));
     }
@@ -2335,7 +2516,7 @@ static ggml_float ggml_vec_soft_max_f32(const int n, float * y, const float * x,
 #endif
         sum += (ggml_float)_mm_cvtss_f32(val);
     }
-#elif defined(__ARM_NEON)
+#elif defined(__ARM_NEON) && defined(__aarch64__)
     for (; i + 3 < n; i += 4) {
         float32x4_t val = ggml_v_expf(vsubq_f32(vld1q_f32(x + i),
                                                 vdupq_n_f32(max)));
@@ -2489,9 +2670,7 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = {
     "ARGSORT",
     "LEAKY_RELU",
 
-    "FLASH_ATTN",
     "FLASH_ATTN_EXT",
-    "FLASH_FF",
     "FLASH_ATTN_BACK",
     "SSM_CONV",
     "SSM_SCAN",
@@ -2517,7 +2696,7 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = {
     "CROSS_ENTROPY_LOSS_BACK",
 };
 
-static_assert(GGML_OP_COUNT == 76, "GGML_OP_COUNT != 76");
+static_assert(GGML_OP_COUNT == 74, "GGML_OP_COUNT != 74");
 
 static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
     "none",
@@ -2579,9 +2758,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
     "argsort(x)",
     "leaky_relu(x)",
 
-    "flash_attn(x)",
     "flash_attn_ext(x)",
-    "flash_ff(x)",
     "flash_attn_back(x)",
     "ssm_conv(x)",
     "ssm_scan(x)",
@@ -2607,7 +2784,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
     "cross_entropy_loss_back(x,y)",
 };
 
-static_assert(GGML_OP_COUNT == 76, "GGML_OP_COUNT != 76");
+static_assert(GGML_OP_COUNT == 74, "GGML_OP_COUNT != 74");
 
 static_assert(GGML_OP_POOL_COUNT == 2, "GGML_OP_POOL_COUNT != 2");
 
@@ -6042,6 +6219,7 @@ static struct ggml_tensor * ggml_rope_impl(
         struct ggml_context * ctx,
         struct ggml_tensor  * a,
         struct ggml_tensor  * b,
+        struct ggml_tensor  * c,
         int                   n_dims,
         int                   mode,
         int                   n_ctx,
@@ -6055,10 +6233,17 @@ static struct ggml_tensor * ggml_rope_impl(
         float                 xpos_base,
         bool                  xpos_down,
         bool                  inplace) {
+    GGML_ASSERT((mode & 1) == 0 && "mode & 1 == 1 is no longer supported");
+
     GGML_ASSERT(ggml_is_vector(b));
     GGML_ASSERT(b->type == GGML_TYPE_I32);
     GGML_ASSERT(a->ne[2] == b->ne[0]);
 
+    if (c) {
+        GGML_ASSERT(c->type == GGML_TYPE_F32);
+        GGML_ASSERT(c->ne[0] >= n_dims / 2);
+    }
+
     bool is_node = false;
 
     if (a->grad) {
@@ -6082,6 +6267,7 @@ static struct ggml_tensor * ggml_rope_impl(
     result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
     result->src[0] = a;
     result->src[1] = b;
+    result->src[2] = c;
 
     return result;
 }
@@ -6094,7 +6280,7 @@ struct ggml_tensor * ggml_rope(
         int                   mode,
         int                   n_ctx) {
     return ggml_rope_impl(
-        ctx, a, b, n_dims, mode, n_ctx, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, false, false
+        ctx, a, b, NULL, n_dims, mode, n_ctx, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, false, false
     );
 }
 
@@ -6106,7 +6292,49 @@ struct ggml_tensor * ggml_rope_inplace(
         int                   mode,
         int                   n_ctx) {
     return ggml_rope_impl(
-        ctx, a, b, n_dims, mode, n_ctx, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, false, true
+        ctx, a, b, NULL, n_dims, mode, n_ctx, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, false, true
+    );
+}
+
+struct ggml_tensor * ggml_rope_ext(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * a,
+        struct ggml_tensor  * b,
+        struct ggml_tensor  * c,
+        int                   n_dims,
+        int                   mode,
+        int                   n_ctx,
+        int                   n_orig_ctx,
+        float                 freq_base,
+        float                 freq_scale,
+        float                 ext_factor,
+        float                 attn_factor,
+        float                 beta_fast,
+        float                 beta_slow) {
+    return ggml_rope_impl(
+        ctx, a, b, c, n_dims, mode, n_ctx, n_orig_ctx, freq_base, freq_scale,
+        ext_factor, attn_factor, beta_fast, beta_slow, 0.0f, false, false
+    );
+}
+
+struct ggml_tensor * ggml_rope_ext_inplace(
+        struct ggml_context * ctx,
+        struct ggml_tensor  * a,
+        struct ggml_tensor  * b,
+        struct ggml_tensor  * c,
+        int                   n_dims,
+        int                   mode,
+        int                   n_ctx,
+        int                   n_orig_ctx,
+        float                 freq_base,
+        float                 freq_scale,
+        float                 ext_factor,
+        float                 attn_factor,
+        float                 beta_fast,
+        float                 beta_slow) {
+    return ggml_rope_impl(
+        ctx, a, b, c, n_dims, mode, n_ctx, n_orig_ctx, freq_base, freq_scale,
+        ext_factor, attn_factor, beta_fast, beta_slow, 0.0f, false, true
     );
 }
 
@@ -6125,7 +6353,7 @@ struct ggml_tensor * ggml_rope_custom(
         float                 beta_fast,
         float                 beta_slow) {
     return ggml_rope_impl(
-        ctx, a, b, n_dims, mode, n_ctx, n_orig_ctx, freq_base, freq_scale,
+        ctx, a, b, NULL, n_dims, mode, n_ctx, n_orig_ctx, freq_base, freq_scale,
         ext_factor, attn_factor, beta_fast, beta_slow, 0.0f, false, false
     );
 }
@@ -6145,27 +6373,18 @@ struct ggml_tensor * ggml_rope_custom_inplace(
         float                 beta_fast,
         float                 beta_slow) {
     return ggml_rope_impl(
-        ctx, a, b, n_dims, mode, n_ctx, n_orig_ctx, freq_base, freq_scale,
+        ctx, a, b, NULL, n_dims, mode, n_ctx, n_orig_ctx, freq_base, freq_scale,
         ext_factor, attn_factor, beta_fast, beta_slow, 0.0f, false, true
     );
 }
 
-struct ggml_tensor * ggml_rope_xpos_inplace(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b,
-        int                   n_dims,
-        float                 base,
-        bool                  down) {
-    return ggml_rope_impl(ctx, a, b, n_dims, 0, 0, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, base, down, true);
-}
-
 // ggml_rope_back
 
 struct ggml_tensor * ggml_rope_back(
         struct ggml_context * ctx,
         struct ggml_tensor  * a,
         struct ggml_tensor  * b,
+        struct ggml_tensor  * c,
         int                   n_dims,
         int                   mode,
         int                   n_ctx,
@@ -6181,6 +6400,7 @@ struct ggml_tensor * ggml_rope_back(
     GGML_ASSERT(ggml_is_vector(b));
     GGML_ASSERT(b->type == GGML_TYPE_I32);
     GGML_ASSERT(a->ne[2] == b->ne[0]);
+    GGML_ASSERT(c == NULL && "freq factors not implemented yet");
 
     GGML_ASSERT((mode & 4) == 0 && "ggml_rope_back() for ChatGLM not implemented yet");
 
@@ -6724,38 +6944,6 @@ struct ggml_tensor * ggml_top_k(
     return result;
 }
 
-// ggml_flash_attn
-
-struct ggml_tensor * ggml_flash_attn(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * q,
-        struct ggml_tensor  * k,
-        struct ggml_tensor  * v,
-        bool                  masked) {
-    GGML_ASSERT(ggml_can_mul_mat(k, q));
-    // TODO: check if vT can be multiplied by (k*qT)
-
-    bool is_node = false;
-
-    if (q->grad || k->grad || v->grad) {
-        is_node = true;
-    }
-
-    //struct ggml_tensor * result = ggml_dup_tensor(ctx, q);
-    struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, GGML_MAX_DIMS, q->ne);
-
-    int32_t t = masked ? 1 : 0;
-    ggml_set_op_params(result, &t, sizeof(t));
-
-    result->op   = GGML_OP_FLASH_ATTN;
-    result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
-    result->src[0] = q;
-    result->src[1] = k;
-    result->src[2] = v;
-
-    return result;
-}
-
 // ggml_flash_attn_ext
 
 struct ggml_tensor * ggml_flash_attn_ext(
@@ -6815,38 +7003,6 @@ void ggml_flash_attn_ext_set_prec(
     ggml_set_op_params_i32(a, 2, prec_i32); // scale is on first pos, max_bias on second
 }
 
-// ggml_flash_ff
-
-struct ggml_tensor * ggml_flash_ff(
-        struct ggml_context * ctx,
-        struct ggml_tensor  * a,
-        struct ggml_tensor  * b0,
-        struct ggml_tensor  * b1,
-        struct ggml_tensor  * c0,
-        struct ggml_tensor  * c1) {
-    GGML_ASSERT(ggml_can_mul_mat(b0, a));
-    // TODO: more checks
-
-    bool is_node = false;
-
-    if (a->grad || b0->grad || b1->grad || c0->grad || c1->grad) {
-        is_node = true;
-    }
-
-    //struct ggml_tensor * result = ggml_dup_tensor(ctx, a);
-    struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, GGML_MAX_DIMS, a->ne);
-
-    result->op   = GGML_OP_FLASH_FF;
-    result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
-    result->src[0] = a;
-    result->src[1] = b0;
-    result->src[2] = b1;
-    result->src[3] = c0;
-    result->src[4] = c1;
-
-    return result;
-}
-
 // ggml_flash_attn_back
 
 struct ggml_tensor * ggml_flash_attn_back(
@@ -6856,6 +7012,8 @@ struct ggml_tensor * ggml_flash_attn_back(
         struct ggml_tensor  * v,
         struct ggml_tensor  * d,
         bool                  masked) {
+    GGML_ASSERT(false && "TODO: adapt to ggml_flash_attn_ext() changes");
+
     GGML_ASSERT(ggml_can_mul_mat(k, q));
     // TODO: check if vT can be multiplied by (k*qT)
 
@@ -14115,6 +14273,7 @@ static void ggml_compute_forward_rope_f32(
 
     const struct ggml_tensor * src0 = dst->src[0];
     const struct ggml_tensor * src1 = dst->src[1];
+    const struct ggml_tensor * src2 = dst->src[2];
 
     if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) {
         return;
@@ -14174,6 +14333,17 @@ static void ggml_compute_forward_rope_f32(
     const bool is_neox = mode & 2;
     const bool is_glm  = mode & 4;
 
+    const float * freq_factors = NULL;
+    if (is_neox) {
+        if (src2 != NULL) {
+            GGML_ASSERT(src2->type == GGML_TYPE_F32);
+            GGML_ASSERT(src2->ne[0] >= n_dims / 2);
+            freq_factors = (const float *) src2->data;
+        }
+    } else {
+        GGML_ASSERT(src2 == NULL && "TODO: freq_factors not implemented for !is_neox");
+    }
+
     // backward process uses inverse rotation by cos and sin.
     // cos and sin build a rotation matrix, where the inverse is the transpose.
     // this essentially just switches the sign of sin.
@@ -14250,10 +14420,11 @@ static void ggml_compute_forward_rope_f32(
 
                             // simplified from `(ib * n_dims + ic) * inv_ndims`
                             float cur_rot = inv_ndims * ic - ib;
+                            float freq_factor = freq_factors ? freq_factors[ic/2] : 1.0f;
 
                             float cos_theta, sin_theta;
                             rope_yarn(
-                                theta_base, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor,
+                                theta_base/freq_factor, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor,
                                 &cos_theta, &sin_theta
                             );
                             sin_theta *= sin_sign;
@@ -14286,6 +14457,7 @@ static void ggml_compute_forward_rope_f32(
     }
 }
 
+// TODO: deduplicate f16/f32 code
 static void ggml_compute_forward_rope_f16(
         const struct ggml_compute_params * params,
         struct ggml_tensor * dst,
@@ -14293,6 +14465,7 @@ static void ggml_compute_forward_rope_f16(
 
     const struct ggml_tensor * src0 = dst->src[0];
     const struct ggml_tensor * src1 = dst->src[1];
+    const struct ggml_tensor * src2 = dst->src[2];
 
     if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) {
         return;
@@ -14345,6 +14518,17 @@ static void ggml_compute_forward_rope_f16(
     const bool is_neox = mode & 2;
     const bool is_glm  = mode & 4;
 
+    const float * freq_factors = NULL;
+    if (is_neox) {
+        if (src2 != NULL) {
+            GGML_ASSERT(src2->type == GGML_TYPE_F32);
+            GGML_ASSERT(src2->ne[0] >= n_dims / 2);
+            freq_factors = (const float *) src2->data;
+        }
+    } else {
+        GGML_ASSERT(src2 == NULL && "TODO: freq_factors not implemented for !is_neox");
+    }
+
     // backward process uses inverse rotation by cos and sin.
     // cos and sin build a rotation matrix, where the inverse is the transpose.
     // this essentially just switches the sign of sin.
@@ -14417,10 +14601,11 @@ static void ggml_compute_forward_rope_f16(
 
                             // simplified from `(ib * n_dims + ic) * inv_ndims`
                             float cur_rot = inv_ndims * ic - ib;
+                            float freq_factor = freq_factors ? freq_factors[ic/2] : 1.0f;
 
                             float cos_theta, sin_theta;
                             rope_yarn(
-                                theta_base, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor,
+                                theta_base/freq_factor, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor,
                                 &cos_theta, &sin_theta
                             );
                             sin_theta *= sin_sign;
@@ -15458,400 +15643,6 @@ static void ggml_compute_forward_argsort(
     }
 }
 
-// ggml_compute_forward_flash_attn
-
-static void ggml_compute_forward_flash_attn_f32(
-        const struct ggml_compute_params * params,
-        const bool masked,
-        struct ggml_tensor * dst) {
-
-    const struct ggml_tensor * q = dst->src[0];
-    const struct ggml_tensor * k = dst->src[1];
-    const struct ggml_tensor * v = dst->src[2];
-
-    int64_t t0 = ggml_perf_time_us();
-    UNUSED(t0);
-
-    GGML_TENSOR_LOCALS(int64_t, neq, q,   ne)
-    GGML_TENSOR_LOCALS(size_t,  nbq, q,   nb)
-    GGML_TENSOR_LOCALS(int64_t, nek, k,   ne)
-    GGML_TENSOR_LOCALS(size_t,  nbk, k,   nb)
-    GGML_TENSOR_LOCALS(int64_t, nev, v,   ne)
-    GGML_TENSOR_LOCALS(size_t,  nbv, v,   nb)
-    GGML_TENSOR_LOCALS(int64_t, ne,  dst, ne)
-    GGML_TENSOR_LOCALS(size_t,  nb,  dst, nb)
-
-    const int ith = params->ith;
-    const int nth = params->nth;
-
-    const int64_t D = neq0;
-    const int64_t N = neq1;
-    const int64_t P = nek1 - N;
-    const int64_t M = P + N;
-
-    const int Mup = ggml_up(M, GGML_SOFT_MAX_UNROLL);
-
-    GGML_ASSERT(ne0 == D);
-    GGML_ASSERT(ne1 == N);
-    GGML_ASSERT(P >= 0);
-
-    GGML_ASSERT(nbq0 == sizeof(float));
-    GGML_ASSERT(nbk0 == sizeof(float));
-    GGML_ASSERT(nbv0 == sizeof(float));
-
-    GGML_ASSERT(neq0 == D);
-    GGML_ASSERT(nek0 == D);
-    GGML_ASSERT(nev1 == D);
-
-    GGML_ASSERT(neq1 == N);
-    GGML_ASSERT(nek1 == N + P);
-    GGML_ASSERT(nev1 == D);
-
-    // dst cannot be transposed or permuted
-    GGML_ASSERT(nb0 == sizeof(float));
-    GGML_ASSERT(nb0 <= nb1);
-    GGML_ASSERT(nb1 <= nb2);
-    GGML_ASSERT(nb2 <= nb3);
-
-    if (params->type == GGML_TASK_TYPE_INIT) {
-        return;
-    }
-
-    if (params->type == GGML_TASK_TYPE_FINALIZE) {
-        return;
-    }
-
-    // parallelize by q rows using ggml_vec_dot_f32
-
-    // total rows in q
-    const int nr = neq1*neq2*neq3;
-
-    // rows per thread
-    const int dr = (nr + nth - 1)/nth;
-
-    // row range for this thread
-    const int ir0 = dr*ith;
-    const int ir1 = MIN(ir0 + dr, nr);
-
-    const float scale = 1.0f/sqrtf(D);
-
-    //printf("P=%d N=%d D=%d ir0=%d ir1=%d scale = %f\n", P, N, D, ir0, ir1, scale);
-
-    for (int ir = ir0; ir < ir1; ++ir) {
-        // q indices
-        const int iq3 = ir/(neq2*neq1);
-        const int iq2 = (ir - iq3*neq2*neq1)/neq1;
-        const int iq1 = (ir - iq3*neq2*neq1 - iq2*neq1);
-
-        float * S = (float *) params->wdata + ith*(Mup + CACHE_LINE_SIZE_F32);
-
-        for (int i = M; i < Mup; ++i) {
-            S[i] = -INFINITY;
-        }
-
-        const int64_t masked_begin = masked ? (P + iq1 + 1) : M;
-        for (int64_t ic = 0; ic < masked_begin; ++ic) {
-            // k indices
-            const int ik3 = iq3;
-            const int ik2 = iq2 % nek2;
-            const int ik1 = ic;
-
-            // S indices
-            const int i1 = ik1;
-
-            ggml_vec_dot_f32(neq0,
-                    S + i1, 0,
-                    (float *) ((char *) k->data + (ik1*nbk1 + ik2*nbk2 + ik3*nbk3)), 0,
-                    (float *) ((char *) q->data + (iq1*nbq1 + iq2*nbq2 + iq3*nbq3)), 0, 1);
-        }
-
-        // scale
-        ggml_vec_scale_f32(masked_begin, S, scale);
-
-        for (int64_t i = masked_begin; i < M; i++) {
-            S[i] = -INFINITY;
-        }
-
-        // softmax
-        // exclude known -INF S[..] values from max and loop
-        // dont forget to set their SW values to zero
-        {
-            float max = -INFINITY;
-            ggml_vec_max_f32(masked_begin, &max, S);
-
-            ggml_float sum = 0.0;
-            {
-#ifdef GGML_SOFT_MAX_ACCELERATE
-                max = -max;
-                vDSP_vsadd(S, 1, &max, S, 1, Mup);
-                vvexpf(S, S, &Mup);
-                ggml_vec_sum_f32(Mup, &sum, S);
-#else
-                sum = ggml_vec_soft_max_f32(Mup, S, S, max);
-#endif
-            }
-
-            assert(sum > 0.0);
-
-            sum = 1.0/sum;
-            ggml_vec_scale_f32(masked_begin, S, sum);
-
-#ifndef NDEBUG
-            for (int i = 0; i < masked_begin; ++i) {
-                assert(!isnan(S[i]));
-                assert(!isinf(S[i]));
-            }
-#endif
-        }
-
-        for (int64_t ic = 0; ic < nev1; ++ic) {
-            // dst indices
-            const int i1 = iq1;
-            const int i2 = iq2;
-            const int i3 = iq3;
-
-            // v indices
-            const int iv2 = iq2 % nev2;
-            const int iv3 = iq3;
-
-            ggml_vec_dot_f32(masked_begin,
-                    (float *) ((char *) dst->data + (ic*nb0 + i1*nb1  + i2*nb2   + i3*nb3)), 0,
-                    (float *) ((char *) v->data   + (         ic*nbv1 + iv2*nbv2 + iv3*nbv3)), 0,
-                    S, 0, 1);
-        }
-    }
-}
-
-static void ggml_compute_forward_flash_attn_f16(
-        const struct ggml_compute_params * params,
-        const bool masked,
-        struct ggml_tensor * dst) {
-
-    const struct ggml_tensor * q = dst->src[0];
-    const struct ggml_tensor * k = dst->src[1];
-    const struct ggml_tensor * v = dst->src[2];
-
-    int64_t t0 = ggml_perf_time_us();
-    UNUSED(t0);
-
-    GGML_TENSOR_LOCALS(int64_t, neq, q,   ne)
-    GGML_TENSOR_LOCALS(size_t,  nbq, q,   nb)
-    GGML_TENSOR_LOCALS(int64_t, nek, k,   ne)
-    GGML_TENSOR_LOCALS(size_t,  nbk, k,   nb)
-    GGML_TENSOR_LOCALS(int64_t, nev, v,   ne)
-    GGML_TENSOR_LOCALS(size_t,  nbv, v,   nb)
-    GGML_TENSOR_LOCALS(int64_t, ne,  dst, ne)
-    GGML_TENSOR_LOCALS(size_t,  nb,  dst, nb)
-
-    const int ith = params->ith;
-    const int nth = params->nth;
-
-    const int64_t D = neq0;
-    const int64_t N = neq1;
-    const int64_t P = nek1 - N;
-    const int64_t M = P + N;
-
-    const int Mup = ggml_up(M, GGML_SOFT_MAX_UNROLL);
-
-    GGML_ASSERT(ne0 == D);
-    GGML_ASSERT(ne1 == N);
-    GGML_ASSERT(P >= 0);
-
-    GGML_ASSERT(nbq0 == sizeof(ggml_fp16_t));
-    GGML_ASSERT(nbk0 == sizeof(ggml_fp16_t));
-    GGML_ASSERT(nbv0 == sizeof(ggml_fp16_t));
-
-    GGML_ASSERT(neq0 == D);
-    GGML_ASSERT(nek0 == D);
-    GGML_ASSERT(nev1 == D);
-
-    GGML_ASSERT(neq1 == N);
-    GGML_ASSERT(nek1 == N + P);
-    GGML_ASSERT(nev1 == D);
-
-    // dst cannot be transposed or permuted
-    GGML_ASSERT(nb0 == sizeof(float));
-    GGML_ASSERT(nb0 <= nb1);
-    GGML_ASSERT(nb1 <= nb2);
-    GGML_ASSERT(nb2 <= nb3);
-
-    if (params->type == GGML_TASK_TYPE_INIT) {
-        return;
-    }
-
-    if (params->type == GGML_TASK_TYPE_FINALIZE) {
-        return;
-    }
-
-    // parallelize by q rows using ggml_vec_dot_f32
-
-    // total rows in q
-    const int nr = neq1*neq2*neq3;
-
-    // rows per thread
-    const int dr = (nr + nth - 1)/nth;
-
-    // row range for this thread
-    const int ir0 = dr*ith;
-    const int ir1 = MIN(ir0 + dr, nr);
-
-    const float scale = 1.0f/sqrtf(D);
-
-    //printf("P=%d N=%d D=%d ir0=%d ir1=%d scale = %f\n", P, N, D, ir0, ir1, scale);
-
-    for (int ir = ir0; ir < ir1; ++ir) {
-        // q indices
-        const int iq3 = ir/(neq2*neq1);
-        const int iq2 = (ir - iq3*neq2*neq1)/neq1;
-        const int iq1 = (ir - iq3*neq2*neq1 - iq2*neq1);
-
-        float * S = (float *) params->wdata + ith*(2*Mup + CACHE_LINE_SIZE_F32);
-
-        for (int i = M; i < Mup; ++i) {
-            S[i] = -INFINITY;
-        }
-
-        if (GGML_VEC_DOT_UNROLL > 2 || nek1 % GGML_VEC_DOT_UNROLL != 0) {
-            for (int64_t ic = 0; ic < nek1; ++ic) {
-                // k indices
-                const int ik3 = iq3;
-                const int ik2 = iq2 % nek2;
-                const int ik1 = ic;
-
-                // S indices
-                const int i1 = ik1;
-
-                ggml_vec_dot_f16(neq0,
-                        S + i1, 0,
-                        (ggml_fp16_t *) ((char *) k->data + (ik1*nbk1 + ik2*nbk2 + ik3*nbk3)), 0,
-                        (ggml_fp16_t *) ((char *) q->data + (iq1*nbq1 + iq2*nbq2 + iq3*nbq3)), 0, 1);
-            }
-        } else {
-            for (int64_t ic = 0; ic < nek1; ic += GGML_VEC_DOT_UNROLL) {
-                // k indices
-                const int ik3 = iq3;
-                const int ik2 = iq2 % nek2;
-                const int ik1 = ic;
-
-                // S indices
-                const int i1 = ik1;
-
-                ggml_vec_dot_f16_unroll(neq0, nbk1,
-                        S + i1,
-                        ((char *) k->data + (ik1*nbk1 + ik2*nbk2 + ik3*nbk3)),
-                        (ggml_fp16_t *) ((char *) q->data + (iq1*nbq1 + iq2*nbq2 + iq3*nbq3)));
-            }
-        }
-
-        // scale
-        ggml_vec_scale_f32(nek1, S, scale);
-
-        if (masked) {
-            for (int64_t i = P; i < M; i++) {
-                if (i > P + iq1) {
-                    S[i] = -INFINITY;
-                }
-            }
-        }
-
-        // softmax
-        // todo: exclude known -INF S[..] values from max and loop, assuming their results to be zero.
-        // dont forget to set their S values to zero
-        {
-            float max = -INFINITY;
-            ggml_vec_max_f32(M, &max, S);
-
-            ggml_float sum = 0.0;
-            {
-#ifdef GGML_SOFT_MAX_ACCELERATE
-                max = -max;
-                vDSP_vsadd(S, 1, &max, S, 1, Mup);
-                vvexpf(S, S, &Mup);
-                ggml_vec_sum_f32(Mup, &sum, S);
-#else
-                sum = ggml_vec_soft_max_f32(Mup, S, S, max);
-#endif
-            }
-
-            assert(sum > 0.0);
-
-            sum = 1.0/sum;
-            ggml_vec_scale_f32(M, S, sum);
-
-#ifndef NDEBUG
-            for (int i = 0; i < M; ++i) {
-                assert(!isnan(S[i]));
-                assert(!isinf(S[i]));
-            }
-#endif
-        }
-
-        ggml_fp16_t * S16 = (ggml_fp16_t *) ((float *) params->wdata + ith*(2*Mup + CACHE_LINE_SIZE_F32) + Mup);
-
-        for (int64_t i = 0; i < M; i++) {
-            S16[i] = GGML_FP32_TO_FP16(S[i]);
-        }
-
-        // todo: exclude known zero S[..] values from dot (reducing nev0 and increasing begin of v and S16).
-        if (GGML_VEC_DOT_UNROLL == 1 || (nev1 % GGML_VEC_DOT_UNROLL != 0)) {
-            for (int64_t ic = 0; ic < nev1; ++ic) {
-                // dst indices
-                const int i1 = iq1;
-                const int i2 = iq2;
-                const int i3 = iq3;
-
-                // v indices
-                const int iv2 = iq2 % nev2;
-                const int iv3 = iq3;
-
-                ggml_vec_dot_f16(nev0,
-                        (float *)       ((char *) dst->data + (ic*nb0 + i1*nb1  + i2*nb2   + i3*nb3)), 0,
-                        (ggml_fp16_t *) ((char *) v->data   + (         ic*nbv1 + iv2*nbv2 + iv3*nbv3)), 0,
-                        S16, 0, 1);
-            }
-        } else {
-            for (int64_t ic = 0; ic < nev1; ic += GGML_VEC_DOT_UNROLL) {
-                // dst indices
-                const int i1 = iq1;
-                const int i2 = iq2;
-                const int i3 = iq3;
-
-                // v indices
-                const int iv2 = iq2 % nev2;
-                const int iv3 = iq3;
-
-                ggml_vec_dot_f16_unroll(nev0, nbv1,
-                        (float *) ((char *) dst->data + (ic*nb0 + i1*nb1  + i2*nb2   + i3*nb3)),
-                        ((char *)             v->data + (         ic*nbv1 + iv2*nbv2 + iv3*nbv3)),
-                        S16);
-            }
-        }
-    }
-}
-
-static void ggml_compute_forward_flash_attn(
-        const struct ggml_compute_params * params,
-        const bool masked,
-        struct ggml_tensor * dst) {
-
-    const struct ggml_tensor * q = dst->src[0];
-
-    switch (q->type) {
-        case GGML_TYPE_F16:
-            {
-                ggml_compute_forward_flash_attn_f16(params, masked, dst);
-            } break;
-        case GGML_TYPE_F32:
-            {
-                ggml_compute_forward_flash_attn_f32(params, masked, dst);
-            } break;
-        default:
-            {
-                GGML_ASSERT(false);
-            } break;
-    }
-}
-
 // ggml_compute_forward_flash_attn_ext
 
 static void ggml_compute_forward_flash_attn_ext_f16(
@@ -15882,9 +15673,10 @@ static void ggml_compute_forward_flash_attn_ext_f16(
     GGML_ASSERT(ne0 == D);
     GGML_ASSERT(ne2 == N);
 
-    GGML_ASSERT(nbq0 == sizeof(float));
-    GGML_ASSERT(nbk0 == sizeof(ggml_fp16_t));
-    GGML_ASSERT(nbv0 == sizeof(ggml_fp16_t));
+    // input tensor rows must be contiguous
+    GGML_ASSERT(nbq0 == ggml_type_size(q->type));
+    GGML_ASSERT(nbk0 == ggml_type_size(k->type));
+    GGML_ASSERT(nbv0 == ggml_type_size(v->type));
 
     GGML_ASSERT(neq0 == D);
     GGML_ASSERT(nek0 == D);
@@ -15938,6 +15730,11 @@ static void ggml_compute_forward_flash_attn_ext_f16(
     const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
     const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
 
+    enum ggml_type    const k_vec_dot_type = type_traits[k->type].vec_dot_type;
+    ggml_from_float_t const q_to_vec_dot   = type_traits[k_vec_dot_type].from_float;
+    ggml_vec_dot_t    const kq_vec_dot     = type_traits[k->type].vec_dot;
+    ggml_to_float_t   const v_to_float     = type_traits[v->type].to_float;
+
     // loop over n_batch and n_head
     for (int ir = ir0; ir < ir1; ++ir) {
         // q indices
@@ -15945,17 +15742,22 @@ static void ggml_compute_forward_flash_attn_ext_f16(
         const int iq2 = (ir - iq3*neq2*neq1)/neq1;
         const int iq1 = (ir - iq3*neq2*neq1 - iq2*neq1);
 
-        const uint32_t h = iq2; // head
+        const uint32_t h = iq2; // head index
         const float slope = (max_bias > 0.0f) ? h < n_head_log2 ? powf(m0, h + 1) : powf(m1, 2*(h - n_head_log2) + 1) : 1.0f;
 
-        float S = 0.0f;
-        float M = -INFINITY;
+        float S = 0.0f;      // sum
+        float M = -INFINITY; // maximum KQ value
 
-        float       * V32 = (float       *) params->wdata + ith*(2*D + CACHE_LINE_SIZE_F32);
-        ggml_fp16_t * Q16 = (ggml_fp16_t *) (V32); // reuse memory
-        ggml_fp16_t * V16 = (ggml_fp16_t *) (V32 + D);
+        float       * VKQ32 = (float       *) params->wdata + ith*(3*D + CACHE_LINE_SIZE_F32); // FP32 VKQ accumulator
+        float       * V32   =                 (VKQ32 + 1*D); // (temporary) FP32 V buffer
+        ggml_fp16_t * VKQ16 = (ggml_fp16_t *) (VKQ32 + 1*D); // (temporary) FP16 VKQ accumulator
+        ggml_fp16_t * Q_q   = (ggml_fp16_t *) (VKQ32 + 2*D); // (temporary) buffer for Q converted to quantized/FP16
 
-        memset(V16, 0, D*sizeof(ggml_fp16_t));
+        if (v->type == GGML_TYPE_F16) {
+            memset(VKQ16, 0, D*sizeof(ggml_fp16_t));
+        } else {
+            memset(VKQ32, 0, D*sizeof(float));
+        }
 
         const ggml_fp16_t * mp = mask ? (ggml_fp16_t *)((char *) mask->data + iq1*mask->nb[1]) : NULL;
 
@@ -15967,6 +15769,9 @@ static void ggml_compute_forward_flash_attn_ext_f16(
         const int iv3 = iq3 / rv3;
         const int iv2 = iq2 / rv2;
 
+        const float * pq = (const float *) ((char *) q->data + (iq1*nbq1 + iq2*nbq2 + iq3*nbq3));
+        q_to_vec_dot(pq, Q_q, D);
+
         // online softmax / attention
         // loop over n_kv and n_head_kv
         // ref: https://arxiv.org/pdf/2112.05682.pdf
@@ -15976,51 +15781,66 @@ static void ggml_compute_forward_flash_attn_ext_f16(
                 continue;
             }
 
-            float s;
+            float s; // KQ value
 
-            // convert Q to F16 in V32
-            {
-                const float * pq = (const float *) ((char *) q->data + (iq1*nbq1 + iq2*nbq2 + iq3*nbq3));
+            const char * k_data = (const char *) k->data + ( ic*nbk1 + ik2*nbk2 + ik3*nbk3);
+            kq_vec_dot(D, &s, 0, k_data, 0, Q_q, 0, 1);
 
-                for (int64_t d = 0; d < D; ++d) {
-                    Q16[d] = GGML_FP32_TO_FP16(pq[d]);
-                }
-            }
-
-            ggml_vec_dot_f16(D,
-                    &s, 0,
-                    (ggml_fp16_t *) ((char *) k->data + ( ic*nbk1 + ik2*nbk2 + ik3*nbk3)), 0,
-                    Q16, 0, 1);
-
-            s = s*scale + mv;
+            s = s*scale + mv; // scale KQ value and apply mask
 
             const float Mold = M;
 
-            float ms = 1.0f;
-            float vs = 1.0f;
+            float ms = 1.0f; // upon new higher max val, scale VKQ and KQ sum with this value
+            float vs = 1.0f; // post-softmax KQ value, expf(s - M)
 
-            if (s > M) {
-                M = s;
-                ms = expf(Mold - M);
+            const char * v_data = ((const char *) v->data + (ic*nbv1 + iv2*nbv2 + iv3*nbv3));
 
-                // V = V*expf(Mold - M)
-                ggml_vec_scale_f16(D, V16, ms);
+            if (v->type== GGML_TYPE_F16) {
+                if (s > M) {
+                    // s is new maximum, ms < 1.0f, vs == expf(s - s) == 1.0f
+                    M = s;
+                    ms = expf(Mold - M);
+
+                    // V = V*expf(Mold - M)
+                    ggml_vec_scale_f16(D, VKQ16, ms);
+                } else {
+                    // no new maximum, ms == 1.0f, vs != 1.0f
+                    vs = expf(s - M);
+                }
+
+                // V += v*expf(s - M)
+                ggml_vec_mad_f16(D, VKQ16, (const ggml_fp16_t *) v_data, vs);
             } else {
-                vs = expf(s - M);
+                if (s > M) {
+                    // s is new maximum, ms < 1.0f, vs == expf(s - s) == 1.0f
+                    M = s;
+                    ms = expf(Mold - M);
+
+                    // V = V*expf(Mold - M)
+                    ggml_vec_scale_f32(D, VKQ32, ms);
+                } else {
+                    // no new maximum, ms == 1.0f, vs != 1.0f
+                    vs = expf(s - M);
+                }
+
+                v_to_float(v_data, V32, D);
+
+                // V += v*expf(s - M)
+                ggml_vec_mad_f32(D, VKQ32, V32, vs);
             }
 
-            const ggml_fp16_t * v16 = (const ggml_fp16_t *) ((char *) v->data + (ic*nbv1 + iv2*nbv2 + iv3*nbv3));
+            S = S*ms + vs; // scale and increment sum with partial sum
+        }
 
-            // V += v*expf(s - M)
-            ggml_vec_mad_f16(D, V16, v16, vs);
-
-            S = S*ms + vs;
+        if (v->type == GGML_TYPE_F16) {
+            for (int64_t d = 0; d < D; ++d) {
+                VKQ32[d] = GGML_FP16_TO_FP32(VKQ16[d]);
+            }
         }
 
         // V /= S
-        for (int64_t d = 0; d < D; ++d) {
-            V32[d] = GGML_FP16_TO_FP32(V16[d])/S;
-        }
+        const float S_inv = 1.0f/S;
+        ggml_vec_scale_f32(D, VKQ32, S_inv);
 
         // dst indices
         const int i1 = iq1;
@@ -16031,7 +15851,7 @@ static void ggml_compute_forward_flash_attn_ext_f16(
         //memcpy((char *) dst->data + (i1*nb1 + i2*nb2 + i3*nb3), V, nev0*sizeof(float));
 
         // permute(0, 2, 1, 3)
-        memcpy((char *) dst->data + (i3*ne2*ne1 + i2 + i1*ne1)*nb1, V32, nb1);
+        memcpy((char *) dst->data + (i3*ne2*ne1 + i2 + i1*ne1)*nb1, VKQ32, nb1);
     }
 }
 
@@ -16056,165 +15876,6 @@ static void ggml_compute_forward_flash_attn_ext(
     }
 }
 
-// ggml_compute_forward_flash_ff
-
-static void ggml_compute_forward_flash_ff_f16(
-        const struct ggml_compute_params * params,
-        struct ggml_tensor * dst) {
-
-    const struct ggml_tensor * a = dst->src[0];  // F16
-    const struct ggml_tensor * b0 = dst->src[1]; // F16 fc_w
-    const struct ggml_tensor * b1 = dst->src[2]; // F32 fc_b
-    const struct ggml_tensor * c0 = dst->src[3]; // F16 proj_w
-    const struct ggml_tensor * c1 = dst->src[4]; // F32 proj_b
-
-    int64_t t0 = ggml_perf_time_us();
-    UNUSED(t0);
-
-    GGML_TENSOR_LOCALS(int64_t, nea,  a,   ne)
-    GGML_TENSOR_LOCALS(size_t,  nba,  a,   nb)
-    GGML_TENSOR_LOCALS(int64_t, neb0, b0,  ne)
-    GGML_TENSOR_LOCALS(size_t,  nbb0, b0,  nb)
-    GGML_TENSOR_LOCALS(int64_t, neb1, b1,  ne)
-    GGML_TENSOR_LOCALS(size_t,  nbb1, b1,  nb)
-    GGML_TENSOR_LOCALS(int64_t, nec0, c0,  ne)
-    GGML_TENSOR_LOCALS(size_t,  nbc0, c0,  nb)
-    GGML_TENSOR_LOCALS(int64_t, nec1, c1,  ne)
-    GGML_TENSOR_LOCALS(size_t,  nbc1, c1,  nb)
-    GGML_TENSOR_LOCALS(int64_t, ne,   dst, ne)
-    GGML_TENSOR_LOCALS(size_t,  nb,   dst, nb)
-
-    const int ith = params->ith;
-    const int nth = params->nth;
-
-    const int64_t D = nea0;
-    //const int64_t N = nea1;
-    const int64_t M = neb01;
-
-    GGML_ASSERT(ne0 == nea0);
-    GGML_ASSERT(ne1 == nea1);
-    GGML_ASSERT(ne2 == nea2);
-
-    GGML_ASSERT(nba0  == sizeof(ggml_fp16_t));
-    GGML_ASSERT(nbb00 == sizeof(ggml_fp16_t));
-    GGML_ASSERT(nbb10 == sizeof(float));
-    GGML_ASSERT(nbc00 == sizeof(ggml_fp16_t));
-    GGML_ASSERT(nbc10 == sizeof(float));
-
-    GGML_ASSERT(neb00 == D);
-    GGML_ASSERT(neb01 == M);
-    GGML_ASSERT(neb10 == M);
-    GGML_ASSERT(neb11 == 1);
-
-    GGML_ASSERT(nec00 == M);
-    GGML_ASSERT(nec01 == D);
-    GGML_ASSERT(nec10 == D);
-    GGML_ASSERT(nec11 == 1);
-
-    // dst cannot be transposed or permuted
-    GGML_ASSERT(nb0 == sizeof(float));
-    GGML_ASSERT(nb0 <= nb1);
-    GGML_ASSERT(nb1 <= nb2);
-    GGML_ASSERT(nb2 <= nb3);
-
-    if (params->type == GGML_TASK_TYPE_INIT) {
-        return;
-    }
-
-    if (params->type == GGML_TASK_TYPE_FINALIZE) {
-        return;
-    }
-
-    // parallelize by a rows using ggml_vec_dot_f32
-
-    // total rows in a
-    const int nr = nea1*nea2*nea3;
-
-    // rows per thread
-    const int dr = (nr + nth - 1)/nth;
-
-    // row range for this thread
-    const int ir0 = dr*ith;
-    const int ir1 = MIN(ir0 + dr, nr);
-
-    for (int ir = ir0; ir < ir1; ++ir) {
-        // a indices
-        const int ia3 = ir/(nea2*nea1);
-        const int ia2 = (ir - ia3*nea2*nea1)/nea1;
-        const int ia1 = (ir - ia3*nea2*nea1 - ia2*nea1);
-
-        float * S = (float *) params->wdata + ith*(2*M + CACHE_LINE_SIZE_F32);
-
-        for (int64_t ic = 0; ic < neb01; ++ic) {
-            // b0 indices
-            const int ib03 = ia3;
-            const int ib02 = ia2;
-            const int ib01 = ic;
-
-            // S indices
-            const int i1 = ib01;
-
-            ggml_vec_dot_f16(nea0,
-                    S + i1, 0,
-                    (ggml_fp16_t *) ((char *) b0->data + (ib01*nbb01 + ib02*nbb02 + ib03*nbb03)), 0,
-                    (ggml_fp16_t *) ((char *)  a->data + ( ia1*nba1  +  ia2*nba2  +  ia3*nba3)), 0, 1);
-        }
-
-        ggml_vec_add_f32(neb01, S, S, (float *) b1->data);
-        //ggml_vec_gelu_f32(neb01, S, S);
-
-        ggml_fp16_t * S16 = (ggml_fp16_t *) ((float *) params->wdata + ith*(2*M + CACHE_LINE_SIZE_F32) + M);
-
-        for (int64_t i = 0; i < M; i++) {
-            S16[i] = GGML_FP32_TO_FP16(S[i]);
-        }
-
-        ggml_vec_gelu_f16(neb01, S16, S16);
-
-        {
-            // dst indices
-            const int i1 = ia1;
-            const int i2 = ia2;
-            const int i3 = ia3;
-
-            for (int64_t ic = 0; ic < nec01; ++ic) {
-
-                ggml_vec_dot_f16(neb01,
-                        (float *)       ((char *) dst->data + (ic*nb0 + i1*nb1   + i2*nb2   + i3*nb3)), 0,
-                        (ggml_fp16_t *) ((char *) c0->data  + (         ic*nbc01 + i2*nbc02 + i3*nbc03)), 0,
-                        S16, 0, 1);
-            }
-
-            ggml_vec_add_f32(nec01,
-                    (float *) ((char *) dst->data + (i1*nb1 + i2*nb2 + i3*nb3)),
-                    (float *) ((char *) dst->data + (i1*nb1 + i2*nb2 + i3*nb3)),
-                    (float *) c1->data);
-        }
-    }
-}
-
-static void ggml_compute_forward_flash_ff(
-        const struct ggml_compute_params * params,
-        struct ggml_tensor * dst) {
-
-    const struct ggml_tensor * b0 = dst->src[1];
-
-    switch (b0->type) {
-        case GGML_TYPE_F16:
-            {
-                ggml_compute_forward_flash_ff_f16(params, dst);
-            } break;
-        case GGML_TYPE_F32:
-            {
-                GGML_ASSERT(false); // TODO
-            } break;
-        default:
-            {
-                GGML_ASSERT(false);
-            } break;
-    }
-}
-
 // ggml_compute_forward_flash_attn_back
 
 static void ggml_compute_forward_flash_attn_back_f32(
@@ -17785,21 +17446,10 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm
             {
                 ggml_compute_forward_leaky_relu(params, tensor);
             } break;
-        case GGML_OP_FLASH_ATTN:
-            {
-                const int32_t t = ggml_get_op_params_i32(tensor, 0);
-                GGML_ASSERT(t == 0 || t == 1);
-                const bool masked = t != 0;
-                ggml_compute_forward_flash_attn(params, masked, tensor);
-            } break;
         case GGML_OP_FLASH_ATTN_EXT:
             {
                 ggml_compute_forward_flash_attn_ext(params, tensor->src[0], tensor->src[1], tensor->src[2], tensor->src[3], tensor);
             } break;
-        case GGML_OP_FLASH_FF:
-            {
-                ggml_compute_forward_flash_ff(params, tensor);
-            } break;
         case GGML_OP_FLASH_ATTN_BACK:
             {
                 int32_t t = ggml_get_op_params_i32(tensor, 0);
@@ -18169,6 +17819,7 @@ static struct ggml_tensor * ggml_sub_or_set(struct ggml_context * ctx, struct gg
 static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor * tensor, struct ggml_hash_set zero_table) {
     struct ggml_tensor * src0 = tensor->src[0];
     struct ggml_tensor * src1 = tensor->src[1];
+    struct ggml_tensor * src2 = tensor->src[2];
 
     switch (tensor->op) {
         case GGML_OP_DUP:
@@ -18700,6 +18351,7 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
                             ggml_rope_back(ctx,
                                 tensor->grad,
                                 src1,
+                                src2,
                                 n_dims,
                                 mode,
                                 n_ctx,
@@ -18739,6 +18391,7 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
                             ggml_rope_impl(ctx,
                                 tensor->grad,
                                 src1,
+                                src2,
                                 n_dims,
                                 mode,
                                 n_ctx,
@@ -18803,7 +18456,6 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
             {
                 GGML_ASSERT(false); // TODO: not implemented
             } break;
-        case GGML_OP_FLASH_ATTN:
         case GGML_OP_FLASH_ATTN_EXT:
             {
                 struct ggml_tensor * flash_grad = NULL;
@@ -18820,7 +18472,6 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
                             masked);
                 }
 
-                struct ggml_tensor * src2 = tensor->src[2];
                 const int64_t elem_q = ggml_nelements(src0);
                 const int64_t elem_k = ggml_nelements(src1);
                 const int64_t elem_v = ggml_nelements(src2);
@@ -18858,10 +18509,6 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
                             zero_table);
                 }
             } break;
-        case GGML_OP_FLASH_FF:
-            {
-                GGML_ASSERT(false); // not supported
-            } break;
         case GGML_OP_FLASH_ATTN_BACK:
             {
                 GGML_ASSERT(false); // not supported
@@ -19548,15 +19195,10 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads, int n_cur_
             {
                 n_tasks = n_threads;
             } break;
-        case GGML_OP_FLASH_ATTN:
         case GGML_OP_FLASH_ATTN_EXT:
             {
                 n_tasks = n_threads;
             } break;
-        case GGML_OP_FLASH_FF:
-            {
-                n_tasks = n_threads;
-            } break;
         case GGML_OP_FLASH_ATTN_BACK:
             {
                 n_tasks = n_threads;
@@ -19953,39 +19595,11 @@ struct ggml_cplan ggml_graph_plan(const struct ggml_cgraph * cgraph, int n_threa
                     cur += sizeof(ggml_fp16_t)*ne00*ne01*ne02*ne03;
                     cur += sizeof(ggml_fp16_t)*ne10*ne11*ne12;
                 } break;
-            case GGML_OP_FLASH_ATTN:
-                {
-                    const int64_t ne11 = ggml_up(node->src[1]->ne[1], GGML_SOFT_MAX_UNROLL);
-
-                    if (node->src[1]->type == GGML_TYPE_F32) {
-                        cur  = sizeof(float)*ne11*n_tasks; // TODO: this can become (n_tasks-1)
-                        cur += sizeof(float)*ne11*n_tasks; // this is overestimated by x2
-                    } else if (node->src[1]->type == GGML_TYPE_F16) {
-                        cur  = sizeof(float)*ne11*n_tasks; // TODO: this can become (n_tasks-1)
-                        cur += sizeof(float)*ne11*n_tasks; // this is overestimated by x2
-                    } else if (node->src[1]->type == GGML_TYPE_BF16) {
-                        cur  = sizeof(float)*ne11*n_tasks; // TODO: this can become (n_tasks-1)
-                        cur += sizeof(float)*ne11*n_tasks; // this is overestimated by x2
-                    }
-                } break;
             case GGML_OP_FLASH_ATTN_EXT:
                 {
                     const int64_t ne00 = node->src[0]->ne[0]; // D
 
-                    cur = 2*sizeof(float)*ne00*n_tasks; // 2x head size
-                } break;
-            case GGML_OP_FLASH_FF:
-                {
-                    if (node->src[1]->type == GGML_TYPE_F32) {
-                        cur  = sizeof(float)*node->src[1]->ne[1]*n_tasks; // TODO: this can become (n_tasks-1)
-                        cur += sizeof(float)*node->src[1]->ne[1]*n_tasks; // this is overestimated by x2
-                    } else if (node->src[1]->type == GGML_TYPE_F16) {
-                        cur  = sizeof(float)*node->src[1]->ne[1]*n_tasks; // TODO: this can become (n_tasks-1)
-                        cur += sizeof(float)*node->src[1]->ne[1]*n_tasks; // this is overestimated by x2
-                    } else if (node->src[1]->type == GGML_TYPE_BF16) {
-                        cur  = sizeof(float)*node->src[1]->ne[1]*n_tasks; // TODO: this can become (n_tasks-1)
-                        cur += sizeof(float)*node->src[1]->ne[1]*n_tasks; // this is overestimated by x2
-                    }
+                    cur = 3*sizeof(float)*ne00*n_tasks; // 3x head size/thread
                 } break;
             case GGML_OP_FLASH_ATTN_BACK:
                 {
@@ -21827,11 +21441,7 @@ size_t ggml_quantize_chunk(
         case GGML_TYPE_IQ1_S:   result = quantize_iq1_s  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ1_M:   result = quantize_iq1_m  (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
         case GGML_TYPE_IQ4_NL:  result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
-#if QK_K == 64
-        case GGML_TYPE_IQ4_XS:  result = quantize_iq4_nl (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
-#else
         case GGML_TYPE_IQ4_XS:  result = quantize_iq4_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break;
-#endif
         case GGML_TYPE_F16:
             {
                 size_t elemsize = sizeof(ggml_fp16_t);
@@ -23108,6 +22718,14 @@ int ggml_cpu_has_avx512_vnni(void) {
 #endif
 }
 
+int ggml_cpu_has_avx512_bf16(void) {
+#if defined(__AVX512BF16__)
+    return 1;
+#else
+    return 0;
+#endif
+}
+
 int ggml_cpu_has_fma(void) {
 #if defined(__FMA__)
     return 1;
diff --git a/ggml.h b/ggml.h
index 8c13f4ba8..be81e0c52 100644
--- a/ggml.h
+++ b/ggml.h
@@ -481,9 +481,7 @@ extern "C" {
         GGML_OP_ARGSORT,
         GGML_OP_LEAKY_RELU,
 
-        GGML_OP_FLASH_ATTN,
         GGML_OP_FLASH_ATTN_EXT,
-        GGML_OP_FLASH_FF,
         GGML_OP_FLASH_ATTN_BACK,
         GGML_OP_SSM_CONV,
         GGML_OP_SSM_SCAN,
@@ -1460,11 +1458,12 @@ extern "C" {
             struct ggml_tensor  * b);
 
     // rotary position embedding
-    // if mode & 1 == 1, skip n_past elements (DEPRECATED)
+    // if mode & 1 == 1, skip n_past elements (NOT SUPPORTED)
     // if mode & 2 == 1, GPT-NeoX style
     // if mode & 4 == 1, ChatGLM style
     //
     // b is an int32 vector with size a->ne[2], it contains the positions
+    // c is freq factors (e.g. phi3-128k), (optional)
     GGML_API struct ggml_tensor * ggml_rope(
             struct ggml_context * ctx,
             struct ggml_tensor  * a,
@@ -1483,10 +1482,11 @@ extern "C" {
             int                   n_ctx);
 
     // custom RoPE
-    GGML_API struct ggml_tensor * ggml_rope_custom(
+    GGML_API struct ggml_tensor * ggml_rope_ext(
             struct ggml_context * ctx,
             struct ggml_tensor  * a,
             struct ggml_tensor  * b,
+            struct ggml_tensor  * c,
             int                   n_dims,
             int                   mode,
             int                   n_ctx,
@@ -1499,7 +1499,23 @@ extern "C" {
             float                 beta_slow);
 
     // in-place, returns view(a)
-    GGML_API struct ggml_tensor * ggml_rope_custom_inplace(
+    GGML_API struct ggml_tensor * ggml_rope_ext_inplace(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * a,
+            struct ggml_tensor  * b,
+            struct ggml_tensor  * c,
+            int                   n_dims,
+            int                   mode,
+            int                   n_ctx,
+            int                   n_orig_ctx,
+            float                 freq_base,
+            float                 freq_scale,
+            float                 ext_factor,
+            float                 attn_factor,
+            float                 beta_fast,
+            float                 beta_slow);
+
+    GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_rope_custom(
             struct ggml_context * ctx,
             struct ggml_tensor  * a,
             struct ggml_tensor  * b,
@@ -1512,20 +1528,28 @@ extern "C" {
             float                 ext_factor,
             float                 attn_factor,
             float                 beta_fast,
-            float                 beta_slow);
+            float                 beta_slow),
+        "use ggml_rope_ext instead");
 
-    // compute correction dims for YaRN RoPE scaling
-    GGML_CALL void ggml_rope_yarn_corr_dims(
-        int n_dims, int n_orig_ctx, float freq_base, float beta_fast, float beta_slow, float dims[2]);
-
-    // xPos RoPE, in-place, returns view(a)
-    GGML_API struct ggml_tensor * ggml_rope_xpos_inplace(
+    GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_rope_custom_inplace(
             struct ggml_context * ctx,
             struct ggml_tensor  * a,
             struct ggml_tensor  * b,
             int                   n_dims,
-            float                 base,
-            bool                  down);
+            int                   mode,
+            int                   n_ctx,
+            int                   n_orig_ctx,
+            float                 freq_base,
+            float                 freq_scale,
+            float                 ext_factor,
+            float                 attn_factor,
+            float                 beta_fast,
+            float                 beta_slow),
+        "use ggml_rope_ext_inplace instead");
+
+    // compute correction dims for YaRN RoPE scaling
+    GGML_CALL void ggml_rope_yarn_corr_dims(
+        int n_dims, int n_orig_ctx, float freq_base, float beta_fast, float beta_slow, float dims[2]);
 
     // rotary position embedding backward, i.e compute dx from dy
     // a - dy
@@ -1533,6 +1557,7 @@ extern "C" {
             struct ggml_context * ctx,
             struct ggml_tensor  * a,
             struct ggml_tensor  * b,
+            struct ggml_tensor  * c,
             int                   n_dims,
             int                   mode,
             int                   n_ctx,
@@ -1734,13 +1759,6 @@ extern "C" {
             struct ggml_tensor  * a,
             int                   k);
 
-    GGML_API struct ggml_tensor * ggml_flash_attn(
-            struct ggml_context * ctx,
-            struct ggml_tensor  * q,
-            struct ggml_tensor  * k,
-            struct ggml_tensor  * v,
-            bool                  masked);
-
 #define GGML_KQ_MASK_PAD 32
 
     // q:    [n_embd, n_batch,     n_head,    1]
@@ -1761,6 +1779,7 @@ extern "C" {
             struct ggml_tensor * a,
             enum ggml_prec       prec);
 
+    // TODO: needs to be adapted to ggml_flash_attn_ext
     GGML_API struct ggml_tensor * ggml_flash_attn_back(
            struct ggml_context * ctx,
            struct ggml_tensor  * q,
@@ -1769,14 +1788,6 @@ extern "C" {
            struct ggml_tensor  * d,
            bool                  masked);
 
-    GGML_API struct ggml_tensor * ggml_flash_ff(
-            struct ggml_context * ctx,
-            struct ggml_tensor  * a,
-            struct ggml_tensor  * b0,
-            struct ggml_tensor  * b1,
-            struct ggml_tensor  * c0,
-            struct ggml_tensor  * c1);
-
     GGML_API struct ggml_tensor * ggml_ssm_conv(
             struct ggml_context * ctx,
             struct ggml_tensor  * s,
@@ -2390,6 +2401,7 @@ extern "C" {
     GGML_API int ggml_cpu_has_avx512     (void);
     GGML_API int ggml_cpu_has_avx512_vbmi(void);
     GGML_API int ggml_cpu_has_avx512_vnni(void);
+    GGML_API int ggml_cpu_has_avx512_bf16(void);
     GGML_API int ggml_cpu_has_fma        (void);
     GGML_API int ggml_cpu_has_neon       (void);
     GGML_API int ggml_cpu_has_arm_fma    (void);
diff --git a/ggml_vk_generate_shaders.py b/ggml_vk_generate_shaders.py
index 162cf5c6e..a8f7373df 100644
--- a/ggml_vk_generate_shaders.py
+++ b/ggml_vk_generate_shaders.py
@@ -2432,7 +2432,6 @@ layout (push_constant) uniform parameter
 {
     uint KX;
     uint KY;
-    uint KZ;
     float scale;
     float max_bias;
     float m0;
@@ -2449,8 +2448,7 @@ layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
 
 layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
 layout (binding = 1) readonly buffer Y {B_TYPE data_b[];};
-layout (binding = 2) readonly buffer Z {C_TYPE data_c[];};
-layout (binding = 3) buffer D {D_TYPE data_d[];};
+layout (binding = 2) buffer D {D_TYPE data_d[];};
 
 shared FLOAT_TYPE vals[BLOCK_SIZE];
 
@@ -2459,7 +2457,7 @@ void main() {
     const uint rowx = gl_WorkGroupID.x;
     const uint rowy = rowx % p.KY;
 
-    float slope = 0.0f;
+    float slope = 1.0f;
 
     // ALiBi
     if (p.max_bias > 0.0f) {
@@ -2472,11 +2470,18 @@ void main() {
     }
 
     // Find max
-    vals[tid] = uintBitsToFloat(0xFF800000);
+    FLOAT_TYPE max_val = uintBitsToFloat(0xFF800000);
 
-    [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
-        vals[tid] = max(vals[tid], FLOAT_TYPE(data_a[rowx * p.KX + col]) * p.scale + (p.KY > 0 ? FLOAT_TYPE(data_b[rowy * p.KX + col]) : FLOAT_TYPE(0.0f)) + (p.KZ > 0 ? slope * FLOAT_TYPE(data_c[col]) : 0.0f));
+    [[unroll]] for (uint col0 = 0; col0 < p.KX; col0 += BLOCK_SIZE) {
+        const uint col = col0 + tid;
+
+        if (col >= p.KX) {
+            break;
+        }
+
+        max_val = max(max_val, FLOAT_TYPE(data_a[rowx * p.KX + col]) * p.scale + (p.KY > 0 ? slope * FLOAT_TYPE(data_b[rowy * p.KX + col]) : FLOAT_TYPE(0.0f)));
     }
+    vals[tid] = max_val;
 
     barrier();
     [[unroll]] for (int s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
@@ -2486,15 +2491,21 @@ void main() {
         barrier();
     }
 
-    const FLOAT_TYPE max_val = vals[0];
+    max_val = vals[0];
     barrier();
 
     // Sum up values
     vals[tid] = FLOAT_TYPE(0.0f);
 
-    [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
+    [[unroll]] for (uint col0 = 0; col0 < p.KX; col0 += BLOCK_SIZE) {
+        const uint col = col0 + tid;
+
+        if (col >= p.KX) {
+            break;
+        }
+
         const uint i = rowx * p.KX + col;
-        const FLOAT_TYPE val = exp(FLOAT_TYPE(data_a[i]) * p.scale + (p.KY > 0 ? FLOAT_TYPE(data_b[rowy * p.KX + col]) : FLOAT_TYPE(0.0f)) - max_val);
+        const FLOAT_TYPE val = exp(FLOAT_TYPE(data_a[i]) * p.scale + (p.KY > 0 ? slope * FLOAT_TYPE(data_b[rowy * p.KX + col]) : FLOAT_TYPE(0.0f)) - max_val);
         vals[tid] += val;
         data_d[i] = D_TYPE(val);
     }
@@ -2509,7 +2520,13 @@ void main() {
 
     const D_TYPE divisor = D_TYPE(vals[0]);
 
-    [[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
+    [[unroll]] for (uint col0 = 0; col0 < p.KX; col0 += BLOCK_SIZE) {
+        const uint col = col0 + tid;
+
+        if (col >= p.KX) {
+            break;
+        }
+
         data_d[rowx*p.KX + col] /= divisor;
     }
 }
@@ -2592,7 +2609,8 @@ layout(local_size_x = 1, local_size_y = 256, local_size_z = 1) in;
 
 layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
 layout (binding = 1) readonly buffer Y {int data_b[];};
-layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};
+layout (binding = 2) readonly buffer Z {float data_freq_factors[];};
+layout (binding = 3) writeonly buffer D {D_TYPE data_d[];};
 
 layout (push_constant) uniform parameter {
     uint ncols;
@@ -2605,6 +2623,7 @@ layout (push_constant) uniform parameter {
     float corr_dims[4];
     float theta_scale;
     float inv_ndims;
+    uint has_freq_facs;
 } p;
 
 float rope_yarn_ramp(const float low, const float high, const uint i0) {
@@ -2654,7 +2673,8 @@ void main() {
     const float cur_rot = p.inv_ndims * ic - ib;
 
     const int pos = data_b[i2];
-    const float theta_base = pos*p.freq_scale*pow(p.theta_scale, col/2.0f);
+    const float freq_factor = p.has_freq_facs != 0 ? data_freq_factors[ic/2] : 1.0f;
+    const float theta_base = pos*p.freq_scale*pow(p.theta_scale, col/2.0f) / freq_factor;
 
     float cos_theta, sin_theta;
     rope_yarn(theta_base, uint(cur_rot), cos_theta, sin_theta);
@@ -2672,20 +2692,26 @@ argsort_src = """
 
 #extension GL_EXT_shader_16bit_storage : require
 
-layout(local_size_x = 1024, local_size_y = 1, local_size_z = 1) in;
+#define BLOCK_SIZE 1024
+#define ASC 0
+
+layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
 
 layout (binding = 0) readonly buffer A {A_TYPE data_a[];};
 layout (binding = 1)          buffer D {int data_d[];};
 
 layout (push_constant) uniform parameter {
     uint ncols;
-    bool ascending;
+    uint ncols_pad;
+    uint order;
 } p;
 
+shared int dst_row[BLOCK_SIZE];
+
 void swap(uint idx0, uint idx1) {
-    int tmp = data_d[idx0];
-    data_d[idx0] = data_d[idx1];
-    data_d[idx1] = tmp;
+    int tmp = dst_row[idx0];
+    dst_row[idx0] = dst_row[idx1];
+    dst_row[idx1] = tmp;
 }
 
 void main() {
@@ -2693,36 +2719,45 @@ void main() {
     const int col = int(gl_LocalInvocationID.x);
     const uint row = gl_WorkGroupID.y;
 
-    if (col >= p.ncols) {
+    if (col >= p.ncols_pad) {
         return;
     }
 
-    const uint a_idx = row * p.ncols;
-    const uint d_idx = row * p.ncols;
+    const uint row_offset = row * p.ncols;
 
     // initialize indices
-    if (col < p.ncols) {
-        data_d[col] = col;
-    }
+    dst_row[col] = col;
     barrier();
 
-    for (uint k = 2; k <= p.ncols; k *= 2) {
+    for (uint k = 2; k <= p.ncols_pad; k *= 2) {
         for (uint j = k / 2; j > 0; j /= 2) {
             const uint ixj = col ^ j;
             if (ixj > col) {
                 if ((col & k) == 0) {
-                    if (p.ascending ? data_a[a_idx + data_d[d_idx + col]] > data_a[a_idx + data_d[d_idx + ixj]] : data_a[a_idx + data_d[d_idx + col]] < data_a[a_idx + data_d[d_idx + ixj]]) {
-                        swap(d_idx + col, d_idx + ixj);
+                    if (dst_row[col] >= p.ncols ||
+                        (dst_row[ixj] < p.ncols && (p.order == ASC ?
+                            data_a[row_offset + dst_row[col]] > data_a[row_offset + dst_row[ixj]] :
+                            data_a[row_offset + dst_row[col]] < data_a[row_offset + dst_row[ixj]]))
+                    ) {
+                        swap(col, ixj);
                     }
                 } else {
-                    if (p.ascending ? data_a[a_idx + data_d[d_idx + col]] < data_a[a_idx + data_d[d_idx + ixj]] : data_a[a_idx + data_d[d_idx + col]] > data_a[a_idx + data_d[d_idx + ixj]]) {
-                        swap(d_idx + col, d_idx + ixj);
+                    if (dst_row[ixj] >= p.ncols ||
+                        (dst_row[col] < p.ncols && (p.order == ASC ?
+                            data_a[row_offset + dst_row[col]] < data_a[row_offset + dst_row[ixj]] :
+                            data_a[row_offset + dst_row[col]] > data_a[row_offset + dst_row[ixj]]))
+                    ) {
+                        swap(col, ixj);
                     }
                 }
             }
             barrier();
         }
     }
+
+    if (col < p.ncols) {
+        data_d[row_offset + col] = dst_row[col];
+    }
 }
 """
 
@@ -2845,13 +2880,16 @@ async def main():
         stream.clear()
         stream.extend((mulmat_head, shader_float_type, mulmat_body1, mulmat_load_scalar, mulmat_body2))
         tasks.append(string_to_spv("matmul_f32", "".join(stream), {"A_TYPE": "float", "B_TYPE": "float", "D_TYPE": "float"}, fp16))
-        tasks.append(string_to_spv("matmul_f32_aligned", "".join(stream), {"LOAD_VEC_A": 1, "LOAD_VEC_B": load_vec, "A_TYPE": "float", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16))
+        tasks.append(string_to_spv("matmul_f32_aligned", "".join(stream), {"LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type, "B_TYPE": vec_type, "D_TYPE": "float"}, fp16))
+
+        tasks.append(string_to_spv("matmul_f32_f16", "".join(stream), {"A_TYPE": "float", "B_TYPE": "float16_t", "D_TYPE": "float"}, fp16))
+        tasks.append(string_to_spv("matmul_f32_f16_aligned", "".join(stream), {"LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type, "B_TYPE": vec_type_f16, "D_TYPE": "float"}, fp16))
 
         tasks.append(string_to_spv("matmul_f16", "".join(stream), {"A_TYPE": "float16_t", "B_TYPE": "float16_t", "D_TYPE": "float"}, fp16))
-        tasks.append(string_to_spv("matmul_f16_aligned", "".join(stream), {"LOAD_VEC_A": 1, "LOAD_VEC_B": load_vec, "A_TYPE": "float16_t", "B_TYPE": vec_type_f16, "D_TYPE": "float"}, fp16))
+        tasks.append(string_to_spv("matmul_f16_aligned", "".join(stream), {"LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type_f16, "B_TYPE": vec_type_f16, "D_TYPE": "float"}, fp16))
 
         tasks.append(string_to_spv("matmul_f16_f32", "".join(stream), {"A_TYPE": "float16_t", "B_TYPE": "float", "D_TYPE": "float"}, fp16))
-        tasks.append(string_to_spv("matmul_f16_f32_aligned", "".join(stream), {"LOAD_VEC_A": 1, "LOAD_VEC_B": load_vec, "A_TYPE": "float16_t", "B_TYPE": vec_type, "D_TYPE": "float"}, fp16))
+        tasks.append(string_to_spv("matmul_f16_f32_aligned", "".join(stream), {"LOAD_VEC_A": load_vec, "LOAD_VEC_B": load_vec, "A_TYPE": vec_type_f16, "B_TYPE": vec_type, "D_TYPE": "float"}, fp16))
 
         stream.clear()
         stream.extend((mulmat_head, shader_int8_ext, shader_float_type, shader_q4_0_defines, mulmat_body1, mulmat_load_q4_0, mulmat_body2))
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index 1a579dc80..9ed7fdf92 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -63,13 +63,13 @@ class Keys:
         KV_LORA_RANK      = "{arch}.attention.kv_lora_rank"
 
     class Rope:
-        DIMENSION_COUNT      = "{arch}.rope.dimension_count"
-        FREQ_BASE            = "{arch}.rope.freq_base"
-        SCALING_TYPE         = "{arch}.rope.scaling.type"
-        SCALING_FACTOR       = "{arch}.rope.scaling.factor"
-        SCALING_ORIG_CTX_LEN = "{arch}.rope.scaling.original_context_length"
-        SCALING_FINETUNED    = "{arch}.rope.scaling.finetuned"
-        SCALING_YARN_LOG_MUL = "{arch}.rope.scaling.yarn_log_multiplier"
+        DIMENSION_COUNT         = "{arch}.rope.dimension_count"
+        FREQ_BASE               = "{arch}.rope.freq_base"
+        SCALING_TYPE            = "{arch}.rope.scaling.type"
+        SCALING_FACTOR          = "{arch}.rope.scaling.factor"
+        SCALING_ATTN_FACTOR     = "{arch}.rope.scaling.attn_factor"
+        SCALING_ORIG_CTX_LEN    = "{arch}.rope.scaling.original_context_length"
+        SCALING_FINETUNED       = "{arch}.rope.scaling.finetuned"
 
     class SSM:
         CONV_KERNEL    = "{arch}.ssm.conv_kernel"
@@ -122,7 +122,6 @@ class MODEL_ARCH(IntEnum):
     GPTNEOX    = auto()
     MPT        = auto()
     STARCODER  = auto()
-    PERSIMMON  = auto()
     REFACT     = auto()
     BERT       = auto()
     NOMIC_BERT = auto()
@@ -146,6 +145,7 @@ class MODEL_ARCH(IntEnum):
     COMMAND_R  = auto()
     DBRX       = auto()
     OLMO       = auto()
+    ARCTIC     = auto()
     DEEPSEEK2  = auto()
 
 
@@ -157,6 +157,8 @@ class MODEL_TENSOR(IntEnum):
     OUTPUT             = auto()
     OUTPUT_NORM        = auto()
     ROPE_FREQS         = auto()
+    ROPE_FACTORS_LONG  = auto()
+    ROPE_FACTORS_SHORT = auto()
     ATTN_Q             = auto()
     ATTN_K             = auto()
     ATTN_V             = auto()
@@ -173,6 +175,7 @@ class MODEL_TENSOR(IntEnum):
     FFN_DOWN           = auto()
     FFN_UP             = auto()
     FFN_ACT            = auto()
+    FFN_NORM_EXP       = auto()
     FFN_GATE_EXP       = auto()
     FFN_DOWN_EXP       = auto()
     FFN_UP_EXP         = auto()
@@ -207,7 +210,6 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
     MODEL_ARCH.GPTNEOX:        "gptneox",
     MODEL_ARCH.MPT:            "mpt",
     MODEL_ARCH.STARCODER:      "starcoder",
-    MODEL_ARCH.PERSIMMON:      "persimmon",
     MODEL_ARCH.REFACT:         "refact",
     MODEL_ARCH.BERT:           "bert",
     MODEL_ARCH.NOMIC_BERT:     "nomic-bert",
@@ -231,6 +233,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
     MODEL_ARCH.COMMAND_R:      "command-r",
     MODEL_ARCH.DBRX:           "dbrx",
     MODEL_ARCH.OLMO:           "olmo",
+    MODEL_ARCH.ARCTIC:         "arctic",
     MODEL_ARCH.DEEPSEEK2:      "deepseek2",
 }
 
@@ -242,6 +245,8 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
     MODEL_TENSOR.OUTPUT_NORM:        "output_norm",
     MODEL_TENSOR.OUTPUT:             "output",
     MODEL_TENSOR.ROPE_FREQS:         "rope_freqs",
+    MODEL_TENSOR.ROPE_FACTORS_LONG:  "rope_factors_long",
+    MODEL_TENSOR.ROPE_FACTORS_SHORT: "rope_factors_short",
     MODEL_TENSOR.ATTN_NORM:          "blk.{bid}.attn_norm",
     MODEL_TENSOR.ATTN_NORM_2:        "blk.{bid}.attn_norm_2",
     MODEL_TENSOR.ATTN_QKV:           "blk.{bid}.attn_qkv",
@@ -263,6 +268,7 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
     MODEL_TENSOR.FFN_DOWN_SHEXP:     "blk.{bid}.ffn_down_shexp",
     MODEL_TENSOR.FFN_UP_SHEXP:       "blk.{bid}.ffn_up_shexp",
     MODEL_TENSOR.FFN_ACT:            "blk.{bid}.ffn",
+    MODEL_TENSOR.FFN_NORM_EXP:       "blk.{bid}.ffn_norm_exps",
     MODEL_TENSOR.FFN_GATE_EXP:       "blk.{bid}.ffn_gate_exps",
     MODEL_TENSOR.FFN_DOWN_EXP:       "blk.{bid}.ffn_down_exps",
     MODEL_TENSOR.FFN_UP_EXP:         "blk.{bid}.ffn_up_exps",
@@ -447,20 +453,6 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
         MODEL_TENSOR.FFN_DOWN,
         MODEL_TENSOR.FFN_UP,
     ],
-    MODEL_ARCH.PERSIMMON: [
-        MODEL_TENSOR.TOKEN_EMBD,
-        MODEL_TENSOR.OUTPUT,
-        MODEL_TENSOR.OUTPUT_NORM,
-        MODEL_TENSOR.ATTN_NORM,
-        MODEL_TENSOR.ATTN_QKV,
-        MODEL_TENSOR.ATTN_OUT,
-        MODEL_TENSOR.FFN_NORM,
-        MODEL_TENSOR.FFN_DOWN,
-        MODEL_TENSOR.FFN_UP,
-        MODEL_TENSOR.ATTN_Q_NORM,
-        MODEL_TENSOR.ATTN_K_NORM,
-        MODEL_TENSOR.ATTN_ROT_EMBD,
-    ],
     MODEL_ARCH.REFACT: [
         MODEL_TENSOR.TOKEN_EMBD,
         MODEL_TENSOR.OUTPUT_NORM,
@@ -764,6 +756,27 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
         MODEL_TENSOR.FFN_DOWN,
         MODEL_TENSOR.FFN_UP,
     ],
+    MODEL_ARCH.ARCTIC: [
+        MODEL_TENSOR.TOKEN_EMBD,
+        MODEL_TENSOR.OUTPUT_NORM,
+        MODEL_TENSOR.OUTPUT,
+        MODEL_TENSOR.ROPE_FREQS,
+        MODEL_TENSOR.ATTN_NORM,
+        MODEL_TENSOR.ATTN_Q,
+        MODEL_TENSOR.ATTN_K,
+        MODEL_TENSOR.ATTN_V,
+        MODEL_TENSOR.ATTN_OUT,
+        MODEL_TENSOR.ATTN_ROT_EMBD,
+        MODEL_TENSOR.FFN_GATE_INP,
+        MODEL_TENSOR.FFN_NORM,
+        MODEL_TENSOR.FFN_GATE,
+        MODEL_TENSOR.FFN_DOWN,
+        MODEL_TENSOR.FFN_UP,
+        MODEL_TENSOR.FFN_NORM_EXP,
+        MODEL_TENSOR.FFN_GATE_EXP,
+        MODEL_TENSOR.FFN_DOWN_EXP,
+        MODEL_TENSOR.FFN_UP_EXP,
+    ],
     MODEL_ARCH.DEEPSEEK2: [
         MODEL_TENSOR.TOKEN_EMBD,
         MODEL_TENSOR.OUTPUT_NORM,
@@ -804,9 +817,6 @@ MODEL_TENSOR_SKIP: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
         MODEL_TENSOR.ROPE_FREQS,
         MODEL_TENSOR.ATTN_ROT_EMBD,
     ],
-    MODEL_ARCH.PERSIMMON: [
-        MODEL_TENSOR.ROPE_FREQS,
-    ],
     MODEL_ARCH.QWEN: [
         MODEL_TENSOR.ROPE_FREQS,
         MODEL_TENSOR.ATTN_ROT_EMBD,
@@ -971,9 +981,8 @@ class GGUFValueType(IntEnum):
             raise ValueError(f"Unknown type: {type(val)}")
 
 
-# Note: Does not support GGML_QKK_64
-QK_K = 256
 # Items here are (block size, type size)
+QK_K = 256
 GGML_QUANT_SIZES: dict[GGMLQuantizationType, tuple[int, int]] = {
     GGMLQuantizationType.F32:     (1, 4),
     GGMLQuantizationType.F16:     (1, 2),
diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py
index c834efd7f..863cba56c 100644
--- a/gguf-py/gguf/gguf_writer.py
+++ b/gguf-py/gguf/gguf_writer.py
@@ -451,6 +451,9 @@ class GGUFWriter:
     def add_rope_scaling_factor(self, value: float) -> None:
         self.add_float32(Keys.Rope.SCALING_FACTOR.format(arch=self.arch), value)
 
+    def add_rope_scaling_attn_factors(self, value: Sequence[float]) -> None:
+        self.add_float32(Keys.Rope.SCALING_ATTN_FACTOR.format(arch=self.arch), value)
+
     def add_rope_scaling_orig_ctx_len(self, value: int) -> None:
         self.add_uint32(Keys.Rope.SCALING_ORIG_CTX_LEN.format(arch=self.arch), value)
 
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 383d8440b..83e3c4c33 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -244,6 +244,7 @@ class TensorNameMap:
             "encoder.layers.{bid}.mlp.fc11",                          # nomic-bert
             "model.layers.{bid}.mlp.c_fc",                            # starcoder2
             "encoder.layer.{bid}.mlp.gated_layers_v",                 # jina-bert-v2
+            "model.layers.{bid}.residual_mlp.w3",                     # arctic
         ),
 
         MODEL_TENSOR.FFN_UP_EXP: (
@@ -273,6 +274,7 @@ class TensorNameMap:
             "encoder.layers.{bid}.mlp.fc12",              # nomic-bert
             "encoder.layer.{bid}.mlp.gated_layers_w",     # jina-bert-v2
             "transformer.h.{bid}.mlp.linear_1",           # refact
+            "model.layers.{bid}.residual_mlp.w1",         # arctic
         ),
 
         MODEL_TENSOR.FFN_GATE_EXP: (
@@ -308,6 +310,7 @@ class TensorNameMap:
             "encoder.layers.{bid}.mlp.fc2",                           # nomic-bert
             "model.layers.{bid}.mlp.c_proj",                          # starcoder2
             "encoder.layer.{bid}.mlp.wo",                             # jina-bert-v2
+            "model.layers.{bid}.residual_mlp.w2",                     # arctic
         ),
 
         MODEL_TENSOR.FFN_DOWN_EXP: (
@@ -409,6 +412,18 @@ class TensorNameMap:
         ),
     }
 
+    # architecture-specific block mappings
+    arch_block_mappings_cfg: dict[MODEL_ARCH, dict[MODEL_TENSOR, tuple[str, ...]]] = {
+        MODEL_ARCH.ARCTIC: {
+            MODEL_TENSOR.FFN_NORM: (
+                "model.layers.{bid}.residual_layernorm",
+            ),
+            MODEL_TENSOR.FFN_NORM_EXP: (
+                "model.layers.{bid}.post_attention_layernorm",
+            ),
+        },
+    }
+
     mapping: dict[str, tuple[MODEL_TENSOR, str]]
 
     def __init__(self, arch: MODEL_ARCH, n_blocks: int):
@@ -420,6 +435,8 @@ class TensorNameMap:
             self.mapping[tensor_name] = (tensor, tensor_name)
             for key in keys:
                 self.mapping[key] = (tensor, tensor_name)
+        if arch in self.arch_block_mappings_cfg:
+            self.block_mappings_cfg.update(self.arch_block_mappings_cfg[arch])
         for bid in range(n_blocks):
             for tensor, keys in self.block_mappings_cfg.items():
                 if tensor not in MODEL_TENSORS[arch]:
diff --git a/llama.cpp b/llama.cpp
index 03bf77fa0..84f884114 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -26,16 +26,9 @@
 #ifdef GGML_USE_METAL
 #  include "ggml-metal.h"
 #endif
-#ifdef GGML_USE_MPI
-#  include "ggml-mpi.h"
-#endif
-#ifndef QK_K
-#  ifdef GGML_QKK_64
-#    define QK_K 64
-#  else
-#    define QK_K 256
-#  endif
-#endif
+
+// TODO: replace with ggml API call
+#define QK_K 256
 
 #ifdef __has_include
     #if __has_include(<unistd.h>)
@@ -205,7 +198,6 @@ enum llm_arch {
     LLM_ARCH_GPTNEOX,
     LLM_ARCH_MPT,
     LLM_ARCH_STARCODER,
-    LLM_ARCH_PERSIMMON,
     LLM_ARCH_REFACT,
     LLM_ARCH_BERT,
     LLM_ARCH_NOMIC_BERT,
@@ -229,6 +221,7 @@ enum llm_arch {
     LLM_ARCH_COMMAND_R,
     LLM_ARCH_DBRX,
     LLM_ARCH_OLMO,
+    LLM_ARCH_ARCTIC,
     LLM_ARCH_DEEPSEEK2,
     LLM_ARCH_UNKNOWN,
 };
@@ -243,7 +236,6 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_MPT,             "mpt"          },
     { LLM_ARCH_BAICHUAN,        "baichuan"     },
     { LLM_ARCH_STARCODER,       "starcoder"    },
-    { LLM_ARCH_PERSIMMON,       "persimmon"    },
     { LLM_ARCH_REFACT,          "refact"       },
     { LLM_ARCH_BERT,            "bert"         },
     { LLM_ARCH_NOMIC_BERT,      "nomic-bert"   },
@@ -267,6 +259,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_COMMAND_R,       "command-r"    },
     { LLM_ARCH_DBRX,            "dbrx"         },
     { LLM_ARCH_OLMO,            "olmo"         },
+    { LLM_ARCH_ARCTIC,          "arctic"       },
     { LLM_ARCH_DEEPSEEK2,       "deepseek2"    },
     { LLM_ARCH_UNKNOWN,         "(unknown)"    },
 };
@@ -317,6 +310,7 @@ enum llm_kv {
     LLM_KV_ROPE_SCALE_LINEAR,
     LLM_KV_ROPE_SCALING_TYPE,
     LLM_KV_ROPE_SCALING_FACTOR,
+    LLM_KV_ROPE_SCALING_ATTN_FACTOR,
     LLM_KV_ROPE_SCALING_ORIG_CTX_LEN,
     LLM_KV_ROPE_SCALING_FINETUNED,
     LLM_KV_ROPE_SCALING_YARN_LOG_MUL,
@@ -401,6 +395,7 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_ROPE_SCALE_LINEAR,             "%s.rope.scale_linear"                    },
     { LLM_KV_ROPE_SCALING_TYPE,             "%s.rope.scaling.type"                    },
     { LLM_KV_ROPE_SCALING_FACTOR,           "%s.rope.scaling.factor"                  },
+    { LLM_KV_ROPE_SCALING_ATTN_FACTOR,      "%s.rope.scaling.attn_factor"             },
     { LLM_KV_ROPE_SCALING_ORIG_CTX_LEN,     "%s.rope.scaling.original_context_length" },
     { LLM_KV_ROPE_SCALING_FINETUNED,        "%s.rope.scaling.finetuned"               },
     { LLM_KV_ROPE_SCALING_YARN_LOG_MUL,     "%s.rope.scaling.yarn_log_multiplier"     },
@@ -457,6 +452,8 @@ enum llm_tensor {
     LLM_TENSOR_OUTPUT,
     LLM_TENSOR_OUTPUT_NORM,
     LLM_TENSOR_ROPE_FREQS,
+    LLM_TENSOR_ROPE_FACTORS_LONG,
+    LLM_TENSOR_ROPE_FACTORS_SHORT,
     LLM_TENSOR_ATTN_Q,
     LLM_TENSOR_ATTN_K,
     LLM_TENSOR_ATTN_V,
@@ -476,6 +473,7 @@ enum llm_tensor {
     LLM_TENSOR_FFN_DOWN_EXP,  // split experts for backward compatibility
     LLM_TENSOR_FFN_GATE_EXP,
     LLM_TENSOR_FFN_UP_EXP,
+    LLM_TENSOR_FFN_NORM_EXPS,
     LLM_TENSOR_FFN_DOWN_EXPS, // merged experts
     LLM_TENSOR_FFN_GATE_EXPS,
     LLM_TENSOR_FFN_UP_EXPS,
@@ -620,23 +618,6 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
             { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
         },
     },
-    {
-        LLM_ARCH_PERSIMMON,
-        {
-            { LLM_TENSOR_TOKEN_EMBD,      "token_embd"},
-            { LLM_TENSOR_OUTPUT_NORM,     "output_norm"},
-            { LLM_TENSOR_OUTPUT,          "output"},
-            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm"},
-            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv"},
-            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output"},
-            { LLM_TENSOR_ATTN_Q_NORM,     "blk.%d.attn_q_norm"},
-            { LLM_TENSOR_ATTN_K_NORM,     "blk.%d.attn_k_norm"},
-            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm"},
-            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down"},
-            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up"},
-            { LLM_TENSOR_ATTN_ROT_EMBD,   "blk.%d.attn_rot_embd"},
-        },
-    },
     {
         LLM_ARCH_MPT,
         {
@@ -847,18 +828,20 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
     {
         LLM_ARCH_PHI3,
         {
-            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
-            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
-            { LLM_TENSOR_OUTPUT,          "output" },
-            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
-            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv" },
-            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
-            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
-            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
-            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
-            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
-            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
-            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_TOKEN_EMBD,         "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,        "output_norm" },
+            { LLM_TENSOR_OUTPUT,             "output" },
+            { LLM_TENSOR_ROPE_FACTORS_LONG,  "rope_factors_long" },
+            { LLM_TENSOR_ROPE_FACTORS_SHORT, "rope_factors_short" },
+            { LLM_TENSOR_ATTN_NORM,          "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_QKV,           "blk.%d.attn_qkv" },
+            { LLM_TENSOR_ATTN_Q,             "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,             "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,             "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,           "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,           "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_DOWN,           "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,             "blk.%d.ffn_up" },
         },
     },
     {
@@ -1074,6 +1057,28 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
             { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
         },
     },
+    {
+        LLM_ARCH_ARCTIC,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_GATE_INP,    "blk.%d.ffn_gate_inp" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_NORM_EXPS,   "blk.%d.ffn_norm_exps" },
+            { LLM_TENSOR_FFN_GATE_EXPS,   "blk.%d.ffn_gate_exps" },
+            { LLM_TENSOR_FFN_DOWN_EXPS,   "blk.%d.ffn_down_exps" },
+            { LLM_TENSOR_FFN_UP_EXPS,     "blk.%d.ffn_up_exps" },
+        },
+    },
     {
         LLM_ARCH_DEEPSEEK2,
         {
@@ -1748,6 +1753,8 @@ struct llama_state {
     llama_state() {
 #ifdef GGML_USE_METAL
         ggml_backend_metal_log_set_callback(log_callback, log_callback_user_data);
+#elif defined(GGML_USE_CUDA)
+        ggml_backend_cuda_log_set_callback(log_callback, log_callback_user_data);
 #endif
     }
 
@@ -1761,17 +1768,24 @@ static llama_state g_state;
 // available llama models
 enum e_model {
     MODEL_UNKNOWN,
+    MODEL_14M,
     MODEL_17M,
     MODEL_22M,
     MODEL_33M,
+    MODEL_70M,
     MODEL_109M,
     MODEL_137M,
+    MODEL_160M,
     MODEL_335M,
+    MODEL_410M,
     MODEL_0_5B,
     MODEL_1B,
+    MODEL_1_4B,
     MODEL_2B,
+    MODEL_2_8B,
     MODEL_3B,
     MODEL_4B,
+    MODEL_6_9B,
     MODEL_7B,
     MODEL_8B,
     MODEL_12B,
@@ -1796,6 +1810,7 @@ enum e_model {
     MODEL_8x7B,
     MODEL_8x22B,
     MODEL_16x12B,
+    MODEL_10B_128x3_66B,
 };
 
 static const size_t kiB = 1024;
@@ -1805,6 +1820,7 @@ static const size_t GiB = 1024*MiB;
 struct llama_hparams {
     bool vocab_only;
     bool rope_finetuned;
+    bool use_par_res;
 
     uint32_t n_vocab;
     uint32_t n_ctx_train; // context size the model was trained on
@@ -1830,6 +1846,7 @@ struct llama_hparams {
     float f_norm_eps;
     float f_norm_rms_eps;
 
+    float    rope_attn_factor = 1.0f;
     float    rope_freq_base_train;
     float    rope_freq_scale_train;
     uint32_t n_yarn_orig_ctx;
@@ -1885,6 +1902,7 @@ struct llama_hparams {
 
         if (!is_float_close(this->f_norm_eps,            other.f_norm_eps,            EPSILON)) return true;
         if (!is_float_close(this->f_norm_rms_eps,        other.f_norm_rms_eps,        EPSILON)) return true;
+        if (!is_float_close(this->rope_attn_factor,      other.rope_attn_factor,      EPSILON)) return true;
         if (!is_float_close(this->rope_freq_base_train,  other.rope_freq_base_train,  EPSILON)) return true;
         if (!is_float_close(this->rope_freq_scale_train, other.rope_freq_scale_train, EPSILON)) return true;
         if (!is_float_close(this->expert_weights_scale,  other.expert_weights_scale,  EPSILON)) return true;
@@ -1990,6 +2008,7 @@ struct llama_layer {
     struct ggml_tensor * ffn_norm_b;
     struct ggml_tensor * layer_out_norm;
     struct ggml_tensor * layer_out_norm_b;
+    struct ggml_tensor * ffn_norm_exps;
 
     // ff
     struct ggml_tensor * ffn_gate; // w1
@@ -2027,6 +2046,10 @@ struct llama_layer {
     // mamba bias
     struct ggml_tensor * ssm_conv1d_b;
     struct ggml_tensor * ssm_dt_b;
+
+    // long rope factors
+    struct ggml_tensor * rope_long  = nullptr;
+    struct ggml_tensor * rope_short = nullptr;
 };
 
 struct llama_kv_cell {
@@ -2343,10 +2366,6 @@ struct llama_context {
 
     // control vectors
     struct llama_control_vector cvec;
-
-#ifdef GGML_USE_MPI
-    ggml_mpi_context * ctx_mpi = NULL;
-#endif
 };
 
 static ggml_backend_buffer_type_t llama_default_buffer_type_offload(const llama_model & model, int gpu) {
@@ -2566,7 +2585,6 @@ static bool llama_kv_cache_init(
 static bool llama_kv_cache_find_slot(
            struct llama_kv_cache & cache,
         const struct llama_batch & batch) {
-    const uint32_t n_ctx    = cache.size;
     const uint32_t n_tokens = batch.n_tokens;
 
     if (cache.recurrent) {
@@ -2617,16 +2635,16 @@ static bool llama_kv_cache_find_slot(
     }
     // otherwise, one cell per token.
 
-    if (n_tokens > n_ctx) {
-        LLAMA_LOG_ERROR("%s: n_tokens=%d > n_ctx=%d\n", __func__, n_tokens, n_ctx);
+    if (n_tokens > cache.size) {
+        LLAMA_LOG_ERROR("%s: n_tokens=%d > cache.size=%d\n", __func__, n_tokens, cache.size);
         return false;
     }
 
     uint32_t n_tested = 0;
 
     while (true) {
-        if (cache.head + n_tokens > n_ctx) {
-            n_tested += n_ctx - cache.head;
+        if (cache.head + n_tokens > cache.size) {
+            n_tested += cache.size - cache.head;
             cache.head = 0;
             continue;
         }
@@ -2645,7 +2663,7 @@ static bool llama_kv_cache_find_slot(
             break;
         }
 
-        if (n_tested >= n_ctx) {
+        if (n_tested >= cache.size) {
             //LLAMA_LOG_ERROR("%s: failed to find a slot for %d tokens\n", __func__, n_tokens);
             return false;
         }
@@ -3405,6 +3423,39 @@ struct llama_model_loader {
         return get_arr_n(llm_kv(kid), result, required);
     }
 
+    template<typename T>
+    bool get_arr(const std::string & key, std::vector<T> & result, const bool required = true) {
+        const int kid = gguf_find_key(meta, key.c_str());
+
+        if (kid < 0) {
+            if (required) {
+                throw std::runtime_error(format("key not found in model: %s", key.c_str()));
+            }
+            return false;
+        }
+
+        struct GGUFMeta::ArrayInfo arr_info =
+            GGUFMeta::GKV<GGUFMeta::ArrayInfo>::get_kv(meta, kid);
+
+        if (arr_info.gt != GGUF_TYPE_FLOAT32 && arr_info.gt != GGUF_TYPE_INT32) {
+            throw std::runtime_error(format("%s is not a float32 or int32 array", key.c_str()));
+        }
+
+        // GGML_ASSERT(gguf_type_size(arr_info.gt) == sizeof(T));
+        GGML_ASSERT((arr_info.gt != GGUF_TYPE_FLOAT32 || std::is_same<T, float>::value));
+        GGML_ASSERT((arr_info.gt != GGUF_TYPE_INT32   || std::is_same<T, int>::value));
+
+        result.resize(arr_info.length);
+        result.assign((const T*)arr_info.data, (const T *)arr_info.data + arr_info.length);
+
+        return true;
+    }
+
+    template<typename T>
+    bool get_arr(const enum llm_kv kid, T& result, const bool required = true) {
+        return get_arr(llm_kv(kid), result, required);
+    }
+
     template<typename T>
     bool get_key(const std::string & key, T & result, const bool required = true) {
         auto it = kv_overrides.find(key);
@@ -3479,11 +3530,15 @@ struct llama_model_loader {
         return get_tensor_meta(get_tensor_name(i));
     }
 
-    struct ggml_tensor * create_tensor_for(struct ggml_context * ctx, const struct ggml_tensor * cur) {
+    struct ggml_tensor * create_tensor_for(struct ggml_context * ctx, const struct ggml_tensor * cur, bool duplicated) {
         struct ggml_tensor * tensor = ggml_dup_tensor(ctx, cur);
         ggml_set_name(tensor, ggml_get_name(cur));
 
-        n_created++;
+        if (duplicated) {
+            size_data += ggml_nbytes(cur);
+        } else {
+            n_created++;
+        }
 
         return tensor;
     }
@@ -3518,14 +3573,17 @@ struct llama_model_loader {
         return cur;
     }
 
-    struct ggml_tensor * create_tensor(struct ggml_context * ctx, const std::string & name, const std::vector<int64_t> & ne, bool required = true) {
-        const struct ggml_tensor * cur = check_tensor_dims(name, ne, required);
+    static const int TENSOR_NOT_REQUIRED = 1;
+    static const int TENSOR_DUPLICATED   = 2;
+
+    struct ggml_tensor * create_tensor(struct ggml_context * ctx, const std::string & name, const std::vector<int64_t> & ne, int flags = 0) {
+        const struct ggml_tensor * cur = check_tensor_dims(name, ne, !(flags & TENSOR_NOT_REQUIRED));
 
         if (cur == NULL) {
             return NULL;
         }
 
-        return create_tensor_for(ctx, cur);
+        return create_tensor_for(ctx, cur, flags & TENSOR_DUPLICATED);
     }
 
     struct ggml_tensor * create_tensor_as_view(struct ggml_context * ctx, struct ggml_tensor * base, const std::string & name, const std::vector<int64_t> & ne, size_t offset, bool required = true) {
@@ -3825,39 +3883,50 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
 
 static const char * llama_model_type_name(e_model type) {
     switch (type) {
-        case MODEL_22M:    return "22M";
-        case MODEL_33M:    return "33M";
-        case MODEL_109M:   return "109M";
-        case MODEL_137M:   return "137M";
-        case MODEL_0_5B:   return "0.5B";
-        case MODEL_1B:     return "1B";
-        case MODEL_2B:     return "2B";
-        case MODEL_3B:     return "3B";
-        case MODEL_7B:     return "7B";
-        case MODEL_8B:     return "8B";
-        case MODEL_12B:    return "12B";
-        case MODEL_13B:    return "13B";
-        case MODEL_14B:    return "14B";
-        case MODEL_15B:    return "15B";
-        case MODEL_16B:    return "16B";
-        case MODEL_20B:    return "20B";
-        case MODEL_30B:    return "30B";
-        case MODEL_34B:    return "34B";
-        case MODEL_35B:    return "35B";
-        case MODEL_40B:    return "40B";
-        case MODEL_65B:    return "65B";
-        case MODEL_70B:    return "70B";
-        case MODEL_236B:   return "236B";
-        case MODEL_314B:   return "314B";
-        case MODEL_SMALL:  return "0.1B";
-        case MODEL_MEDIUM: return "0.4B";
-        case MODEL_LARGE:  return "0.8B";
-        case MODEL_XL:     return "1.5B";
-        case MODEL_A2_7B:  return "A2.7B";
-        case MODEL_8x7B:   return "8x7B";
-        case MODEL_8x22B:  return "8x22B";
-        case MODEL_16x12B: return "16x12B";
-        default:           return "?B";
+        case MODEL_14M:           return "14M";
+        case MODEL_17M:           return "17M";
+        case MODEL_22M:           return "22M";
+        case MODEL_33M:           return "33M";
+        case MODEL_70M:           return "70M";
+        case MODEL_109M:          return "109M";
+        case MODEL_137M:          return "137M";
+        case MODEL_160M:          return "160M";
+        case MODEL_335M:          return "335M";
+        case MODEL_410M:          return "410M";
+        case MODEL_0_5B:          return "0.5B";
+        case MODEL_1B:            return "1B";
+        case MODEL_1_4B:          return "1.4B";
+        case MODEL_2B:            return "2B";
+        case MODEL_2_8B:          return "2.8B";
+        case MODEL_3B:            return "3B";
+        case MODEL_4B:            return "4B";
+        case MODEL_6_9B:          return "6.9B";
+        case MODEL_7B:            return "7B";
+        case MODEL_8B:            return "8B";
+        case MODEL_12B:           return "12B";
+        case MODEL_13B:           return "13B";
+        case MODEL_14B:           return "14B";
+        case MODEL_15B:           return "15B";
+        case MODEL_16B:           return "16B";
+        case MODEL_20B:           return "20B";
+        case MODEL_30B:           return "30B";
+        case MODEL_34B:           return "34B";
+        case MODEL_35B:           return "35B";
+        case MODEL_40B:           return "40B";
+        case MODEL_65B:           return "65B";
+        case MODEL_70B:           return "70B";
+        case MODEL_236B:          return "236B";
+        case MODEL_314B:          return "314B";
+        case MODEL_SMALL:         return "0.1B";
+        case MODEL_MEDIUM:        return "0.4B";
+        case MODEL_LARGE:         return "0.8B";
+        case MODEL_XL:            return "1.5B";
+        case MODEL_A2_7B:         return "A2.7B";
+        case MODEL_8x7B:          return "8x7B";
+        case MODEL_8x22B:         return "8x22B";
+        case MODEL_16x12B:        return "16x12B";
+        case MODEL_10B_128x3_66B: return "10B+128x3.66B";
+        default:                  return "?B";
     }
 }
 
@@ -3950,6 +4019,8 @@ static void llm_load_hparams(
     }
     hparams.rope_freq_scale_train = ropescale == 0.0f ? 1.0f : 1.0f/ropescale;
 
+    ml.get_key(LLM_KV_ROPE_SCALING_ATTN_FACTOR, hparams.rope_attn_factor, false);
+
     // sanity check for n_rot (optional)
     {
         hparams.n_rot = (hparams.n_head == 0) ? 0 : hparams.n_embd / hparams.n_head;
@@ -4049,14 +4120,6 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
-        case LLM_ARCH_PERSIMMON:
-            {
-                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
-                switch (hparams.n_layer) {
-                    case 36: model.type = e_model::MODEL_8B; break;
-                    default: model.type = e_model::MODEL_UNKNOWN;
-                }
-            } break;
         case LLM_ARCH_REFACT:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
@@ -4198,6 +4261,7 @@ static void llm_load_hparams(
                 switch (hparams.n_layer) {
                     case 24: model.type = e_model::MODEL_1B; break;
                     case 32: model.type = e_model::MODEL_3B; break;
+                    case 40: model.type = e_model::MODEL_14B; break;
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
@@ -4338,6 +4402,65 @@ static void llm_load_hparams(
                     default: model.type = e_model::MODEL_UNKNOWN;
                 }
             } break;
+        case LLM_ARCH_GPTNEOX:
+            {
+                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
+                ml.get_key(LLM_KV_USE_PARALLEL_RESIDUAL, hparams.use_par_res);
+                switch (hparams.n_layer) {
+                    case 6:
+                        switch (hparams.n_ff) {
+                            case 512: model.type = e_model::MODEL_14M; break;
+                            case 2048: model.type = e_model::MODEL_70M; break;
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    case 12:
+                        switch (hparams.n_ff) {
+                            case 3072: model.type = e_model::MODEL_160M; break;
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    case 16:
+                        switch (hparams.n_ff) {
+                            case 8192: model.type = e_model::MODEL_1B; break;
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    case 24:
+                        switch (hparams.n_ff) {
+                            case 4096: model.type = e_model::MODEL_410M; break;
+                            case 8192: model.type = e_model::MODEL_1_4B; break;
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    case 32:
+                        switch (hparams.n_ff) {
+                            case 10240: model.type = e_model::MODEL_2_8B; break;
+                            case 16384: model.type = e_model::MODEL_6_9B; break;
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    case 36:
+                        switch (hparams.n_ff) {
+                            case 20480: model.type = e_model::MODEL_12B; break;
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    case 44:
+                        switch (hparams.n_ff) {
+                            case 24576: model.type = e_model::MODEL_20B; break;
+                            default: model.type = e_model::MODEL_UNKNOWN;
+                        } break;
+                    default: model.type = e_model::MODEL_UNKNOWN;
+                }
+            } break;
+        case LLM_ARCH_ARCTIC:
+            {
+                ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+
+                if (hparams.n_expert == 128) {
+                    switch (hparams.n_layer) {
+                        case 35: model.type = e_model::MODEL_10B_128x3_66B; break;
+                        default: model.type = e_model::MODEL_UNKNOWN;
+                    }
+                } else {
+                    model.type = e_model::MODEL_UNKNOWN;
+                }
+            } break;
         case LLM_ARCH_DEEPSEEK2:
             {
                 bool is_lite = (hparams.n_layer == 27);
@@ -4557,6 +4680,9 @@ static void llm_load_vocab(
             } else if (
                 tokenizer_pre == "qwen2") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_QWEN2;
+            } else if (
+                tokenizer_pre == "stablelm2") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_STABLELM2;
             } else if (
                 tokenizer_pre == "olmo") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_OLMO;
@@ -4678,7 +4804,8 @@ static void llm_load_vocab(
                         (t.first == "<|eot_id|>" ||
                          t.first == "<|im_end|>" ||
                          t.first == "<|end|>" ||
-                         t.first == "<end_of_turn>"
+                         t.first == "<end_of_turn>" ||
+                         t.first == "<|endoftext|>"
                         )
                    ) {
                     vocab.special_eot_id = t.second;
@@ -5004,6 +5131,7 @@ static bool llm_load_tensors(
     // create tensors for the weights
     {
         const int64_t n_embd       = hparams.n_embd;
+        const int64_t n_embd_head  = n_embd / hparams.n_head;
         const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa();
         const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa();
         const int64_t n_embd_gqa   = n_embd_v_gqa;
@@ -5036,12 +5164,10 @@ static bool llm_load_tensors(
                     {
                         model.output_norm = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                         if (model.arch != LLM_ARCH_MINICPM){
-                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, false);
+                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                             // if output is NULL, init from the input tok embed
                             if (model.output == NULL) {
-                                model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                                ml.n_created--; // artificial tensor
-                                ml.size_data += ggml_nbytes(model.output);
+                                model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
                             }
                         }
                     }
@@ -5060,10 +5186,10 @@ static bool llm_load_tensors(
                         layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
 
                         // optional bias tensors
-                        layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i), {n_embd},     false);
-                        layer.bk = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i), {n_embd_gqa}, false);
-                        layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i), {n_embd_gqa}, false);
-                        layer.bo = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i), {n_embd},     false);
+                        layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i), {n_embd},     llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.bk = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i), {n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i), {n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.bo = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i), {n_embd},     llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
 
@@ -5074,7 +5200,7 @@ static bool llm_load_tensors(
                         } else {
                             layer.ffn_gate_inp = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert});
 
-                            layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd,   n_ff, n_expert}, false);
+                            layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd,   n_ff, n_expert}, llama_model_loader::TENSOR_NOT_REQUIRED);
                             if (layer.ffn_gate_exps) {
                                 layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {  n_ff, n_embd, n_expert});
                                 layer.ffn_up_exps   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS,   "weight", i), {n_embd,   n_ff, n_expert});
@@ -5116,12 +5242,10 @@ static bool llm_load_tensors(
                     // output
                     {
                         model.output_norm = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, false);
+                        model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         // if output is NULL, init from the input tok embed
                         if (model.output == NULL) {
-                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                            ml.n_created--; // artificial tensor
-                            ml.size_data += ggml_nbytes(model.output);
+                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
                         }
                     }
 
@@ -5144,7 +5268,7 @@ static bool llm_load_tensors(
 
                         layer.ffn_gate_inp = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert});
 
-                        layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd, n_ff, n_expert}, false);
+                        layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd, n_ff, n_expert}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         if (layer.ffn_gate_exps) {
                             layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {  n_ff, n_embd, n_expert});
                             layer.ffn_up_exps   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS,   "weight", i), {n_embd,   n_ff, n_expert});
@@ -5246,11 +5370,9 @@ static bool llm_load_tensors(
                         model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                         model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
 
-                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, false);
+                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         if (!model.output) {
-                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // needs to be on GPU
-                            ml.n_created--; // artificial tensor
-                            ml.size_data += ggml_nbytes(model.output);
+                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // needs to be on GPU
                         }
                     }
 
@@ -5263,8 +5385,8 @@ static bool llm_load_tensors(
                         layer.attn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
                         layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "bias", i),   {n_embd});
 
-                        layer.attn_norm_2   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM_2, "weight", i), {n_embd}, false);
-                        layer.attn_norm_2_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM_2, "bias", i),   {n_embd}, false);
+                        layer.attn_norm_2   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM_2, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_norm_2_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM_2, "bias", i),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
                         layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
@@ -5282,7 +5404,12 @@ static bool llm_load_tensors(
                     {
                         model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                         model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
-                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab});
+                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        if (!model.output) {
+                            // needs to be on GPU
+                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
+                        }
+
                     }
 
                     for (int i = 0; i < n_layer; ++i) {
@@ -5310,47 +5437,6 @@ static bool llm_load_tensors(
                         layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP, "bias", i),     {n_ff});
                     }
                 } break;
-            case LLM_ARCH_PERSIMMON:
-                {
-                    model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"),  {n_embd, n_vocab});
-
-                    {
-                        model.output_norm    = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output_norm_b  = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
-                        model.output         = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab});
-                    }
-
-                    for (int i = 0; i < n_layer; ++i) {
-                        ggml_context * ctx_layer = ctx_for_layer(i);
-                        ggml_context * ctx_split = ctx_for_layer_split(i);
-
-                        auto & layer = model.layers[i];
-
-                        layer.attn_norm     = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM,   "weight", i), {n_embd});
-                        layer.attn_norm_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM,   "bias",   i), {n_embd});
-
-                        layer.wqkv          = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV,    "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
-                        layer.bqkv          = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV,    "bias",   i), {n_embd + 2*n_embd_gqa});
-
-                        layer.wo            = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT,    "weight", i), {n_embd, n_embd});
-                        layer.bo            = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT,    "bias",   i), {n_embd});
-
-                        layer.ffn_down      = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN,    "weight", i), {n_ff, n_embd});
-                        layer.ffn_down_b    = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN,    "bias",   i), {n_embd});
-
-                        layer.ffn_up        = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,      "weight", i), {n_embd, n_ff});
-                        layer.ffn_up_b      = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,      "bias",   i), {n_ff});
-
-                        layer.ffn_norm      = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM,    "weight", i), {n_embd});
-                        layer.ffn_norm_b    = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM,    "bias",   i), {n_embd});
-
-                        layer.attn_q_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {64});
-                        layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias",   i), {64});
-
-                        layer.attn_k_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {64});
-                        layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias",   i), {64});
-                    }
-                } break;
             case LLM_ARCH_BERT:
             case LLM_ARCH_NOMIC_BERT:
                 {
@@ -5419,14 +5505,14 @@ static bool llm_load_tensors(
                         layer.wq   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
                         layer.bq   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i),   {n_embd});
 
-                        layer.attn_q_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd}, false);
-                        layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias", i), {n_embd}, false);
+                        layer.attn_q_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wk   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
                         layer.bk   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i),   {n_embd_gqa});
 
-                        layer.attn_k_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, false);
-                        layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias", i), {n_embd}, false);
+                        layer.attn_k_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wv   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
                         layer.bv   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i),   {n_embd_gqa});
@@ -5488,18 +5574,16 @@ static bool llm_load_tensors(
             case LLM_ARCH_MPT:
                 {
                     model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, hparams.n_ctx_train}, false);
+                    model.pos_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, hparams.n_ctx_train}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                     // output
                     {
                         model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, false);
+                        model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
-                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, false);
+                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         if (!model.output) {
-                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); // needs to be on GPU
-                            ml.n_created--; // artificial tensor
-                            ml.size_data += ggml_nbytes(model.output);
+                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // needs to be on GPU
                         }
                     }
 
@@ -5510,31 +5594,31 @@ static bool llm_load_tensors(
                         auto & layer = model.layers[i];
 
                         layer.attn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
-                        layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "bias", i),   {n_embd}, false);
+                        layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "bias", i),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
-                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa}, false);
+                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
-                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd}, false);
+                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
-                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd}, false);
+                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
-                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd}, false);
+                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});
-                        layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff}, false);
+                        layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
-                        layer.attn_q_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd}, false);
-                        layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias",   i), {n_embd}, false);
+                        layer.attn_q_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_q_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "bias",   i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
-                        layer.attn_k_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, false);
-                        layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias",   i), {n_embd}, false);
+                        layer.attn_k_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_k_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "bias",   i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         // AWQ ScaleActivation layer
-                        layer.ffn_act = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_ACT, "scales", i), {n_ff}, false);
+                        layer.ffn_act = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_ACT, "scales", i), {n_ff}, llama_model_loader::TENSOR_NOT_REQUIRED);
                     }
                 } break;
             case LLM_ARCH_STABLELM:
@@ -5563,17 +5647,17 @@ static bool llm_load_tensors(
                         layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
 
                         // optional bias tensors, present in Stable LM 2 1.6B
-                        layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i), {n_embd},     false);
-                        layer.bk = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i), {n_embd_gqa}, false);
-                        layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i), {n_embd_gqa}, false);
+                        layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q,   "bias", i), {n_embd},     llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.bk = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K,   "bias", i), {n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.bv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_V,   "bias", i), {n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         // optional q and k layernorms, present in StableLM 2 12B
-                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head}, false);
-                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv}, false);
+                        layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         // optional FFN norm, not present in StableLM 2 12B which uses parallel residual
-                        layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, false);
-                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd}, false);
+                        layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff});
                         layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd});
@@ -5616,12 +5700,10 @@ static bool llm_load_tensors(
                     // output
                     {
                         model.output_norm = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                        model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, false);
+                        model.output      = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         // if output is NULL, init from the input tok embed
                         if (model.output == NULL) {
-                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                            ml.n_created--; // artificial tensor
-                            ml.size_data += ggml_nbytes(model.output);
+                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
                         }
                     }
 
@@ -5719,8 +5801,8 @@ static bool llm_load_tensors(
                         layer.attn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
                         layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "bias", i),   {n_embd});
 
-                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa}, false);
-                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa}, false);
+                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa}, llama_model_loader::TENSOR_NOT_REQUIRED);
 
                         if (layer.wqkv == nullptr) {
                             layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd});
@@ -5757,17 +5839,20 @@ static bool llm_load_tensors(
                         ggml_context* ctx_layer = ctx_for_layer(i);
                         ggml_context* ctx_split = ctx_for_layer_split(i);
 
-                        auto& layer = model.layers[i];
+                        auto & layer = model.layers[i];
 
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), { n_embd });
 
-                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), { n_embd, n_embd + 2 * n_embd_gqa }, false);
-                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), { n_embd, n_embd });
+                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), { n_embd, n_embd + 2 * n_embd_gqa }, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), { n_embd, n_embd });
 
                         layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), { n_embd });
 
                         layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd });
                         layer.ffn_up = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i), { n_embd, 2 * n_ff });
+
+                        layer.rope_long  = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ROPE_FACTORS_LONG,  "weight"), { n_embd_head/2 }, llama_model_loader::TENSOR_NOT_REQUIRED | (i != 0 ? llama_model_loader::TENSOR_DUPLICATED : 0));
+                        layer.rope_short = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ROPE_FACTORS_SHORT, "weight"), { n_embd_head/2 }, llama_model_loader::TENSOR_NOT_REQUIRED | (i != 0 ? llama_model_loader::TENSOR_DUPLICATED : 0));
                     }
                 } break;
             case LLM_ARCH_PLAMO:
@@ -5936,9 +6021,7 @@ static bool llm_load_tensors(
 
                     // output
                     model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
-                    model.output      = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}); // same as tok_embd, duplicated to allow offloading
-                    ml.n_created--; // artificial tensor
-                    ml.size_data += ggml_nbytes(model.output);
+                    model.output      = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD,  "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
 
                     const int64_t n_ff          = hparams.n_ff;
                     const int64_t n_embd_head_k = hparams.n_embd_head_k;
@@ -5973,12 +6056,10 @@ static bool llm_load_tensors(
                         model.output_norm   = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                         model.output_norm_b = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
 
-                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, false);
+                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         // if output is NULL, init from the input tok embed
                         if (model.output == NULL) {
-                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                            ml.n_created--; // artificial tensor
-                            ml.size_data += ggml_nbytes(model.output);
+                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
                         }
 
                     }
@@ -6029,12 +6110,10 @@ static bool llm_load_tensors(
                     {
                         model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
 
-                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, false);
+                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         // if output is NULL, init from the input tok embed, duplicated to allow offloading
                         if (model.output == NULL) {
-                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                            ml.n_created--; // artificial tensor
-                            ml.size_data += ggml_nbytes(model.output);
+                            model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
                         }
                     }
 
@@ -6095,9 +6174,7 @@ static bool llm_load_tensors(
                     {
                         model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
                         // init output from the input tok embed
-                        model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                        ml.n_created--; // artificial tensor
-                        ml.size_data += ggml_nbytes(model.output);
+                        model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
                     }
 
                     for (int i = 0; i < n_layer; ++i) {
@@ -6129,12 +6206,10 @@ static bool llm_load_tensors(
 
                     // output
                     {
-                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, false);
+                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
                         // if output is NULL, init from the input tok embed
                         if (model.output == NULL) {
-                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
-                            ml.n_created--; // artificial tensor
-                            ml.size_data += ggml_nbytes(model.output);
+                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
                         }
                     }
 
@@ -6154,6 +6229,81 @@ static bool llm_load_tensors(
                         layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff});
                     }
                 } break;
+            case LLM_ARCH_GPTNEOX:
+                {
+                    model.tok_embd   = ml.create_tensor(ctx_input,  tn(LLM_TENSOR_TOKEN_EMBD,      "weight"), {n_embd, n_vocab});
+                    // output
+                    {
+                        model.output_norm   = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output_norm_b = ml.create_tensor(ctx_output,       tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd});
+                        model.output        = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab});
+                    }
+
+                    for (int i = 0; i < n_layer; ++i) {
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
+
+                        auto & layer = model.layers[i];
+
+                        layer.attn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+                        layer.attn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "bias", i),   {n_embd});
+
+                        layer.wqkv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa});
+                        layer.bqkv = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_QKV, "bias", i),   {n_embd + 2*n_embd_gqa});
+
+                        layer.wo   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+                        layer.bo   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd});
+
+                        layer.ffn_norm   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+                        layer.ffn_norm_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd});
+
+                        layer.ffn_down   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd});
+                        layer.ffn_down_b = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd});
+
+                        layer.ffn_up     = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff});
+                        layer.ffn_up_b   = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff});
+                    }
+                } break;
+            case LLM_ARCH_ARCTIC:
+                {
+                    model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+                    // output
+                    {
+                        model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+                        model.output = ml.create_tensor(ctx_output_split, tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_NOT_REQUIRED);
+                        // if output is NULL, init from the input tok embed
+                        if (model.output == NULL) {
+                            model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED);
+                        }
+                    }
+
+                    for (int i = 0; i < n_layer; ++i) {
+                        ggml_context * ctx_layer = ctx_for_layer(i);
+                        ggml_context * ctx_split = ctx_for_layer_split(i);
+
+                        auto & layer = model.layers[i];
+
+                        layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
+                        layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
+                        layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
+                        layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
+                        layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+
+                        layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+
+                        layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_embd});
+                        layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_embd, n_embd});
+                        layer.ffn_up   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_embd});
+
+                        layer.ffn_gate_inp = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_GATE_INP, "weight", i), {n_embd, n_expert});
+                        layer.ffn_norm_exps = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM_EXPS, "weight", i), {n_embd});
+                        layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), {n_embd,   n_ff, n_expert}, false);
+                        layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {  n_ff, n_embd, n_expert});
+                        layer.ffn_up_exps   = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS,   "weight", i), {n_embd,   n_ff, n_expert});
+                    }
+                } break;
             case LLM_ARCH_DEEPSEEK2:
                 {
                     bool is_lite = (hparams.n_layer == 27);
@@ -6482,10 +6632,7 @@ static struct ggml_tensor * llm_build_inp_embd(
 
         inpL = ggml_get_rows(ctx, tok_embd, lctx.inp_tokens);
     } else {
-#ifdef GGML_USE_MPI
-        GGML_ASSERT(false && "not implemented");
-#endif
-        lctx.inp_embd = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, batch.n_tokens);
+       lctx.inp_embd = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_embd, batch.n_tokens);
         inpL = lctx.inp_embd;
         ggml_set_input(lctx.inp_embd);
     }
@@ -6816,7 +6963,7 @@ static struct ggml_tensor * llm_build_kqv(
 
         cur = ggml_flash_attn_ext(ctx, q, k, v, kq_mask, kq_scale, hparams.f_max_alibi_bias);
 
-        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3) {
+        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX) {
             ggml_flash_attn_ext_set_prec(cur, GGML_PREC_F32);
         }
 
@@ -6825,7 +6972,7 @@ static struct ggml_tensor * llm_build_kqv(
         struct ggml_tensor * kq = ggml_mul_mat(ctx, k, q);
         cb(kq, "kq", il);
 
-        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3) {
+        if (model.arch == LLM_ARCH_PHI2 || model.arch == LLM_ARCH_PHI3 || model.arch == LLM_ARCH_GPTNEOX) {
             // for this arch, we need to perform the KQ multiplication with F32 precision, otherwise we get NaNs
             // ref: https://github.com/ggerganov/llama.cpp/pull/4490#issuecomment-1859055847
             ggml_mul_mat_set_prec(kq, GGML_PREC_F32);
@@ -7050,17 +7197,20 @@ struct llm_build_context {
         cb(lctx.inp_K_shift, "K_shift", -1);
         ggml_set_input(lctx.inp_K_shift);
 
+
         for (int il = 0; il < n_layer; ++il) {
+            struct ggml_tensor * rope_factors = build_rope_factors(il);
             struct ggml_tensor * tmp =
                 // we rotate only the first n_rot dimensions
-                ggml_rope_custom_inplace(ctx0,
+                ggml_rope_ext_inplace(ctx0,
                         ggml_view_3d(ctx0, kv_self.k_l[il],
                             n_embd_head_k, n_head_kv, n_ctx,
                             ggml_row_size(kv_self.k_l[il]->type, n_embd_head_k),
                             ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
                             0),
-                        lctx.inp_K_shift, n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
+                        lctx.inp_K_shift, rope_factors, n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
+
             cb(tmp, "K_shifted", il);
             ggml_build_forward_expand(gf, tmp);
         }
@@ -7163,6 +7313,17 @@ struct llm_build_context {
         return lctx.inp_pos;
     }
 
+    struct ggml_tensor * build_rope_factors(int il) {
+        // choose long/short freq factors based on the context size
+        const auto n_ctx_pre_seq = cparams.n_ctx / cparams.n_seq_max;
+
+        if (n_ctx_pre_seq > hparams.n_yarn_orig_ctx) {
+            return model.layers[il].rope_long;
+        }
+
+        return model.layers[il].rope_short;
+    }
+
     struct ggml_tensor * build_inp_out_ids() {
         lctx.inp_out_ids = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_outputs);
         cb(lctx.inp_out_ids, "inp_out_ids", -1);
@@ -7270,15 +7431,15 @@ struct llm_build_context {
                     cb(Vcur, "Vcur", il);
                 }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -7401,13 +7562,13 @@ struct llm_build_context {
 
                 switch (model.type) {
                     case MODEL_7B:
-                        Qcur = ggml_rope_custom(
-                            ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                        Qcur = ggml_rope_ext(
+                            ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                             n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                             ext_factor, attn_factor, beta_fast, beta_slow
                         );
-                        Kcur = ggml_rope_custom(
-                            ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                        Kcur = ggml_rope_ext(
+                            ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                             n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                             ext_factor, attn_factor, beta_fast, beta_slow
                         );
@@ -7513,15 +7674,15 @@ struct llm_build_context {
                 struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -7634,14 +7795,14 @@ struct llm_build_context {
                 Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
 
                 // using mode = 2 for neox mode
-                Qcur = ggml_rope_custom(
-                    ctx0, Qcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Qcur = ggml_rope_ext(
+                    ctx0, Qcur, inp_pos, nullptr, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, Kcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Kcur = ggml_rope_ext(
+                    ctx0, Kcur, inp_pos, nullptr, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Kcur, "Kcur", il);
@@ -7757,15 +7918,15 @@ struct llm_build_context {
                     cb(Vcur, "Vcur", il);
                 }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -7910,15 +8071,15 @@ struct llm_build_context {
                 cb(Kcur, "Kcur", il);
                 cb(Vcur, "Vcur", il);
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -8088,213 +8249,6 @@ struct llm_build_context {
         return gf;
     }
 
-    struct ggml_cgraph * build_persimmon() {
-        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
-
-        const int64_t n_embd_head = hparams.n_embd_head_v;
-        GGML_ASSERT(n_embd_head   == hparams.n_embd_head_k);
-        GGML_ASSERT(n_embd_head/2 == hparams.n_rot);
-
-        struct ggml_tensor * cur;
-        struct ggml_tensor * inpL;
-
-        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
-
-        // inp_pos - contains the positions
-        struct ggml_tensor * inp_pos = build_inp_pos();
-
-        // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
-        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
-
-        for (int il = 0; il < n_layer; ++il) {
-            struct ggml_tensor * residual = inpL;
-
-            cur = llm_build_norm(ctx0, inpL, hparams,
-                    model.layers[il].attn_norm,
-                    model.layers[il].attn_norm_b,
-                    LLM_NORM, cb, il);
-            cb(cur, "attn_norm", il);
-
-            // self attention
-            {
-                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
-                cb(cur, "wqkv", il);
-
-                cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
-                cb(cur, "bqkv", il);
-
-                // split qkv
-                GGML_ASSERT(n_head_kv == n_head);
-
-                struct ggml_tensor * tmpqkv = ggml_reshape_4d(ctx0, cur, n_embd_head, 3, n_head, n_tokens);
-                cb(tmpqkv, "tmpqkv", il);
-
-                struct ggml_tensor * tmpqkv_perm = ggml_cont(ctx0, ggml_permute(ctx0, tmpqkv, 0, 3, 1, 2));
-                cb(tmpqkv_perm, "tmpqkv", il);
-
-                struct ggml_tensor * tmpq = ggml_view_3d(
-                        ctx0, tmpqkv_perm, n_embd_head, n_head, n_tokens,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head * n_head,
-                        0
-                        );
-                cb(tmpq, "tmpq", il);
-
-                struct ggml_tensor * tmpk = ggml_view_3d(
-                        ctx0, tmpqkv_perm, n_embd_head, n_head, n_tokens,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head * n_head,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head * n_head * n_tokens
-                        );
-                cb(tmpk, "tmpk", il);
-
-                // Q/K Layernorm
-                tmpq = llm_build_norm(ctx0, tmpq, hparams,
-                        model.layers[il].attn_q_norm,
-                        model.layers[il].attn_q_norm_b,
-                        LLM_NORM, cb, il);
-                cb(tmpq, "tmpq", il);
-
-                tmpk = llm_build_norm(ctx0, tmpk, hparams,
-                        model.layers[il].attn_k_norm,
-                        model.layers[il].attn_k_norm_b,
-                        LLM_NORM, cb, il);
-                cb(tmpk, "tmpk", il);
-
-                // RoPE the first n_rot of q/k, pass the other half, and concat.
-                struct ggml_tensor * qrot = ggml_view_3d(
-                        ctx0, tmpq, n_rot, n_head, n_tokens,
-                        ggml_element_size(tmpq) * n_embd_head,
-                        ggml_element_size(tmpq) * n_embd_head * n_head,
-                        0
-                        );
-                cb(qrot, "qrot", il);
-
-                struct ggml_tensor * krot = ggml_view_3d(
-                        ctx0, tmpk, n_rot, n_head, n_tokens,
-                        ggml_element_size(tmpk) * n_embd_head,
-                        ggml_element_size(tmpk) * n_embd_head * n_head,
-                        0
-                        );
-                cb(krot, "krot", il);
-
-                // get the second half of tmpq, e.g tmpq[n_rot:, :, :]
-                struct ggml_tensor * qpass = ggml_view_3d(
-                        ctx0, tmpq, n_rot, n_head, n_tokens,
-                        ggml_element_size(tmpq) * n_embd_head,
-                        ggml_element_size(tmpq) * n_embd_head * n_head,
-                        ggml_element_size(tmpq) * n_rot
-                        );
-                cb(qpass, "qpass", il);
-
-                struct ggml_tensor * kpass = ggml_view_3d(
-                        ctx0, tmpk, n_rot, n_head, n_tokens,
-                        ggml_element_size(tmpk) * n_embd_head,
-                        ggml_element_size(tmpk) * n_embd_head * n_head,
-                        ggml_element_size(tmpk) * n_rot
-                        );
-                cb(kpass, "kpass", il);
-
-                struct ggml_tensor * qrotated = ggml_rope_custom(
-                    ctx0, qrot, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
-                    freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
-                );
-                cb(qrotated, "qrotated", il);
-
-                struct ggml_tensor * krotated = ggml_rope_custom(
-                    ctx0, krot, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
-                    freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
-                );
-                cb(krotated, "krotated", il);
-
-                // ggml currently only supports concatenation on dim=2
-                // so we need to permute qrot, qpass, concat, then permute back.
-                qrotated = ggml_cont(ctx0, ggml_permute(ctx0, qrotated, 2, 1, 0, 3));
-                cb(qrotated, "qrotated", il);
-
-                krotated = ggml_cont(ctx0, ggml_permute(ctx0, krotated, 2, 1, 0, 3));
-                cb(krotated, "krotated", il);
-
-                qpass = ggml_cont(ctx0, ggml_permute(ctx0, qpass, 2, 1, 0, 3));
-                cb(qpass, "qpass", il);
-
-                kpass = ggml_cont(ctx0, ggml_permute(ctx0, kpass, 2, 1, 0, 3));
-                cb(kpass, "kpass", il);
-
-                struct ggml_tensor * Qcur = ggml_concat(ctx0, qrotated, qpass);
-                cb(Qcur, "Qcur", il);
-
-                struct ggml_tensor * Kcur = ggml_concat(ctx0, krotated, kpass);
-                cb(Kcur, "Kcur", il);
-
-                struct ggml_tensor * Q = ggml_cont(ctx0, ggml_permute(ctx0, Qcur, 2, 1, 0, 3));
-                cb(Q, "Q", il);
-
-                Kcur = ggml_cont(ctx0, ggml_permute(ctx0, Kcur, 2, 1, 0, 3));
-                cb(Kcur, "Kcur", il);
-
-                struct ggml_tensor * Vcur = ggml_view_3d(
-                        ctx0, tmpqkv_perm, n_embd_head, n_head, n_tokens,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head * n_head,
-                        ggml_element_size(tmpqkv_perm) * n_embd_head * n_head * n_tokens * 2
-                        );
-                cb(Vcur, "Vcur", il);
-
-                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
-                        model.layers[il].wo, model.layers[il].bo,
-                        Kcur, Vcur, Q, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
-            }
-
-            if (il == n_layer - 1) {
-                // skip computing output for unused tokens
-                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
-                cur      = ggml_get_rows(ctx0,      cur, inp_out_ids);
-                residual = ggml_get_rows(ctx0, residual, inp_out_ids);
-            }
-
-            struct ggml_tensor * ffn_inp = ggml_add(ctx0, residual, cur);
-            cb(ffn_inp, "ffn_inp", il);
-
-            // feed-forward network
-            {
-                cur = llm_build_norm(ctx0, ffn_inp, hparams,
-                        model.layers[il].ffn_norm,
-                        model.layers[il].ffn_norm_b,
-                        LLM_NORM, cb, il);
-                cb(cur, "ffn_norm", il);
-
-                cur = llm_build_ffn(ctx0, cur,
-                        model.layers[il].ffn_up,   model.layers[il].ffn_up_b,
-                        NULL,                      NULL,
-                        model.layers[il].ffn_down, model.layers[il].ffn_down_b,
-                        NULL,
-                        LLM_FFN_RELU_SQR, LLM_FFN_SEQ, cb, il);
-                cb(cur, "ffn_out", il);
-            }
-
-            cur = ggml_add(ctx0, cur, ffn_inp);
-            cb(cur, "l_out", il);
-
-            inpL = cur;
-        }
-
-        cur = inpL;
-
-        cur = llm_build_norm(ctx0, cur, hparams,
-                model.output_norm,
-                model.output_norm_b,
-                LLM_NORM, cb, -1);
-        cb(cur, "result_norm", -1);
-
-        cur = ggml_mul_mat(ctx0, model.output, cur);
-        cb(cur, "result_output", -1);
-
-        ggml_build_forward_expand(gf, cur);
-
-        return gf;
-    }
-
     struct ggml_cgraph * build_refact() {
         struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
 
@@ -8471,15 +8425,15 @@ struct llm_build_context {
                 cb(Kcur, "Kcur", il);
                 cb(Vcur, "Vcur", il);
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -8911,15 +8865,15 @@ struct llm_build_context {
                 }
 
 
-                Qcur = ggml_rope_custom(
-                    ctx0, Qcur, inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, Qcur, inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, Kcur, inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, Kcur, inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -9031,14 +8985,14 @@ struct llm_build_context {
                 Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
 
                 // using mode = 2 for neox mode
-                Qcur = ggml_rope_custom(
-                    ctx0, Qcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Qcur = ggml_rope_ext(
+                    ctx0, Qcur, inp_pos, nullptr, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, Kcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Kcur = ggml_rope_ext(
+                    ctx0, Kcur, inp_pos, nullptr, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Kcur, "Kcur", il);
@@ -9142,15 +9096,15 @@ struct llm_build_context {
                 Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
                 cb(Vcur, "Vcur", il);
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -9256,15 +9210,15 @@ struct llm_build_context {
                 Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);
                 cb(Vcur, "Vcur", il);
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -9409,8 +9363,8 @@ struct llm_build_context {
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens);
                 Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
 
-                Qcur = ggml_rope_custom(
-                    ctx0, Qcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Qcur = ggml_rope_ext(
+                    ctx0, Qcur, inp_pos, nullptr, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
@@ -9420,8 +9374,8 @@ struct llm_build_context {
                 Qcur = ggml_scale(ctx0, Qcur, 1.0f/sqrtf(float(n_embd_head)));
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, Kcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Kcur = ggml_rope_ext(
+                    ctx0, Kcur, inp_pos, nullptr, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Kcur, "Kcur", il);
@@ -9497,6 +9451,9 @@ struct llm_build_context {
 
             // self-attention
             {
+                // rope freq factors for 128k context
+                struct ggml_tensor * rope_factors = build_rope_factors(il);
+
                 struct ggml_tensor* attn_norm_output = llm_build_norm(ctx0, inpL, hparams,
                     model.layers[il].attn_norm,
                     NULL,
@@ -9528,8 +9485,8 @@ struct llm_build_context {
                 Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens);
                 Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
 
-                Qcur = ggml_rope_custom(
-                    ctx0, Qcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Qcur = ggml_rope_ext(
+                    ctx0, Qcur, inp_pos, rope_factors, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
@@ -9537,8 +9494,8 @@ struct llm_build_context {
                 Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head)));
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, Kcur, inp_pos, n_rot, rope_type, 0, n_orig_ctx,
+                Kcur = ggml_rope_ext(
+                    ctx0, Kcur, inp_pos, rope_factors, n_rot, rope_type, 0, n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Kcur, "Kcur", il);
@@ -9644,14 +9601,14 @@ struct llm_build_context {
                 struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
-                Qcur = ggml_rope_custom(
-                        ctx0, ggml_reshape_3d(ctx0, Qcur, n_rot, n_head,    n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                        ctx0, ggml_reshape_3d(ctx0, Qcur, n_rot, n_head,    n_tokens), inp_pos, nullptr,
                         n_embd_head, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                        ctx0, ggml_reshape_3d(ctx0, Kcur, n_rot, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                        ctx0, ggml_reshape_3d(ctx0, Kcur, n_rot, n_head_kv, n_tokens), inp_pos, nullptr,
                         n_embd_head, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Kcur, "Kcur", il);
@@ -9852,15 +9809,15 @@ struct llm_build_context {
                 cb(tmpk, "tmpk", il);
                 cb(Vcur, "Vcur", il);
 
-                struct ggml_tensor * Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, tmpq, n_embd_head, n_head,    n_tokens), inp_pos,
+                struct ggml_tensor * Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, tmpq, n_embd_head, n_head,    n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                struct ggml_tensor * Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, tmpk, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                struct ggml_tensor * Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, tmpk, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -9968,15 +9925,15 @@ struct llm_build_context {
                 //     cb(Vcur, "Vcur", il);
                 // }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -10085,15 +10042,15 @@ struct llm_build_context {
                     cb(Vcur, "Vcur", il);
                 }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -10215,15 +10172,15 @@ struct llm_build_context {
                     cb(Vcur, "Vcur", il);
                 }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -10335,8 +10292,8 @@ struct llm_build_context {
                 struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
                 cb(Vcur, "Vcur", il);
 
-                Qcur = ggml_rope_custom(
-                        ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head,    n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                        ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head,    n_tokens), inp_pos, nullptr,
                         n_embd_head_k, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Qcur, "Qcur", il);
@@ -10344,8 +10301,8 @@ struct llm_build_context {
                 Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head_k)));
                 cb(Qcur, "Qcur_scaled", il);
 
-                Kcur = ggml_rope_custom(
-                        ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                        ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos, nullptr,
                         n_embd_head_k, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                         ext_factor, attn_factor, beta_fast, beta_slow);
                 cb(Kcur, "Kcur", il);
@@ -10455,15 +10412,15 @@ struct llm_build_context {
                     cb(Vcur, "Vcur", il);
                 }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -10745,15 +10702,15 @@ struct llm_build_context {
                     cb(Kcur, "Kcur", il);
                 }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -10876,15 +10833,15 @@ struct llm_build_context {
                     cb(Vcur, "Vcur", il);
                 }
 
-                Qcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
                 cb(Qcur, "Qcur", il);
 
-                Kcur = ggml_rope_custom(
-                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -10949,6 +10906,275 @@ struct llm_build_context {
         return gf;
     }
 
+    struct ggml_cgraph * build_gptneox() {
+        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+        const int64_t n_embd_head = hparams.n_embd_head_v;
+        const int64_t n_embd_gqa  = hparams.n_embd_v_gqa();
+        GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
+
+        struct ggml_tensor * cur;
+        struct ggml_tensor * inpL;
+
+        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+        // inp_pos - contains the positions
+        struct ggml_tensor * inp_pos = build_inp_pos();
+
+        // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+        for (int il = 0; il < n_layer; ++il) {
+            cur = llm_build_norm(ctx0, inpL, hparams,
+                    model.layers[il].attn_norm,
+                    model.layers[il].attn_norm_b,
+                    LLM_NORM, cb, il);
+            cb(cur, "attn_norm", il);
+
+            // self-attention
+            {
+                cur = ggml_mul_mat(ctx0, model.layers[il].wqkv, cur);
+                cb(cur, "wqkv", il);
+
+                cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
+                cb(cur, "bqkv", il);
+
+                struct ggml_tensor * Qcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd,     n_tokens, cur->nb[1], 0*sizeof(float)*(n_embd)));
+                struct ggml_tensor * Kcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*sizeof(float)*(n_embd)));
+                struct ggml_tensor * Vcur = ggml_cont(ctx0, ggml_view_2d(ctx0, cur, n_embd_gqa, n_tokens, cur->nb[1], 1*sizeof(float)*(n_embd + n_embd_gqa)));
+
+                cb(Qcur, "Qcur", il);
+                cb(Kcur, "Kcur", il);
+                cb(Vcur, "Vcur", il);
+
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
+                    n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Qcur, "Qcur", il);
+
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
+                    n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Kcur, "Kcur", il);
+
+                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                        model.layers[il].wo, model.layers[il].bo,
+                        Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
+            }
+
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);
+                inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);
+            }
+
+            // ffn
+            if (hparams.use_par_res) {
+                // attention and ffn are computed in parallel
+                // x = x + attn(ln1(x)) + ffn(ln2(x))
+
+                struct ggml_tensor * attn_out = cur;
+
+                cur = llm_build_norm(ctx0, inpL, hparams,
+                        model.layers[il].ffn_norm,
+                        model.layers[il].ffn_norm_b,
+                        LLM_NORM, cb, il);
+                cb(cur, "ffn_norm", il);
+
+                cur = llm_build_ffn(ctx0, cur,
+                        model.layers[il].ffn_up,   model.layers[il].ffn_up_b,
+                        NULL,                      NULL,
+                        model.layers[il].ffn_down, model.layers[il].ffn_down_b,
+                        NULL,
+                        LLM_FFN_GELU, LLM_FFN_SEQ, cb, il);
+                cb(cur, "ffn_out", il);
+
+                cur = ggml_add(ctx0, cur, inpL);
+                cb(cur, "ffn_out", il);
+
+                inpL = ggml_add(ctx0, cur, attn_out);
+                cb(inpL, "l_out", il);
+            } else {
+                // attention and ffn are computed sequentially
+                // x = x + attn(ln1(x))
+                // x = x + ffn(ln2(x))
+
+                struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);
+                cb(ffn_inp, "ffn_inp", il);
+
+                cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                        model.layers[il].ffn_norm,
+                        model.layers[il].ffn_norm_b,
+                        LLM_NORM, cb, il);
+                cb(cur, "ffn_norm", il);
+
+                cur = llm_build_ffn(ctx0, cur,
+                        model.layers[il].ffn_up,   model.layers[il].ffn_up_b,
+                        NULL,                      NULL,
+                        model.layers[il].ffn_down, model.layers[il].ffn_down_b,
+                        NULL,
+                        LLM_FFN_GELU, LLM_FFN_SEQ, cb, il);
+                cb(cur, "ffn_out", il);
+
+                inpL = ggml_add(ctx0, cur, ffn_inp);
+                cb(inpL, "l_out", il);
+            }
+        }
+
+        cur = llm_build_norm(ctx0, inpL, hparams,
+                model.output_norm,
+                model.output_norm_b,
+                LLM_NORM, cb, -1);
+        cb(cur, "result_norm", -1);
+
+        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cb(cur, "result_output", -1);
+
+        ggml_build_forward_expand(gf, cur);
+
+        return gf;
+    }
+
+    struct ggml_cgraph * build_arctic() {
+        struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+        // mutable variable, needed during the last layer of the computation to skip unused tokens
+        int32_t n_tokens = this->n_tokens;
+
+        const int64_t n_embd_head = hparams.n_embd_head_v;
+        GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
+        GGML_ASSERT(n_embd_head == hparams.n_rot);
+
+        struct ggml_tensor * cur;
+        struct ggml_tensor * inpL;
+
+        inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+        // inp_pos - contains the positions
+        struct ggml_tensor * inp_pos = build_inp_pos();
+
+        // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+        struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+        for (int il = 0; il < n_layer; ++il) {
+            struct ggml_tensor * inpSA = inpL;
+
+            // norm
+            cur = llm_build_norm(ctx0, inpL, hparams,
+                    model.layers[il].attn_norm, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "attn_norm", il);
+
+            // self-attention
+            {
+                // compute Q and K and RoPE them
+                struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+                cb(Qcur, "Qcur", il);
+
+                struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+                cb(Kcur, "Kcur", il);
+
+                struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+                cb(Vcur, "Vcur", il);
+
+                Qcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, nullptr,
+                    n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Qcur, "Qcur", il);
+
+                Kcur = ggml_rope_ext(
+                    ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, nullptr,
+                    n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
+                    ext_factor, attn_factor, beta_fast, beta_slow
+                );
+                cb(Kcur, "Kcur", il);
+
+                cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+                        model.layers[il].wo, NULL,
+                        Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f/sqrtf(float(n_embd_head)), cb, il);
+            }
+
+            if (il == n_layer - 1) {
+                // skip computing output for unused tokens
+                struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+                n_tokens = n_outputs;
+                cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);
+                inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
+            }
+
+            struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
+            cb(ffn_inp, "ffn_inp", il);
+
+            // feed-forward network
+            cur = llm_build_norm(ctx0, ffn_inp, hparams,
+                    model.layers[il].ffn_norm, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "ffn_norm", il);
+
+            cur = llm_build_ffn(ctx0, cur,
+                    model.layers[il].ffn_up,   NULL,
+                    model.layers[il].ffn_gate, NULL,
+                    model.layers[il].ffn_down, NULL,
+                    NULL,
+                    LLM_FFN_SILU, LLM_FFN_PAR, cb, il);
+            cb(cur, "ffn_out", il);
+
+            struct ggml_tensor * ffn_out = ggml_add(ctx0, cur, ffn_inp);
+            cb(ffn_out, "ffn_out", il);
+
+            // MoE
+            cur = llm_build_norm(ctx0, inpSA, hparams,
+                    model.layers[il].ffn_norm_exps, NULL,
+                    LLM_NORM_RMS, cb, il);
+            cb(cur, "ffn_norm_exps", il);
+
+            cur = llm_build_moe_ffn(ctx0, cur,
+                    model.layers[il].ffn_gate_inp,
+                    model.layers[il].ffn_up_exps,
+                    model.layers[il].ffn_gate_exps,
+                    model.layers[il].ffn_down_exps,
+                    n_expert, n_expert_used,
+                    LLM_FFN_SILU, true,
+                    true, hparams.expert_weights_scale,
+                    cb, il);
+            cb(cur, "ffn_moe_out", il);
+
+            cur = ggml_add(ctx0, cur, ffn_out);
+            cb(cur, "ffn_out", il);
+
+            ggml_tensor * layer_dir = lctx.cvec.tensor_for(il);
+            if (layer_dir != nullptr) {
+                cur = ggml_add(ctx0, cur, layer_dir);
+            }
+            cb(cur, "l_out", il);
+
+            // input for next layer
+            inpL = cur;
+        }
+
+        cur = inpL;
+
+        cur = llm_build_norm(ctx0, cur, hparams,
+                model.output_norm, NULL,
+                LLM_NORM_RMS, cb, -1);
+        cb(cur, "result_norm", -1);
+
+        // lm_head
+        cur = ggml_mul_mat(ctx0, model.output, cur);
+        cb(cur, "result_output", -1);
+
+        ggml_build_forward_expand(gf, cur);
+
+        return gf;
+    }
+
     struct ggml_cgraph * build_deepseek2() {
         struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
 
@@ -11051,16 +11277,16 @@ struct llm_build_context {
                 value_states = ggml_view_2d(ctx0, value_states, hparams.n_embd_head_v * n_head, n_tokens, ggml_element_size(kv) * hparams.n_embd_head_v * n_head, 0);
                 cb(value_states, "value_states", il);
 
-                q_pe = ggml_rope_custom(
-                    ctx0, q_pe, inp_pos,
+                q_pe = ggml_rope_ext(
+                    ctx0, q_pe, inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor_scaled, beta_fast, beta_slow
                 );
                 cb(q_pe, "q_pe", il);
 
                 // shared RoPE key
-                k_pe = ggml_rope_custom(
-                    ctx0, ggml_view_3d(ctx0, k_pe, qk_rope_head_dim, 1, n_tokens, k_pe->nb[0], k_pe->nb[1], 0), inp_pos,
+                k_pe = ggml_rope_ext(
+                    ctx0, ggml_view_3d(ctx0, k_pe, qk_rope_head_dim, 1, n_tokens, k_pe->nb[0], k_pe->nb[1], 0), inp_pos, nullptr,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor_scaled, beta_fast, beta_slow
                 );
@@ -11164,6 +11390,7 @@ struct llm_build_context {
 
         return gf;
     }
+
 };
 
 static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const std::vector<uint32_t> & ids) {
@@ -11280,10 +11507,6 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_starcoder();
             } break;
-        case LLM_ARCH_PERSIMMON:
-            {
-                result = llm.build_persimmon();
-            } break;
         case LLM_ARCH_REFACT:
             {
                 result = llm.build_refact();
@@ -11378,6 +11601,14 @@ static struct ggml_cgraph * llama_build_graph(
             {
                 result = llm.build_olmo();
             } break;
+        case LLM_ARCH_GPTNEOX:
+            {
+                result = llm.build_gptneox();
+            } break;
+        case LLM_ARCH_ARCTIC:
+            {
+                result = llm.build_arctic();
+            } break;
         case LLM_ARCH_DEEPSEEK2:
             {
                 result = llm.build_deepseek2();
@@ -11727,11 +11958,6 @@ static void llama_graph_compute(
         llama_context & lctx,
           ggml_cgraph * gf,
                   int   n_threads) {
-#ifdef GGML_USE_MPI
-    const int64_t n_layer = lctx.model.hparams.n_layer;
-    ggml_mpi_graph_compute_pre(lctx.ctx_mpi, gf, n_layer);
-#endif
-
 #ifdef GGML_USE_METAL
     if (ggml_backend_is_metal(lctx.backend_metal)) {
         ggml_backend_metal_set_n_cb(lctx.backend_metal, n_threads);
@@ -11746,10 +11972,6 @@ static void llama_graph_compute(
     ggml_backend_sched_graph_compute_async(lctx.sched, gf);
 
     // fprintf(stderr, "splits: %d\n", ggml_backend_sched_get_n_splits(lctx.sched));
-
-#ifdef GGML_USE_MPI
-    ggml_mpi_graph_compute_post(lctx.ctx_mpi, gf, n_layer);
-#endif
 }
 
 // decode a batch of tokens by evaluating the transformer
@@ -11787,12 +12009,6 @@ static int llama_decode_internal(
     }
     lctx.n_queued_tokens += n_tokens_all;
 
-#ifdef GGML_USE_MPI
-    // TODO: needs fix after #3228
-    GGML_ASSERT(false && "not implemented");
-    //ggml_mpi_eval_init(lctx.ctx_mpi, &n_tokens, &n_past, &n_threads);
-#endif
-
     auto & kv_self = lctx.kv_self;
 
     const int64_t n_embd  = hparams.n_embd;
@@ -12742,6 +12958,7 @@ struct llm_tokenizer_bpe {
                             "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
                         });
                         break;
+                    case LLAMA_VOCAB_PRE_TYPE_STABLELM2:
                     case LLAMA_VOCAB_PRE_TYPE_QWEN2:
                         word_collection = unicode_regex_split(text, {
                             // original regex from tokenizer.json
@@ -12964,16 +13181,16 @@ struct llm_tokenizer_wpm {
         // to lowercase, pad chinese characters, pad punctuation
         std::string new_str = "";
         for (uint32_t code : cpts_nfd) {
-            int type = unicode_cpt_type(code);
-            if (type == CODEPOINT_TYPE_ACCENT_MARK || type == CODEPOINT_TYPE_CONTROL) {
+            const codepoint_flags flags = unicode_cpt_flags(code);
+            if (flags.is_accent_mark || flags.is_control) {
                 continue;
             }
             code = unicode_tolower(code);
-            if (type == CODEPOINT_TYPE_SEPARATOR) {
+            if (flags.is_separator || flags.is_whitespace) {  //####FIXME: is_separator ?
                 code = ' ';
             }
             std::string s = unicode_cpt_to_utf8(code);
-            if (type == CODEPOINT_TYPE_PUNCTUATION || is_ascii_punct(code) || is_chinese_char(code)) {
+            if (flags.is_punctuation || is_ascii_punct(code) || is_chinese_char(code)) {
                 new_str += " ";
                 new_str += s;
                 new_str += " ";
@@ -13176,9 +13393,14 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
                 // tokenizer.encode('', add_special_tokens=True)  returns [1]
                 // tokenizer.encode('', add_special_tokens=False) returns []
 
+                static const bool rtrim = true;  //TODO: as param
+                bool is_prev_special = false;
+                bool special_token_rtrim = false;
+
                 if (add_special && vocab.special_add_bos != 0) {
                     GGML_ASSERT(vocab.special_bos_id != -1);
                     output.push_back(vocab.special_bos_id);
+                    is_prev_special = true;
                 }
 
                 for (const auto & fragment : fragment_buffer) {
@@ -13190,9 +13412,21 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
                         //  and passing 'add space prefix' as bool argument
                         //
                         auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length);
-                        if (&fragment == &fragment_buffer.front()) {
-                            if (vocab.add_space_prefix) {
-                                raw_text = " " + raw_text; // prefix with space if the first token is not special
+
+                        if (special_token_rtrim) {
+                            size_t num_whitespaces = 0;
+                            while (isspace(raw_text[num_whitespaces])) {
+                                num_whitespaces++;
+                            }
+                            if (num_whitespaces == raw_text.size()) {
+                                continue; // skip if all whitespaces
+                            }
+                            raw_text = raw_text.substr(num_whitespaces);
+                        }
+
+                        if (vocab.add_space_prefix) {
+                            if (!output.size() || is_prev_special) {  // prefix with space if first token
+                                raw_text = " " + raw_text;
                             }
                         }
 
@@ -13204,6 +13438,12 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
                         tokenizer.tokenize(raw_text, output);
                     } else { // if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN)
                         output.push_back(fragment.token);
+                        is_prev_special = true;
+                        // phi-3 special tokens without rtrim, works fine for llama-spm too
+                        special_token_rtrim = rtrim
+                            && fragment.token != vocab.special_bos_id
+                            && fragment.token != vocab.special_unk_id
+                            && fragment.token != vocab.special_eos_id;
                     }
                 }
 
@@ -14906,8 +15146,6 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
         else if ((ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) &&
                 use_more_bits(qs.i_attention_wv, qs.n_attention_wv)) new_type = GGML_TYPE_Q6_K;
         else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S && qs.i_attention_wv < 4) new_type = GGML_TYPE_Q5_K;
-        else if (QK_K == 64 && (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_S) &&
-                (qs.i_attention_wv < qs.n_attention_wv/8 || qs.i_attention_wv >= 7*qs.n_attention_wv/8)) new_type = GGML_TYPE_Q6_K;
         if (qs.model.type == MODEL_70B) {
             // In the 70B model we have 8 heads sharing the same attn_v weights. As a result, the attn_v.weight tensor is
             // 8x smaller compared to attn_q.weight. Hence, we can get a nice boost in quantization accuracy with
@@ -15921,10 +16159,6 @@ void llama_backend_init(void) {
         struct ggml_context * ctx = ggml_init(params);
         ggml_free(ctx);
     }
-
-#ifdef GGML_USE_MPI
-    ggml_mpi_backend_init();
-#endif
 }
 
 void llama_numa_init(enum ggml_numa_strategy numa) {
@@ -15934,9 +16168,6 @@ void llama_numa_init(enum ggml_numa_strategy numa) {
 }
 
 void llama_backend_free(void) {
-#ifdef GGML_USE_MPI
-    ggml_mpi_backend_free();
-#endif
     ggml_quantize_free();
 }
 
@@ -16079,6 +16310,7 @@ struct llama_context * llama_new_context_with_model(
         cparams.yarn_ext_factor = rope_scaling_type == LLAMA_ROPE_SCALING_TYPE_YARN ? 1.0f : 0.0f;
     }
 
+    cparams.yarn_attn_factor *= hparams.rope_attn_factor;
     cparams.causal_attn = hparams.causal_attn;
 
     if (cparams.pooling_type == LLAMA_POOLING_TYPE_UNSPECIFIED) {
@@ -16337,20 +16569,6 @@ struct llama_context * llama_new_context_with_model(
         }
     }
 
-#ifdef GGML_USE_MPI
-    ctx->ctx_mpi = ggml_mpi_init();
-
-    if (ggml_mpi_rank(ctx->ctx_mpi) > 0) {
-        // Enter a blocking eval loop with dummy input, letting rank=0 drive the process
-        // TODO: needs fix after #3228
-        GGML_ASSERT(false && "not implemented");
-        //const std::vector<llama_token> tmp(ctx->model.hparams.n_ctx, llama_token_bos(ctx));
-        //while (!llama_eval(ctx, tmp.data(), tmp.size(), 0, 0)) {};
-        llama_backend_free();
-        exit(1);
-    }
-#endif
-
     return ctx;
 }
 
@@ -16387,7 +16605,6 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         // these models do not use RoPE
         case LLM_ARCH_GPT2:
         case LLM_ARCH_GPTJ:
-        case LLM_ARCH_GPTNEOX:
         case LLM_ARCH_MPT:
         case LLM_ARCH_REFACT:
         case LLM_ARCH_BLOOM:
@@ -16407,6 +16624,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_XVERSE:
         case LLM_ARCH_COMMAND_R:
         case LLM_ARCH_OLMO:
+        case LLM_ARCH_ARCTIC:
         case LLM_ARCH_DEEPSEEK2:
             return LLAMA_ROPE_TYPE_NORM;
 
@@ -16414,7 +16632,6 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_FALCON:
         case LLM_ARCH_GROK:
         case LLM_ARCH_DBRX:
-        case LLM_ARCH_PERSIMMON:
         case LLM_ARCH_BERT:
         case LLM_ARCH_NOMIC_BERT:
         case LLM_ARCH_STABLELM:
@@ -16425,6 +16642,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
         case LLM_ARCH_PHI3:
         case LLM_ARCH_GEMMA:
         case LLM_ARCH_STARCODER2:
+        case LLM_ARCH_GPTNEOX:
             return LLAMA_ROPE_TYPE_NEOX;
 
         // all model arches should be listed explicitly here
@@ -16584,6 +16802,7 @@ static bool llama_control_vector_init(struct llama_control_vector & cvec, const
     }
 
     // make tensors
+    cvec.tensors.reserve(model.hparams.n_layer);
     cvec.tensors.push_back(nullptr); // there's never a tensor for layer 0
     for (size_t il = 1; il < model.hparams.n_layer; il++) {
         struct ggml_context * ctx = ctx_map.at(model.buft_layer[il].buft);
@@ -16592,6 +16811,8 @@ static bool llama_control_vector_init(struct llama_control_vector & cvec, const
     }
 
     // allocate tensors / buffers and zero
+    cvec.ctxs.reserve(ctx_map.size());
+    cvec.bufs.reserve(ctx_map.size());
     for (auto it : ctx_map) {
         ggml_backend_buffer_type_t buft = it.first;
         ggml_context * ctx = it.second;
@@ -17800,6 +18021,14 @@ void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_
     ctx->cparams.n_threads_batch = n_threads_batch;
 }
 
+uint32_t llama_n_threads(struct llama_context * ctx) {
+    return ctx->cparams.n_threads;
+}
+
+uint32_t llama_n_threads_batch(struct llama_context * ctx) {
+    return ctx->cparams.n_threads_batch;
+}
+
 void llama_set_abort_callback(struct llama_context * ctx, bool (*abort_callback)(void * data), void * abort_callback_data) {
     ctx->abort_callback      = abort_callback;
     ctx->abort_callback_data = abort_callback_data;
@@ -18234,6 +18463,15 @@ static int32_t llama_chat_apply_template_internal(
             }
         }
         // llama2 templates seem to not care about "add_generation_prompt"
+    } else if (tmpl == "phi3" || (tmpl.find("<|assistant|>") != std::string::npos && tmpl.find("<|end|>") != std::string::npos)) {
+        // Phi 3
+        for (auto message : chat) {
+            std::string role(message->role);
+            ss << "<|" << role << "|>\n" << message->content << "<|end|>\n";
+        }
+        if (add_ass) {
+            ss << "<|assistant|>\n";
+        }
     } else if (tmpl == "zephyr" || tmpl.find("<|user|>") != std::string::npos) {
         // zephyr template
         for (auto message : chat) {
@@ -18366,15 +18604,6 @@ static int32_t llama_chat_apply_template_internal(
         if (add_ass) {
             ss << "<|start_header_id|>assistant<|end_header_id|>\n\n";
         }
-    } else if (tmpl == "phi3" || (tmpl.find("<|assistant|>") != std::string::npos && tmpl.find("<|end|>") != std::string::npos )) {
-        // Phi 3
-        for (auto message : chat) {
-            std::string role(message->role);
-            ss << "<|" << role << "|>\n" << trim(message->content) << "<|end|>\n";
-        }
-        if (add_ass) {
-            ss << "<|assistant|>\n";
-        }
     } else {
         // template not supported
         return -1;
@@ -18496,6 +18725,7 @@ const char * llama_print_system_info(void) {
     s += "AVX512 = "      + std::to_string(ggml_cpu_has_avx512())      + " | ";
     s += "AVX512_VBMI = " + std::to_string(ggml_cpu_has_avx512_vbmi()) + " | ";
     s += "AVX512_VNNI = " + std::to_string(ggml_cpu_has_avx512_vnni()) + " | ";
+    s += "AVX512_BF16 = " + std::to_string(ggml_cpu_has_avx512_bf16()) + " | ";
     s += "FMA = "         + std::to_string(ggml_cpu_has_fma())         + " | ";
     s += "NEON = "        + std::to_string(ggml_cpu_has_neon())        + " | ";
     s += "ARM_FMA = "     + std::to_string(ggml_cpu_has_arm_fma())     + " | ";
@@ -18556,6 +18786,8 @@ void llama_log_set(ggml_log_callback log_callback, void * user_data) {
     g_state.log_callback_user_data = user_data;
 #ifdef GGML_USE_METAL
     ggml_backend_metal_log_set_callback(g_state.log_callback, g_state.log_callback_user_data);
+#elif defined(GGML_USE_CUDA)
+    ggml_backend_cuda_log_set_callback(g_state.log_callback, g_state.log_callback_user_data);
 #endif
 }
 
diff --git a/llama.h b/llama.h
index 612e32c4e..16cece5db 100644
--- a/llama.h
+++ b/llama.h
@@ -81,9 +81,10 @@ extern "C" {
         LLAMA_VOCAB_PRE_TYPE_GPT2           = 7,
         LLAMA_VOCAB_PRE_TYPE_REFACT         = 8,
         LLAMA_VOCAB_PRE_TYPE_COMMAND_R      = 9,
-        LLAMA_VOCAB_PRE_TYPE_QWEN2          = 10,
-        LLAMA_VOCAB_PRE_TYPE_OLMO           = 11,
-        LLAMA_VOCAB_PRE_TYPE_DBRX           = 12,
+        LLAMA_VOCAB_PRE_TYPE_STABLELM2      = 10,
+        LLAMA_VOCAB_PRE_TYPE_QWEN2          = 11,
+        LLAMA_VOCAB_PRE_TYPE_OLMO           = 12,
+        LLAMA_VOCAB_PRE_TYPE_DBRX           = 13,
     };
 
     // note: these values should be synchronized with ggml_rope
@@ -758,6 +759,12 @@ extern "C" {
     // n_threads_batch is the number of threads used for prompt and batch processing (multiple tokens)
     LLAMA_API void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_t n_threads_batch);
 
+    // Get the number of threads used for generation of a single token.
+    LLAMA_API uint32_t llama_n_threads(struct llama_context * ctx);
+
+    // Get the number of threads used for prompt and batch processing (multiple token).
+    LLAMA_API uint32_t llama_n_threads_batch(struct llama_context * ctx);
+
     // Set whether to use causal attention or not
     // If set to true, the model will only attend to the past tokens
     LLAMA_API void llama_set_causal_attn(struct llama_context * ctx, bool causal_attn);
diff --git a/requirements.txt b/requirements.txt
index e7d14e16a..43f82dc2e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -9,4 +9,3 @@
 -r ./requirements/requirements-convert-hf-to-gguf.txt
 -r ./requirements/requirements-convert-hf-to-gguf-update.txt
 -r ./requirements/requirements-convert-llama-ggml-to-gguf.txt
--r ./requirements/requirements-convert-persimmon-to-gguf.txt
diff --git a/requirements/requirements-convert-persimmon-to-gguf.txt b/requirements/requirements-convert-persimmon-to-gguf.txt
deleted file mode 100644
index 6ac402610..000000000
--- a/requirements/requirements-convert-persimmon-to-gguf.txt
+++ /dev/null
@@ -1,2 +0,0 @@
--r ./requirements-convert.txt
-torch~=2.1.1
diff --git a/scripts/LlamaConfig.cmake.in b/scripts/LlamaConfig.cmake.in
index f842c7137..92e39708b 100644
--- a/scripts/LlamaConfig.cmake.in
+++ b/scripts/LlamaConfig.cmake.in
@@ -5,7 +5,6 @@ set(LLAMA_SHARED_LIB @BUILD_SHARED_LIBS@)
 set(LLAMA_BLAS @LLAMA_BLAS@)
 set(LLAMA_CUDA @LLAMA_CUDA@)
 set(LLAMA_METAL @LLAMA_METAL@)
-set(LLAMA_MPI @LLAMA_MPI@)
 set(LLAMA_CLBLAST @LLAMA_CLBLAST@)
 set(LLAMA_HIPBLAS @LLAMA_HIPBLAS@)
 set(LLAMA_ACCELERATE @LLAMA_ACCELERATE@)
@@ -37,10 +36,6 @@ if (LLAMA_METAL)
     find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
 endif()
 
-if (LLAMA_MPI)
-    find_package(MPI REQUIRED)
-endif()
-
 if (LLAMA_CLBLAST)
     find_package(CLBlast REQUIRED)
 endif()
diff --git a/scripts/gen-unicode-data.py b/scripts/gen-unicode-data.py
index 37d1e396c..744873c2a 100644
--- a/scripts/gen-unicode-data.py
+++ b/scripts/gen-unicode-data.py
@@ -1,64 +1,134 @@
 import regex
+import ctypes
+import unicodedata
 
 
-def get_matches(regex_expr):
-    regex_expr_compiled = regex.compile(regex_expr)
-    unicode_ranges = []
-    current_range = None
-
-    for codepoint in range(0x110000):
-        char = chr(codepoint)
-        if regex_expr_compiled.match(char):
-            if current_range is None:
-                current_range = [codepoint, codepoint]
-            else:
-                current_range[1] = codepoint
-        elif current_range is not None:
-            unicode_ranges.append(tuple(current_range))
-            current_range = None
-
-    if current_range is not None:
-        unicode_ranges.append(tuple(current_range))
-
-    return unicode_ranges
+class CoodepointFlags (ctypes.Structure):
+    _fields_ = [  # see definition in unicode.h
+        ("is_undefined",   ctypes.c_uint16, 1),
+        ("is_number",      ctypes.c_uint16, 1),  # regex: \p{N}
+        ("is_letter",      ctypes.c_uint16, 1),  # regex: \p{L}
+        ("is_separator",   ctypes.c_uint16, 1),  # regex: \p{Z}
+        ("is_accent_mark", ctypes.c_uint16, 1),  # regex: \p{M}
+        ("is_punctuation", ctypes.c_uint16, 1),  # regex: \p{P}
+        ("is_symbol",      ctypes.c_uint16, 1),  # regex: \p{S}
+        ("is_control",     ctypes.c_uint16, 1),  # regex: \p{C}
+    ]
 
 
-def print_cat(mode, cat, ranges):
-    if mode == "range":
-        print("const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_{} = {{".format(cat)) # noqa: NP100
-    if mode == "map":
-        print("const std::map<uint32_t, uint32_t> unicode_map_{} = {{".format(cat)) # noqa: NP100
-    for i, values in enumerate(ranges):
-        end = ",\n" if (i % 4 == 3 or i + 1 == len(ranges)) else ", "
-        values = ["0x%08X" % value for value in values]
-        print("{" + ", ".join(values) + "}", end=end) # noqa: NP100
-    print("};") # noqa: NP100
-    print("") # noqa: NP100
+assert (ctypes.sizeof(CoodepointFlags) == 2)
 
 
-print_cat("range", "number",      get_matches(r'\p{N}'))
-print_cat("range", "letter",      get_matches(r'\p{L}'))
-print_cat("range", "separator",   get_matches(r'\p{Z}'))
-print_cat("range", "accent_mark", get_matches(r'\p{M}'))
-print_cat("range", "punctuation", get_matches(r'\p{P}'))
-print_cat("range", "symbol",      get_matches(r'\p{S}'))
-print_cat("range", "control",     get_matches(r'\p{C}'))
+MAX_CODEPOINTS = 0x110000
 
-print_cat("range", "whitespace",  get_matches(r'\s'))
+regex_number      = regex.compile(r'\p{N}')
+regex_letter      = regex.compile(r'\p{L}')
+regex_separator   = regex.compile(r'\p{Z}')
+regex_accent_mark = regex.compile(r'\p{M}')
+regex_punctuation = regex.compile(r'\p{P}')
+regex_symbol      = regex.compile(r'\p{S}')
+regex_control     = regex.compile(r'\p{C}')
+regex_whitespace  = regex.compile(r'\s')
 
+codepoint_flags = (CoodepointFlags * MAX_CODEPOINTS)()
+table_whitespace = []
+table_lowercase = []
+table_uppercase = []
+table_nfd = []
 
-map_lowercase = []
-map_uppercase = []
-for codepoint in range(0x110000):
+for codepoint in range(MAX_CODEPOINTS):
+    # convert codepoint to unicode character
     char = chr(codepoint)
+
+    # regex categories
+    flags = codepoint_flags[codepoint]
+    flags.is_number      = bool(regex_number.match(char))
+    flags.is_letter      = bool(regex_letter.match(char))
+    flags.is_separator   = bool(regex_separator.match(char))
+    flags.is_accent_mark = bool(regex_accent_mark.match(char))
+    flags.is_punctuation = bool(regex_punctuation.match(char))
+    flags.is_symbol      = bool(regex_symbol.match(char))
+    flags.is_control     = bool(regex_control.match(char))
+    flags.is_undefined   = bytes(flags)[0] == 0
+    assert (not flags.is_undefined)
+
+    # whitespaces
+    if bool(regex_whitespace.match(char)):
+        table_whitespace.append(codepoint)
+
+    # lowercase conversion
     lower = ord(char.lower()[0])
-    upper = ord(char.upper()[0])
     if codepoint != lower:
-        map_lowercase.append((codepoint, lower))
+        table_lowercase.append((codepoint, lower))
+
+    # uppercase conversion
+    upper = ord(char.upper()[0])
     if codepoint != upper:
-        map_uppercase.append((codepoint, upper))
-print_cat("map", "lowercase", map_lowercase)
-print_cat("map", "uppercase", map_uppercase)
+        table_uppercase.append((codepoint, upper))
+
+    # NFD normalization
+    norm = ord(unicodedata.normalize('NFD', char)[0])
+    if codepoint != norm:
+        table_nfd.append((codepoint, norm))
 
 
-# TODO: generate unicode_map_nfd
+# group ranges with same flags
+ranges_flags = [(0, codepoint_flags[0])]  # start, flags
+for codepoint, flags in enumerate(codepoint_flags):
+    if bytes(flags) != bytes(ranges_flags[-1][1]):
+        ranges_flags.append((codepoint, flags))
+ranges_flags.append((MAX_CODEPOINTS, CoodepointFlags()))
+
+
+# group ranges with same nfd
+ranges_nfd = [(0, 0, 0)]  # start, last, nfd
+for codepoint, norm in table_nfd:
+    start = ranges_nfd[-1][0]
+    if ranges_nfd[-1] != (start, codepoint - 1, norm):
+        ranges_nfd.append(None)
+        start = codepoint
+    ranges_nfd[-1] = (start, codepoint, norm)
+
+
+# Generate 'unicode-data.cpp'
+
+
+def out(line=""):
+    print(line, end='\n')  # noqa
+
+
+out("""\
+// generated with scripts/gen-unicode-data.py
+
+#include "unicode-data.h"
+
+#include <cstdint>
+#include <vector>
+#include <unordered_map>
+#include <unordered_set>
+""")
+
+out("const std::vector<std::pair<uint32_t, uint16_t>> unicode_ranges_flags = {  // start, flags // last=next_start-1")
+for codepoint, flags in ranges_flags:
+    flags = int.from_bytes(bytes(flags), "little")
+    out("{0x%06X, 0x%04X}," % (codepoint, flags))
+out("};\n")
+
+out("const std::unordered_set<uint32_t> unicode_set_whitespace = {")
+out(", ".join("0x%06X" % cpt for cpt in table_whitespace))
+out("};\n")
+
+out("const std::unordered_map<uint32_t, uint32_t> unicode_map_lowercase = {")
+for tuple in table_lowercase:
+    out("{0x%06X, 0x%06X}," % tuple)
+out("};\n")
+
+out("const std::unordered_map<uint32_t, uint32_t> unicode_map_uppercase = {")
+for tuple in table_uppercase:
+    out("{0x%06X, 0x%06X}," % tuple)
+out("};\n")
+
+out("const std::vector<range_nfd> unicode_ranges_nfd = {  // start, last, nfd")
+for triple in ranges_nfd:
+    out("{0x%06X, 0x%06X, 0x%06X}," % triple)
+out("};\n")
diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp
index 85ef21c2a..de74585da 100644
--- a/tests/test-backend-ops.cpp
+++ b/tests/test-backend-ops.cpp
@@ -16,6 +16,7 @@
 #include <thread>
 #include <vector>
 
+
 static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float max = 1.0f) {
     // static RNG initialization (revisit if n_threads stops being constant)
     static const size_t n_threads = std::thread::hardware_concurrency();
@@ -49,6 +50,22 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m
         t.join();
     }
 
+#if 0
+    const char * val_str = getenv("GGML_TEST_EPS");
+    float val = 1e-9f;
+    if (val_str != nullptr) {
+        val = std::stof(val_str);
+        printf("GGML_TEST_EPS=%e\n", val);
+    }
+
+    // test quantization with very small values that may result in nan scales due to division by zero
+    if (ggml_is_quantized(tensor->type)) {
+        for (int i = 0; i < 256; i++) {
+            data[i] = val;
+        }
+    }
+#endif
+
     if (tensor->type == GGML_TYPE_F32 || tensor->type == GGML_TYPE_I32) {
         ggml_backend_tensor_set(tensor, data.data(), 0, size * sizeof(float));
     } else if (ggml_is_quantized(tensor->type) || tensor->type == GGML_TYPE_F16 || tensor->type == GGML_TYPE_BF16) {
@@ -64,6 +81,7 @@ static void init_tensor_uniform(ggml_tensor * tensor, float min = -1.0f, float m
             }
         }
         ggml_quantize_chunk(tensor->type, data.data(), dataq.data(), 0, size/tensor->ne[0], tensor->ne[0], im);
+        GGML_ASSERT(ggml_validate_row_data(tensor->type, dataq.data(), dataq.size()));
         ggml_backend_tensor_set(tensor, dataq.data(), 0, dataq.size());
     } else if (tensor->type == GGML_TYPE_I8 || tensor->type == GGML_TYPE_I16 || tensor->type == GGML_TYPE_I32) {
         // This is going to create some weird integers though.
@@ -1124,20 +1142,22 @@ struct test_rope : public test_case {
     int n_dims;
     int mode;
     int n_ctx;
+    bool ff;
 
     std::string vars() override {
-        return VARS_TO_STR5(type, ne, n_dims, mode, n_ctx);
+        return VARS_TO_STR6(type, ne, n_dims, mode, n_ctx, ff);
     }
 
     test_rope(ggml_type type = GGML_TYPE_F32,
             std::array<int64_t, 4> ne = {10, 10, 10, 1},
-            int n_dims = 10, int mode = 0, int n_ctx = 512)
-        : type(type), ne(ne), n_dims(n_dims), mode(mode), n_ctx(n_ctx) {}
+            int n_dims = 10, int mode = 0, int n_ctx = 512, bool ff = false)
+        : type(type), ne(ne), n_dims(n_dims), mode(mode), n_ctx(n_ctx), ff(ff) {}
 
     ggml_tensor * build_graph(ggml_context * ctx) override {
         ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne.data());
         ggml_tensor * pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne[2]);
-        ggml_tensor * out = ggml_rope(ctx, a, pos, n_dims, mode, n_ctx);
+        ggml_tensor * freq = ff ? ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_dims/2) : nullptr;
+        ggml_tensor * out = ggml_rope_ext(ctx, a, pos, freq, n_dims, mode, n_ctx, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f);
         return out;
     }
 
@@ -1151,7 +1171,12 @@ struct test_rope : public test_case {
                 }
                 ggml_backend_tensor_set(t, data.data(), 0, ne[2] * sizeof(int));
             } else {
-                init_tensor_uniform(t);
+                if (t->ne[0] == n_dims/2) {
+                    // frequency factors in the range [0.9f, 1.1f]
+                    init_tensor_uniform(t, 0.9f, 1.1f);
+                } else {
+                    init_tensor_uniform(t);
+                }
             }
         }
     }
@@ -1745,14 +1770,14 @@ struct test_llama : public test_llm {
                 struct ggml_tensor * Kcur = ggml_mul_mat(ctx, wk, cur);
                 struct ggml_tensor * Vcur = ggml_mul_mat(ctx, wv, cur);
 
-                Qcur = ggml_rope_custom(
-                    ctx, ggml_reshape_3d(ctx, Qcur, hp.n_embd_head, hp.n_head,    hp.n_tokens), inp_pos,
+                Qcur = ggml_rope_ext(
+                    ctx, ggml_reshape_3d(ctx, Qcur, hp.n_embd_head, hp.n_head,    hp.n_tokens), inp_pos, nullptr,
                     hp.n_rot, 0, 0, hp.n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
 
-                Kcur = ggml_rope_custom(
-                    ctx, ggml_reshape_3d(ctx, Kcur, hp.n_embd_head, hp.n_head_kv, hp.n_tokens), inp_pos,
+                Kcur = ggml_rope_ext(
+                    ctx, ggml_reshape_3d(ctx, Kcur, hp.n_embd_head, hp.n_head_kv, hp.n_tokens), inp_pos, nullptr,
                     hp.n_rot, 0, 0, hp.n_orig_ctx, freq_base, freq_scale,
                     ext_factor, attn_factor, beta_fast, beta_slow
                 );
@@ -1871,13 +1896,13 @@ struct test_falcon : public test_llm {
                 Kcur = ggml_reshape_3d(ctx, Kcur, hp.n_embd_head, hp.n_head_kv, hp.n_tokens);
 
                 // using mode = 2 for neox mode
-                Qcur = ggml_rope_custom(
-                    ctx, Qcur, inp_pos, hp.n_rot, 2, 0, hp.n_orig_ctx,
+                Qcur = ggml_rope_ext(
+                    ctx, Qcur, inp_pos, nullptr, hp.n_rot, 2, 0, hp.n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
 
-                Kcur = ggml_rope_custom(
-                    ctx, Kcur, inp_pos, hp.n_rot, 2, 0, hp.n_orig_ctx,
+                Kcur = ggml_rope_ext(
+                    ctx, Kcur, inp_pos, nullptr, hp.n_rot, 2, 0, hp.n_orig_ctx,
                     freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow
                 );
 
@@ -2170,16 +2195,20 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op
     test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true,  0.1f, 8.0f));
 
     for (ggml_type type : {GGML_TYPE_F32, GGML_TYPE_F16}) {
-        test_cases.emplace_back(new test_rope(type, {128,  32, 10, 1}, 128, 0, 512)); // llama 7B
-        test_cases.emplace_back(new test_rope(type, {128,  40, 10, 1}, 128, 0, 512)); // llama 13B
-        test_cases.emplace_back(new test_rope(type, {128,  52, 10, 1}, 128, 0, 512)); // llama 30B
-        test_cases.emplace_back(new test_rope(type, {128,  64, 10, 1}, 128, 0, 512)); // llama 65B
-        test_cases.emplace_back(new test_rope(type, { 64,   1, 10, 1},  64, 2, 512)); // neox (falcon 7B)
-        test_cases.emplace_back(new test_rope(type, { 64,  71, 10, 1},  64, 2, 512)); // neox (falcon 7B)
-        test_cases.emplace_back(new test_rope(type, { 64,   8, 10, 1},  64, 2, 512)); // neox (falcon 40B)
-        test_cases.emplace_back(new test_rope(type, { 64, 128, 10, 1},  64, 2, 512)); // neox (falcon 40B)
-        test_cases.emplace_back(new test_rope(type, { 80,  32, 10, 1},  20, 2, 512)); // neox (stablelm)
-        test_cases.emplace_back(new test_rope(type, { 80,  32, 10, 1},  32, 2, 512)); // neox (phi-2)
+        // TODO: ff not supported yet for !neox
+        test_cases.emplace_back(new test_rope(type, {128,  32, 10, 1}, 128, 0, 512, false)); // llama 7B
+        test_cases.emplace_back(new test_rope(type, {128,  40, 10, 1}, 128, 0, 512, false)); // llama 13B
+        test_cases.emplace_back(new test_rope(type, {128,  52, 10, 1}, 128, 0, 512, false)); // llama 30B
+        test_cases.emplace_back(new test_rope(type, {128,  64, 10, 1}, 128, 0, 512, false)); // llama 65B
+
+        for (bool ff : {false, true}) { // freq_factors
+            test_cases.emplace_back(new test_rope(type, { 64,   1, 10, 1},  64, 2, 512, ff)); // neox (falcon 7B)
+            test_cases.emplace_back(new test_rope(type, { 64,  71, 10, 1},  64, 2, 512, ff)); // neox (falcon 7B)
+            test_cases.emplace_back(new test_rope(type, { 64,   8, 10, 1},  64, 2, 512, ff)); // neox (falcon 40B)
+            test_cases.emplace_back(new test_rope(type, { 64, 128, 10, 1},  64, 2, 512, ff)); // neox (falcon 40B)
+            test_cases.emplace_back(new test_rope(type, { 80,  32, 10, 1},  20, 2, 512, ff)); // neox (stablelm)
+            test_cases.emplace_back(new test_rope(type, { 80,  32, 10, 1},  32, 2, 512, ff)); // neox (phi-2)
+        }
     }
 
     test_cases.emplace_back(new test_concat(GGML_TYPE_F32));
diff --git a/tests/test-chat-template.cpp b/tests/test-chat-template.cpp
index 4fe9183b9..cef9a650b 100644
--- a/tests/test-chat-template.cpp
+++ b/tests/test-chat-template.cpp
@@ -49,8 +49,14 @@ int main(void) {
         "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true %}{% set loop_messages = messages %}{% set system_message = 'You are Command-R, a brilliant, sophisticated, AI-assistant trained to assist human users by providing thorough responses. You are trained by Cohere.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% if system_message != false %}{{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% elif message['role'] == 'assistant' %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'  + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}{% endif %}",
         // Llama-3
         "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}",
-        // Phi-3
-        "{{ bos_token }}{% for message in messages %}{{'<|' + message['role'] + '|>' + ' ' + message['content'] + '<|end|> ' }}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|> ' }}{% else %}{{ eos_token }}{% endif %}"
+        //Phi-3-mini
+        "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %}",
+        //Phi-3-small
+        "{{ bos_token }}{% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '<|end|>\n' }}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}",
+        //Phi-3-medium
+        "{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %}",
+        //Phi-3-vision
+        "{% for message in messages %}{{'<|' + message['role'] + '|>' + '\n' + message['content'] + '<|end|>\n' }}{% endfor %}{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{- '<|assistant|>\n' -}}{% endif %}"
     };
     std::vector<std::string> expected_output = {
         // teknium/OpenHermes-2.5-Mistral-7B
@@ -79,8 +85,14 @@ int main(void) {
         "<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>You are a helpful assistant<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>Hi there<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Who are you<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>I am an assistant<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Another question<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>",
         // Llama 3
         "<|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nHi there<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWho are you<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nI am an assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nAnother question<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
-        // Phi 3
-        "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\nI am an assistant<|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
+        //Phi-3-mini
+        "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
+        //Phi-3-small
+        "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
+        //Phi-3-medium
+        "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
+        //Phi-3-vision
+        "<|system|>\nYou are a helpful assistant<|end|>\n<|user|>\nHello<|end|>\n<|assistant|>\nHi there<|end|>\n<|user|>\nWho are you<|end|>\n<|assistant|>\n   I am an assistant   <|end|>\n<|user|>\nAnother question<|end|>\n<|assistant|>\n",
     };
     std::vector<char> formatted_chat(1024);
     int32_t res;
diff --git a/tests/test-grad0.cpp b/tests/test-grad0.cpp
index 8ff76c891..21ca43be3 100644
--- a/tests/test-grad0.cpp
+++ b/tests/test-grad0.cpp
@@ -1515,90 +1515,50 @@ int main(int argc, const char ** argv) {
         }
 
         // flash_attn f32
-        {
-            srand(seed);
-            const int nargs = 3;
+        // TODO: adapt to ggml_flash_attn_ext() changes
+        //{
+        //    srand(seed);
+        //    const int nargs = 3;
 
-            int64_t ne2[4];
+        //    int64_t ne2[4];
 
-            get_random_dims(ne2, 4);
-            int64_t D = ne2[0];
-            int64_t N = ne2[1];
-            int64_t M = ne2[2] + N;
-            int64_t B = ne2[3];
+        //    get_random_dims(ne2, 4);
+        //    int64_t D = ne2[0];
+        //    int64_t N = ne2[1];
+        //    int64_t M = ne2[2] + N;
+        //    int64_t B = ne2[3];
 
-            for (int masked = 0; masked <= 1; ++masked) {
-                for (int ndims = 2; ndims <= 4; ++ndims) {
-                    int max_nrep = (ndims >= 3) ? 2 : 1;
-                    for (int nrep = 1; nrep < max_nrep; ++nrep) {
-                        int64_t neq[4] = { D, N, B*nrep, ne[3] };
-                        int64_t nek[4] = { D, M, B, ne[3] };
-                        int64_t nev[4] = { M, D, B, ne[3] };
-                        if (ndims == 2) {
-                            neq[2] = 1; neq[3] = 1;
-                            nek[2] = 1; nek[3] = 1;
-                            nev[2] = 1; nev[3] = 1;
-                        } else if (ndims == 3) {
-                            neq[3] = 1;
-                            nek[3] = 1;
-                            nev[3] = 1;
-                        }
-                        x[0] = get_random_tensor_f32(ctx0, ndims, neq, -0.1250f, 0.1250f);
-                        x[1] = get_random_tensor_f32(ctx0, ndims, nek, -0.1250f, 0.1250f);
-                        x[2] = get_random_tensor_f32(ctx0, ndims, nev, -0.1250f, 0.1250f);
-                        ggml_set_param(ctx0, x[0]);
-                        ggml_set_param(ctx0, x[1]);
-                        ggml_set_param(ctx0, x[2]);
+        //    for (int masked = 0; masked <= 1; ++masked) {
+        //        for (int ndims = 2; ndims <= 4; ++ndims) {
+        //            int max_nrep = (ndims >= 3) ? 2 : 1;
+        //            for (int nrep = 1; nrep < max_nrep; ++nrep) {
+        //                int64_t neq[4] = { D, N, B*nrep, ne[3] };
+        //                int64_t nek[4] = { D, M, B, ne[3] };
+        //                int64_t nev[4] = { M, D, B, ne[3] };
+        //                if (ndims == 2) {
+        //                    neq[2] = 1; neq[3] = 1;
+        //                    nek[2] = 1; nek[3] = 1;
+        //                    nev[2] = 1; nev[3] = 1;
+        //                } else if (ndims == 3) {
+        //                    neq[3] = 1;
+        //                    nek[3] = 1;
+        //                    nev[3] = 1;
+        //                }
+        //                x[0] = get_random_tensor_f32(ctx0, ndims, neq, -0.1250f, 0.1250f);
+        //                x[1] = get_random_tensor_f32(ctx0, ndims, nek, -0.1250f, 0.1250f);
+        //                x[2] = get_random_tensor_f32(ctx0, ndims, nev, -0.1250f, 0.1250f);
+        //                ggml_set_param(ctx0, x[0]);
+        //                ggml_set_param(ctx0, x[1]);
+        //                ggml_set_param(ctx0, x[2]);
 
-                        struct ggml_tensor * f = ggml_sum(ctx0, ggml_flash_attn(ctx0, x[0], x[1], x[2], (masked == 0)));
+        //                struct ggml_tensor * f = ggml_sum(ctx0, ggml_flash_attn(ctx0, x[0], x[1], x[2], (masked == 0)));
 
-                        check_gradient("flash_attn f32", ctx0, x, f, ndims, nargs, 1.5e-4f, 1e-3f, INFINITY);
-                    }
-                }
-            }
-        }
+        //                check_gradient("flash_attn f32", ctx0, x, f, ndims, nargs, 1.5e-4f, 1e-3f, INFINITY);
+        //            }
+        //        }
+        //    }
+        //}
 
-        // flash_attn f16, not yet fully implemented
-        if(0)
-        {
-            srand(seed);
-            const int nargs = 3;
-
-            int64_t ne2[4];
-
-            get_random_dims(ne2, 4);
-            int64_t D = ne2[0];
-            int64_t N = ne2[1];
-            int64_t M = ne2[2] + N;
-            int64_t B = ne2[3];
-
-            for (int masked = 0; masked <= 1; ++masked) {
-                for (int ndims = 2; ndims <= 4; ++ndims) {
-                    int64_t neq[4] = { D, N, B, ne[3] };
-                    int64_t nek[4] = { D, M, B, ne[3] };
-                    int64_t nev[4] = { M, D, B, ne[3] };
-                    if (ndims == 2) {
-                        neq[2] = 1; neq[3] = 1;
-                        nek[2] = 1; nek[3] = 1;
-                        nev[2] = 1; nev[3] = 1;
-                    } else if (ndims == 3) {
-                        neq[3] = 1;
-                        nek[3] = 1;
-                        nev[3] = 1;
-                    }
-                    x[0] = get_random_tensor_f16(ctx0, ndims, neq, -0.1250f, 0.1250f);
-                    x[1] = get_random_tensor_f16(ctx0, ndims, nek, -0.1250f, 0.1250f);
-                    x[2] = get_random_tensor_f16(ctx0, ndims, nev, -0.1250f, 0.1250f);
-                    ggml_set_param(ctx0, x[0]);
-                    ggml_set_param(ctx0, x[1]);
-                    ggml_set_param(ctx0, x[2]);
-
-                    struct ggml_tensor * f = ggml_sum(ctx0, ggml_flash_attn(ctx0, x[0], x[1], x[2], (masked == 0)));
-
-                    check_gradient("flash_attn f16", ctx0, x, f, ndims, nargs, 1.5e-4f, 1e-3f, INFINITY);
-                }
-            }
-        }
         ggml_free(ctx0);
     }
 
diff --git a/tests/test-tokenizer-0.sh b/tests/test-tokenizer-0.sh
index 2fb8632d8..1fec8bbf1 100755
--- a/tests/test-tokenizer-0.sh
+++ b/tests/test-tokenizer-0.sh
@@ -17,10 +17,15 @@ make -j tests/test-tokenizer-0
 
 printf "Testing %s on %s ...\n" $name $input
 
-python3 ./tests/test-tokenizer-0.py ./models/tokenizers/$name --fname-tok $input > /tmp/test-tokenizer-0-$name-py.log 2>&1
-cat /tmp/test-tokenizer-0-$name-py.log | grep "tokenized in"
+set -e
 
+printf "Tokenizing using (py)  Python AutoTokenizer ...\n"
+python3 ./tests/test-tokenizer-0.py ./models/tokenizers/$name --fname-tok $input > /tmp/test-tokenizer-0-$name-py.log 2>&1
+
+printf "Tokenizing using (cpp) llama.cpp ...\n"
 ./tests/test-tokenizer-0 ./models/ggml-vocab-$name.gguf $input > /tmp/test-tokenizer-0-$name-cpp.log 2>&1
+
+cat /tmp/test-tokenizer-0-$name-py.log | grep "tokenized in"
 cat /tmp/test-tokenizer-0-$name-cpp.log | grep "tokenized in"
 
 diff $input.tok $input.tokcpp > /dev/null 2>&1
diff --git a/tests/test-tokenizer-random.py b/tests/test-tokenizer-random.py
index 5b2ab8ef7..7e1b656e5 100644
--- a/tests/test-tokenizer-random.py
+++ b/tests/test-tokenizer-random.py
@@ -1,5 +1,5 @@
 # Test libllama tokenizer == AutoTokenizer.
-# Brute force random tokens/text generation.
+# Brute force random words/text generation.
 #
 # Sample usage:
 #
@@ -12,10 +12,10 @@ import argparse
 import subprocess
 import random
 
-from typing import Iterator
+from typing import Callable, Iterator
 
 import cffi
-from transformers import AutoTokenizer, PreTrainedTokenizerBase
+from transformers import AutoTokenizer
 
 logger = logging.getLogger("test-tokenizer-random-bpe")
 
@@ -145,28 +145,50 @@ def generator_custom_text() -> Iterator[str]:
 def generator_custom_text_edge_cases() -> Iterator[str]:
     """Edge cases found while debugging"""
     yield from [
-        '\x1f-a',   # unicode_ranges_control, {0x00001C, 0x00001F}
-        '¼-a',      # unicode_ranges_digit, 0x00BC
-        '½-a',      # unicode_ranges_digit, 0x00BD
-        '¾-a',      # unicode_ranges_digit, 0x00BE
-        'a 〇b',    # unicode_ranges_digit, 0x3007
-        'Ⅵ-a',     # unicode_ranges_digit, {0x00002150, 0x0000218F} // Number Forms
-        '\uFEFF//', # unicode_ranges_control, 0xFEFF (BOM)
-        '<s>a'      # TODO: Phi-3 fail
+        '\x1f-a',     # unicode_ranges_control, {0x00001C, 0x00001F}
+        '¼-a',        # unicode_ranges_digit, 0x00BC
+        '½-a',        # unicode_ranges_digit, 0x00BD
+        '¾-a',        # unicode_ranges_digit, 0x00BE
+        'a 〇b',      # unicode_ranges_digit, 0x3007
+        'Ⅵ-a',       # unicode_ranges_digit, {0x00002150, 0x0000218F} // Number Forms
+        '\uFEFF//',   # unicode_ranges_control, 0xFEFF (BOM)
+        'Cửa Việt',   # llama-3, ignore_merges = true
+        '<s>a',       # Phi-3 fail
+        '<unk><|endoftext|><s>',  # Phi-3 fail
+        'a\na',       # TODO: Bert fail
     ]
 
 
-def generator_random_chars(iterations = 100) -> Iterator[str]:
+def generator_random_special_tokens(tokenizer, iterations=100) -> Iterator[str]:
+    special_tokens = set(tokenizer.all_special_tokens)
+    special_tokens.update([" ", "\n", "\t", "-", "!", "one", "1", "<s>", "</s>"])
+    special_tokens = list(sorted(special_tokens))
+    rand = random.Random()
+    for m in range(iterations):
+        rand.seed(m)
+        words = rand.choices(special_tokens, k=500)
+        if tokenizer.add_bos_token:  # skip spam warning of double BOS
+            while words and words[0] == tokenizer.bos_token:
+                words.pop(0)
+        yield "".join(words)
+
+
+def generator_vocab_words(vocab: list[str]) -> Iterator[str]:
+    """Brute force check all vocab words"""
+    yield from vocab
+
+
+def generator_random_chars(iterations=100) -> Iterator[str]:
     """Brute force random text with simple characters"""
 
     WHITESPACES = list(" " * 20 + "\n" * 5 + "\r\n" * 5 + "\t" * 5)
-    CHARS = list(set("""
+    CHARS = list(sorted(set("""
         ABCDEFGHIJKLMNOPQRSTUVWXYZ
         abcdefghijklmnopqrstuvwxyz
         ÁÉÍÓÚÀÈÌÒÙÂÊÎÔÛÄËÏÖÜ
         áéíóúàèìòùâêîôûäëïöü
         .-,*/-+ª!"·$%&/()=?¿[]{}<>\\|@#~½¬~;:_
-    """))
+    """)))
 
     rand = random.Random()
     for m in range(iterations):
@@ -181,13 +203,13 @@ def generator_random_chars(iterations = 100) -> Iterator[str]:
         yield "".join(text)
 
 
-def generator_random_vocab_chars(tokenizer: PreTrainedTokenizerBase, iterations = 100) -> Iterator[str]:
+def generator_random_vocab_chars(vocab: list[str], iterations=100) -> Iterator[str]:
     """Brute force random text with vocab characters"""
 
-    vocab_ids = list(tokenizer.vocab.values())
-    vocab_text = tokenizer.decode(vocab_ids, skip_special_tokens=True)
-    vocab_chars = list(set(vocab_text))
-    del vocab_ids, vocab_text
+    vocab_chars = set()
+    for word in vocab:
+        vocab_chars.update(word)
+    vocab_chars = list(sorted(vocab_chars))
 
     rand = random.Random()
     for m in range(iterations):
@@ -196,19 +218,11 @@ def generator_random_vocab_chars(tokenizer: PreTrainedTokenizerBase, iterations
         yield "".join(text)
 
 
-def generator_random_vocab_tokens(tokenizer: PreTrainedTokenizerBase, iterations = 100) -> Iterator[str]:
-    """Brute force random text from vocab tokens"""
+def generator_random_vocab_words(vocab: list[str], iterations=100) -> Iterator[str]:
+    """Brute force random text from vocab words"""
 
-    space_id = tokenizer.encode(" ", add_special_tokens=False)[0]
-    vocab_ids = list(tokenizer.vocab.values())
-    vocab_ids = list(sorted(vocab_ids + vocab_ids))
-    for i in range(1, len(vocab_ids), 2):
-        vocab_ids[i] = space_id
-    vocab_tokens = tokenizer.decode(vocab_ids, skip_special_tokens=True)
-    vocab_tokens = vocab_tokens.split(" ")
-    del vocab_ids
-
-    yield from vocab_tokens
+    vocab = [w.strip() for w in vocab]
+    yield from vocab
 
     rand = random.Random()
     for m in range(iterations):
@@ -217,14 +231,13 @@ def generator_random_vocab_tokens(tokenizer: PreTrainedTokenizerBase, iterations
         num_words = rand.randint(300, 400)
         for i in range(num_words):
             k = rand.randint(1, 3)
-            tokens = rand.choices(vocab_tokens, k=k)
-            tokens = [t.strip(" \n\r\t") for t in tokens]
+            words = rand.choices(vocab, k=k)
             sep = rand.choice("     \n\r\t")
-            text.append("".join(tokens) + sep)
+            text.append("".join(words) + sep)
         yield "".join(text)
 
 
-def generator_random_bytes(iterations = 100) -> Iterator[str]:
+def generator_random_bytes(iterations=100) -> Iterator[str]:
     """Brute force random bytes"""
 
     WHITESPACES = list(" " * 20 + "\n" * 5 + "\r\n" * 5 + "\t" * 5)
@@ -242,10 +255,10 @@ def generator_random_bytes(iterations = 100) -> Iterator[str]:
         yield "".join(text)
 
 
-def test_compare_tokenizer(model: LibLlamaModel, tokenizer: PreTrainedTokenizerBase, generator: Iterator[str]):
+def test_compare_tokenizer(func_tokenize1: Callable, func_tokenize2: Callable, generator: Iterator[str]):
 
     def find_first_mismatch(ids1: list[int], ids2: list[int]):
-        for i, (a,b) in enumerate(zip(ids1, ids2)):
+        for i, (a, b) in enumerate(zip(ids1, ids2)):
             if a != b:
                 return i
         if len(ids1) == len(ids2):
@@ -255,15 +268,12 @@ def test_compare_tokenizer(model: LibLlamaModel, tokenizer: PreTrainedTokenizerB
     t0 = time.perf_counter()
     logger.info("%s: %s" % (generator.__name__, "ini"))
     for text in generator:
-        ids1 = model.tokenize(text, add_special=False, parse_special=False)
-        ids2 = tokenizer.encode(text, add_special_tokens=False)
+        ids1 = func_tokenize1(text)
+        ids2 = func_tokenize2(text)
         if ids1 != ids2:
             i = find_first_mismatch(ids1, ids2)
             ids1 = list(ids1)[max(0, i - 2) : i + 2 + 1]
             ids2 = list(ids2)[max(0, i - 2) : i + 2 + 1]
-            text2 = tokenizer.decode(ids2, skip_special_tokens=True)
-            assert (text2 in text)
-            logger.info(" Text:     " + repr(text2))
             logger.info(" TokenIDs: " + str(ids1))
             logger.info(" Expected: " + str(ids2))
             raise Exception()
@@ -271,25 +281,55 @@ def test_compare_tokenizer(model: LibLlamaModel, tokenizer: PreTrainedTokenizerB
     logger.info("%s: end, time: %.3f secs" % (generator.__name__, t1 - t0))
 
 
-if __name__ == "__main__":
-
+def main(argv: list[str] = None):
     parser = argparse.ArgumentParser()
     parser.add_argument("vocab_file", help="path to vocab 'gguf' file")
     parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file")
     parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
-    args = parser.parse_args()
+    args = parser.parse_args(argv)
 
     logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
 
-    model = LibLlamaModel(LibLlama(), args.vocab_file, mparams=dict(vocab_only=True), cparams=dict(n_ctx=2048))
-
+    model = LibLlamaModel(LibLlama(), args.vocab_file, mparams=dict(vocab_only=True), cparams=dict(n_ctx=4096))
     tokenizer = AutoTokenizer.from_pretrained(args.dir_tokenizer)
 
-    test_compare_tokenizer(model, tokenizer, generator_custom_text())
-    test_compare_tokenizer(model, tokenizer, generator_custom_text_edge_cases())
-    test_compare_tokenizer(model, tokenizer, generator_random_chars(10_000))
-    test_compare_tokenizer(model, tokenizer, generator_random_vocab_chars(tokenizer, 10_000))
-    test_compare_tokenizer(model, tokenizer, generator_random_vocab_tokens(tokenizer, 10_000))
-    # test_compare_tokenizer(model, tokenizer, generator_random_bytes(10_000)) # FAIL
+    tokenizer.add_bos_token = getattr(tokenizer, "add_bos_token", True)
+    tokenizer.add_eos_token = getattr(tokenizer, "add_eos_token", False)
+
+    def func_tokenize1(text: str):
+        return model.tokenize(text, add_special=True, parse_special=True)
+
+    def func_tokenize2(text: str):
+        return tokenizer.encode(text, add_special_tokens=True)
+
+    vocab = list(sorted(tokenizer.batch_decode(list(tokenizer.get_vocab().values()), skip_special_tokens=True)))
+    test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_custom_text())
+    test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_custom_text_edge_cases())
+    test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_random_special_tokens(tokenizer, 10_000))
+    test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_vocab_words(vocab))
+    test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_random_chars(10_000))
+    test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_random_vocab_chars(vocab, 10_000))
+    test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_random_vocab_words(vocab, 5_000))
+    # test_compare_tokenizer(func_tokenize1, func_tokenize2, generator_random_bytes(10_000)) # FAIL
 
     model.free()
+
+
+if __name__ == "__main__":
+    # main()
+
+    path_tokenizers = "./models/tokenizers/"
+    path_vocab_format = "./models/ggml-vocab-%s.gguf"
+
+    # import os
+    # tokenizers = os.listdir(path_tokenizers)
+    tokenizers = [
+        "llama-spm",   # SPM
+        "phi-3",       # SPM
+    ]
+
+    for tokenizer in tokenizers:
+        print("\n" + "=" * 50 + "\n" + tokenizer + "\n")  # noqa
+        vocab_file = path_vocab_format % tokenizer
+        dir_tokenizer = path_tokenizers + "/" + tokenizer
+        main([vocab_file, dir_tokenizer, "--verbose"])
diff --git a/unicode-data.cpp b/unicode-data.cpp
index c54175fc3..d7c1c898d 100644
--- a/unicode-data.cpp
+++ b/unicode-data.cpp
@@ -1,2183 +1,6983 @@
-#include "unicode-data.h"
+// generated with scripts/gen-unicode-data.py
+
+#include "unicode-data.h"
 
 #include <cstdint>
-#include <map>
-#include <utility>
 #include <vector>
+#include <unordered_map>
+#include <unordered_set>
 
-// generated with scripts/gen-unicode-data.py
-//
-// TODO: generate unicode_map_nfd
-
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_number = {
-{0x00000030, 0x00000039}, {0x000000B2, 0x000000B3}, {0x000000B9, 0x000000B9}, {0x000000BC, 0x000000BE},
-{0x00000660, 0x00000669}, {0x000006F0, 0x000006F9}, {0x000007C0, 0x000007C9}, {0x00000966, 0x0000096F},
-{0x000009E6, 0x000009EF}, {0x000009F4, 0x000009F9}, {0x00000A66, 0x00000A6F}, {0x00000AE6, 0x00000AEF},
-{0x00000B66, 0x00000B6F}, {0x00000B72, 0x00000B77}, {0x00000BE6, 0x00000BF2}, {0x00000C66, 0x00000C6F},
-{0x00000C78, 0x00000C7E}, {0x00000CE6, 0x00000CEF}, {0x00000D58, 0x00000D5E}, {0x00000D66, 0x00000D78},
-{0x00000DE6, 0x00000DEF}, {0x00000E50, 0x00000E59}, {0x00000ED0, 0x00000ED9}, {0x00000F20, 0x00000F33},
-{0x00001040, 0x00001049}, {0x00001090, 0x00001099}, {0x00001369, 0x0000137C}, {0x000016EE, 0x000016F0},
-{0x000017E0, 0x000017E9}, {0x000017F0, 0x000017F9}, {0x00001810, 0x00001819}, {0x00001946, 0x0000194F},
-{0x000019D0, 0x000019DA}, {0x00001A80, 0x00001A89}, {0x00001A90, 0x00001A99}, {0x00001B50, 0x00001B59},
-{0x00001BB0, 0x00001BB9}, {0x00001C40, 0x00001C49}, {0x00001C50, 0x00001C59}, {0x00002070, 0x00002070},
-{0x00002074, 0x00002079}, {0x00002080, 0x00002089}, {0x00002150, 0x00002182}, {0x00002185, 0x00002189},
-{0x00002460, 0x0000249B}, {0x000024EA, 0x000024FF}, {0x00002776, 0x00002793}, {0x00002CFD, 0x00002CFD},
-{0x00003007, 0x00003007}, {0x00003021, 0x00003029}, {0x00003038, 0x0000303A}, {0x00003192, 0x00003195},
-{0x00003220, 0x00003229}, {0x00003248, 0x0000324F}, {0x00003251, 0x0000325F}, {0x00003280, 0x00003289},
-{0x000032B1, 0x000032BF}, {0x0000A620, 0x0000A629}, {0x0000A6E6, 0x0000A6EF}, {0x0000A830, 0x0000A835},
-{0x0000A8D0, 0x0000A8D9}, {0x0000A900, 0x0000A909}, {0x0000A9D0, 0x0000A9D9}, {0x0000A9F0, 0x0000A9F9},
-{0x0000AA50, 0x0000AA59}, {0x0000ABF0, 0x0000ABF9}, {0x0000FF10, 0x0000FF19}, {0x00010107, 0x00010133},
-{0x00010140, 0x00010178}, {0x0001018A, 0x0001018B}, {0x000102E1, 0x000102FB}, {0x00010320, 0x00010323},
-{0x00010341, 0x00010341}, {0x0001034A, 0x0001034A}, {0x000103D1, 0x000103D5}, {0x000104A0, 0x000104A9},
-{0x00010858, 0x0001085F}, {0x00010879, 0x0001087F}, {0x000108A7, 0x000108AF}, {0x000108FB, 0x000108FF},
-{0x00010916, 0x0001091B}, {0x000109BC, 0x000109BD}, {0x000109C0, 0x000109CF}, {0x000109D2, 0x000109FF},
-{0x00010A40, 0x00010A48}, {0x00010A7D, 0x00010A7E}, {0x00010A9D, 0x00010A9F}, {0x00010AEB, 0x00010AEF},
-{0x00010B58, 0x00010B5F}, {0x00010B78, 0x00010B7F}, {0x00010BA9, 0x00010BAF}, {0x00010CFA, 0x00010CFF},
-{0x00010D30, 0x00010D39}, {0x00010E60, 0x00010E7E}, {0x00010F1D, 0x00010F26}, {0x00010F51, 0x00010F54},
-{0x00010FC5, 0x00010FCB}, {0x00011052, 0x0001106F}, {0x000110F0, 0x000110F9}, {0x00011136, 0x0001113F},
-{0x000111D0, 0x000111D9}, {0x000111E1, 0x000111F4}, {0x000112F0, 0x000112F9}, {0x00011450, 0x00011459},
-{0x000114D0, 0x000114D9}, {0x00011650, 0x00011659}, {0x000116C0, 0x000116C9}, {0x00011730, 0x0001173B},
-{0x000118E0, 0x000118F2}, {0x00011950, 0x00011959}, {0x00011C50, 0x00011C6C}, {0x00011D50, 0x00011D59},
-{0x00011DA0, 0x00011DA9}, {0x00011F50, 0x00011F59}, {0x00011FC0, 0x00011FD4}, {0x00012400, 0x0001246E},
-{0x00016A60, 0x00016A69}, {0x00016AC0, 0x00016AC9}, {0x00016B50, 0x00016B59}, {0x00016B5B, 0x00016B61},
-{0x00016E80, 0x00016E96}, {0x0001D2C0, 0x0001D2D3}, {0x0001D2E0, 0x0001D2F3}, {0x0001D360, 0x0001D378},
-{0x0001D7CE, 0x0001D7FF}, {0x0001E140, 0x0001E149}, {0x0001E2F0, 0x0001E2F9}, {0x0001E4F0, 0x0001E4F9},
-{0x0001E8C7, 0x0001E8CF}, {0x0001E950, 0x0001E959}, {0x0001EC71, 0x0001ECAB}, {0x0001ECAD, 0x0001ECAF},
-{0x0001ECB1, 0x0001ECB4}, {0x0001ED01, 0x0001ED2D}, {0x0001ED2F, 0x0001ED3D}, {0x0001F100, 0x0001F10C},
-{0x0001FBF0, 0x0001FBF9},
+const std::vector<std::pair<uint32_t, uint16_t>> unicode_ranges_flags = {  // start, flags // last=next_start-1
+{0x000000, 0x0080},
+{0x000020, 0x0008},
+{0x000021, 0x0020},
+{0x000024, 0x0040},
+{0x000025, 0x0020},
+{0x00002B, 0x0040},
+{0x00002C, 0x0020},
+{0x000030, 0x0002},
+{0x00003A, 0x0020},
+{0x00003C, 0x0040},
+{0x00003F, 0x0020},
+{0x000041, 0x0004},
+{0x00005B, 0x0020},
+{0x00005E, 0x0040},
+{0x00005F, 0x0020},
+{0x000060, 0x0040},
+{0x000061, 0x0004},
+{0x00007B, 0x0020},
+{0x00007C, 0x0040},
+{0x00007D, 0x0020},
+{0x00007E, 0x0040},
+{0x00007F, 0x0080},
+{0x0000A0, 0x0008},
+{0x0000A1, 0x0020},
+{0x0000A2, 0x0040},
+{0x0000A7, 0x0020},
+{0x0000A8, 0x0040},
+{0x0000AA, 0x0004},
+{0x0000AB, 0x0020},
+{0x0000AC, 0x0040},
+{0x0000AD, 0x0080},
+{0x0000AE, 0x0040},
+{0x0000B2, 0x0002},
+{0x0000B4, 0x0040},
+{0x0000B5, 0x0004},
+{0x0000B6, 0x0020},
+{0x0000B8, 0x0040},
+{0x0000B9, 0x0002},
+{0x0000BA, 0x0004},
+{0x0000BB, 0x0020},
+{0x0000BC, 0x0002},
+{0x0000BF, 0x0020},
+{0x0000C0, 0x0004},
+{0x0000D7, 0x0040},
+{0x0000D8, 0x0004},
+{0x0000F7, 0x0040},
+{0x0000F8, 0x0004},
+{0x0002C2, 0x0040},
+{0x0002C6, 0x0004},
+{0x0002D2, 0x0040},
+{0x0002E0, 0x0004},
+{0x0002E5, 0x0040},
+{0x0002EC, 0x0004},
+{0x0002ED, 0x0040},
+{0x0002EE, 0x0004},
+{0x0002EF, 0x0040},
+{0x000300, 0x0010},
+{0x000370, 0x0004},
+{0x000375, 0x0040},
+{0x000376, 0x0004},
+{0x000378, 0x0080},
+{0x00037A, 0x0004},
+{0x00037E, 0x0020},
+{0x00037F, 0x0004},
+{0x000380, 0x0080},
+{0x000384, 0x0040},
+{0x000386, 0x0004},
+{0x000387, 0x0020},
+{0x000388, 0x0004},
+{0x00038B, 0x0080},
+{0x00038C, 0x0004},
+{0x00038D, 0x0080},
+{0x00038E, 0x0004},
+{0x0003A2, 0x0080},
+{0x0003A3, 0x0004},
+{0x0003F6, 0x0040},
+{0x0003F7, 0x0004},
+{0x000482, 0x0040},
+{0x000483, 0x0010},
+{0x00048A, 0x0004},
+{0x000530, 0x0080},
+{0x000531, 0x0004},
+{0x000557, 0x0080},
+{0x000559, 0x0004},
+{0x00055A, 0x0020},
+{0x000560, 0x0004},
+{0x000589, 0x0020},
+{0x00058B, 0x0080},
+{0x00058D, 0x0040},
+{0x000590, 0x0080},
+{0x000591, 0x0010},
+{0x0005BE, 0x0020},
+{0x0005BF, 0x0010},
+{0x0005C0, 0x0020},
+{0x0005C1, 0x0010},
+{0x0005C3, 0x0020},
+{0x0005C4, 0x0010},
+{0x0005C6, 0x0020},
+{0x0005C7, 0x0010},
+{0x0005C8, 0x0080},
+{0x0005D0, 0x0004},
+{0x0005EB, 0x0080},
+{0x0005EF, 0x0004},
+{0x0005F3, 0x0020},
+{0x0005F5, 0x0080},
+{0x000606, 0x0040},
+{0x000609, 0x0020},
+{0x00060B, 0x0040},
+{0x00060C, 0x0020},
+{0x00060E, 0x0040},
+{0x000610, 0x0010},
+{0x00061B, 0x0020},
+{0x00061C, 0x0080},
+{0x00061D, 0x0020},
+{0x000620, 0x0004},
+{0x00064B, 0x0010},
+{0x000660, 0x0002},
+{0x00066A, 0x0020},
+{0x00066E, 0x0004},
+{0x000670, 0x0010},
+{0x000671, 0x0004},
+{0x0006D4, 0x0020},
+{0x0006D5, 0x0004},
+{0x0006D6, 0x0010},
+{0x0006DD, 0x0080},
+{0x0006DE, 0x0040},
+{0x0006DF, 0x0010},
+{0x0006E5, 0x0004},
+{0x0006E7, 0x0010},
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+{0x016FF0, 0x0010},
+{0x016FF2, 0x0080},
+{0x017000, 0x0004},
+{0x0187F8, 0x0080},
+{0x018800, 0x0004},
+{0x018CD6, 0x0080},
+{0x018D00, 0x0004},
+{0x018D09, 0x0080},
+{0x01AFF0, 0x0004},
+{0x01AFF4, 0x0080},
+{0x01AFF5, 0x0004},
+{0x01AFFC, 0x0080},
+{0x01AFFD, 0x0004},
+{0x01AFFF, 0x0080},
+{0x01B000, 0x0004},
+{0x01B123, 0x0080},
+{0x01B132, 0x0004},
+{0x01B133, 0x0080},
+{0x01B150, 0x0004},
+{0x01B153, 0x0080},
+{0x01B155, 0x0004},
+{0x01B156, 0x0080},
+{0x01B164, 0x0004},
+{0x01B168, 0x0080},
+{0x01B170, 0x0004},
+{0x01B2FC, 0x0080},
+{0x01BC00, 0x0004},
+{0x01BC6B, 0x0080},
+{0x01BC70, 0x0004},
+{0x01BC7D, 0x0080},
+{0x01BC80, 0x0004},
+{0x01BC89, 0x0080},
+{0x01BC90, 0x0004},
+{0x01BC9A, 0x0080},
+{0x01BC9C, 0x0040},
+{0x01BC9D, 0x0010},
+{0x01BC9F, 0x0020},
+{0x01BCA0, 0x0080},
+{0x01CF00, 0x0010},
+{0x01CF2E, 0x0080},
+{0x01CF30, 0x0010},
+{0x01CF47, 0x0080},
+{0x01CF50, 0x0040},
+{0x01CFC4, 0x0080},
+{0x01D000, 0x0040},
+{0x01D0F6, 0x0080},
+{0x01D100, 0x0040},
+{0x01D127, 0x0080},
+{0x01D129, 0x0040},
+{0x01D165, 0x0010},
+{0x01D16A, 0x0040},
+{0x01D16D, 0x0010},
+{0x01D173, 0x0080},
+{0x01D17B, 0x0010},
+{0x01D183, 0x0040},
+{0x01D185, 0x0010},
+{0x01D18C, 0x0040},
+{0x01D1AA, 0x0010},
+{0x01D1AE, 0x0040},
+{0x01D1EB, 0x0080},
+{0x01D200, 0x0040},
+{0x01D242, 0x0010},
+{0x01D245, 0x0040},
+{0x01D246, 0x0080},
+{0x01D2C0, 0x0002},
+{0x01D2D4, 0x0080},
+{0x01D2E0, 0x0002},
+{0x01D2F4, 0x0080},
+{0x01D300, 0x0040},
+{0x01D357, 0x0080},
+{0x01D360, 0x0002},
+{0x01D379, 0x0080},
+{0x01D400, 0x0004},
+{0x01D455, 0x0080},
+{0x01D456, 0x0004},
+{0x01D49D, 0x0080},
+{0x01D49E, 0x0004},
+{0x01D4A0, 0x0080},
+{0x01D4A2, 0x0004},
+{0x01D4A3, 0x0080},
+{0x01D4A5, 0x0004},
+{0x01D4A7, 0x0080},
+{0x01D4A9, 0x0004},
+{0x01D4AD, 0x0080},
+{0x01D4AE, 0x0004},
+{0x01D4BA, 0x0080},
+{0x01D4BB, 0x0004},
+{0x01D4BC, 0x0080},
+{0x01D4BD, 0x0004},
+{0x01D4C4, 0x0080},
+{0x01D4C5, 0x0004},
+{0x01D506, 0x0080},
+{0x01D507, 0x0004},
+{0x01D50B, 0x0080},
+{0x01D50D, 0x0004},
+{0x01D515, 0x0080},
+{0x01D516, 0x0004},
+{0x01D51D, 0x0080},
+{0x01D51E, 0x0004},
+{0x01D53A, 0x0080},
+{0x01D53B, 0x0004},
+{0x01D53F, 0x0080},
+{0x01D540, 0x0004},
+{0x01D545, 0x0080},
+{0x01D546, 0x0004},
+{0x01D547, 0x0080},
+{0x01D54A, 0x0004},
+{0x01D551, 0x0080},
+{0x01D552, 0x0004},
+{0x01D6A6, 0x0080},
+{0x01D6A8, 0x0004},
+{0x01D6C1, 0x0040},
+{0x01D6C2, 0x0004},
+{0x01D6DB, 0x0040},
+{0x01D6DC, 0x0004},
+{0x01D6FB, 0x0040},
+{0x01D6FC, 0x0004},
+{0x01D715, 0x0040},
+{0x01D716, 0x0004},
+{0x01D735, 0x0040},
+{0x01D736, 0x0004},
+{0x01D74F, 0x0040},
+{0x01D750, 0x0004},
+{0x01D76F, 0x0040},
+{0x01D770, 0x0004},
+{0x01D789, 0x0040},
+{0x01D78A, 0x0004},
+{0x01D7A9, 0x0040},
+{0x01D7AA, 0x0004},
+{0x01D7C3, 0x0040},
+{0x01D7C4, 0x0004},
+{0x01D7CC, 0x0080},
+{0x01D7CE, 0x0002},
+{0x01D800, 0x0040},
+{0x01DA00, 0x0010},
+{0x01DA37, 0x0040},
+{0x01DA3B, 0x0010},
+{0x01DA6D, 0x0040},
+{0x01DA75, 0x0010},
+{0x01DA76, 0x0040},
+{0x01DA84, 0x0010},
+{0x01DA85, 0x0040},
+{0x01DA87, 0x0020},
+{0x01DA8C, 0x0080},
+{0x01DA9B, 0x0010},
+{0x01DAA0, 0x0080},
+{0x01DAA1, 0x0010},
+{0x01DAB0, 0x0080},
+{0x01DF00, 0x0004},
+{0x01DF1F, 0x0080},
+{0x01DF25, 0x0004},
+{0x01DF2B, 0x0080},
+{0x01E000, 0x0010},
+{0x01E007, 0x0080},
+{0x01E008, 0x0010},
+{0x01E019, 0x0080},
+{0x01E01B, 0x0010},
+{0x01E022, 0x0080},
+{0x01E023, 0x0010},
+{0x01E025, 0x0080},
+{0x01E026, 0x0010},
+{0x01E02B, 0x0080},
+{0x01E030, 0x0004},
+{0x01E06E, 0x0080},
+{0x01E08F, 0x0010},
+{0x01E090, 0x0080},
+{0x01E100, 0x0004},
+{0x01E12D, 0x0080},
+{0x01E130, 0x0010},
+{0x01E137, 0x0004},
+{0x01E13E, 0x0080},
+{0x01E140, 0x0002},
+{0x01E14A, 0x0080},
+{0x01E14E, 0x0004},
+{0x01E14F, 0x0040},
+{0x01E150, 0x0080},
+{0x01E290, 0x0004},
+{0x01E2AE, 0x0010},
+{0x01E2AF, 0x0080},
+{0x01E2C0, 0x0004},
+{0x01E2EC, 0x0010},
+{0x01E2F0, 0x0002},
+{0x01E2FA, 0x0080},
+{0x01E2FF, 0x0040},
+{0x01E300, 0x0080},
+{0x01E4D0, 0x0004},
+{0x01E4EC, 0x0010},
+{0x01E4F0, 0x0002},
+{0x01E4FA, 0x0080},
+{0x01E7E0, 0x0004},
+{0x01E7E7, 0x0080},
+{0x01E7E8, 0x0004},
+{0x01E7EC, 0x0080},
+{0x01E7ED, 0x0004},
+{0x01E7EF, 0x0080},
+{0x01E7F0, 0x0004},
+{0x01E7FF, 0x0080},
+{0x01E800, 0x0004},
+{0x01E8C5, 0x0080},
+{0x01E8C7, 0x0002},
+{0x01E8D0, 0x0010},
+{0x01E8D7, 0x0080},
+{0x01E900, 0x0004},
+{0x01E944, 0x0010},
+{0x01E94B, 0x0004},
+{0x01E94C, 0x0080},
+{0x01E950, 0x0002},
+{0x01E95A, 0x0080},
+{0x01E95E, 0x0020},
+{0x01E960, 0x0080},
+{0x01EC71, 0x0002},
+{0x01ECAC, 0x0040},
+{0x01ECAD, 0x0002},
+{0x01ECB0, 0x0040},
+{0x01ECB1, 0x0002},
+{0x01ECB5, 0x0080},
+{0x01ED01, 0x0002},
+{0x01ED2E, 0x0040},
+{0x01ED2F, 0x0002},
+{0x01ED3E, 0x0080},
+{0x01EE00, 0x0004},
+{0x01EE04, 0x0080},
+{0x01EE05, 0x0004},
+{0x01EE20, 0x0080},
+{0x01EE21, 0x0004},
+{0x01EE23, 0x0080},
+{0x01EE24, 0x0004},
+{0x01EE25, 0x0080},
+{0x01EE27, 0x0004},
+{0x01EE28, 0x0080},
+{0x01EE29, 0x0004},
+{0x01EE33, 0x0080},
+{0x01EE34, 0x0004},
+{0x01EE38, 0x0080},
+{0x01EE39, 0x0004},
+{0x01EE3A, 0x0080},
+{0x01EE3B, 0x0004},
+{0x01EE3C, 0x0080},
+{0x01EE42, 0x0004},
+{0x01EE43, 0x0080},
+{0x01EE47, 0x0004},
+{0x01EE48, 0x0080},
+{0x01EE49, 0x0004},
+{0x01EE4A, 0x0080},
+{0x01EE4B, 0x0004},
+{0x01EE4C, 0x0080},
+{0x01EE4D, 0x0004},
+{0x01EE50, 0x0080},
+{0x01EE51, 0x0004},
+{0x01EE53, 0x0080},
+{0x01EE54, 0x0004},
+{0x01EE55, 0x0080},
+{0x01EE57, 0x0004},
+{0x01EE58, 0x0080},
+{0x01EE59, 0x0004},
+{0x01EE5A, 0x0080},
+{0x01EE5B, 0x0004},
+{0x01EE5C, 0x0080},
+{0x01EE5D, 0x0004},
+{0x01EE5E, 0x0080},
+{0x01EE5F, 0x0004},
+{0x01EE60, 0x0080},
+{0x01EE61, 0x0004},
+{0x01EE63, 0x0080},
+{0x01EE64, 0x0004},
+{0x01EE65, 0x0080},
+{0x01EE67, 0x0004},
+{0x01EE6B, 0x0080},
+{0x01EE6C, 0x0004},
+{0x01EE73, 0x0080},
+{0x01EE74, 0x0004},
+{0x01EE78, 0x0080},
+{0x01EE79, 0x0004},
+{0x01EE7D, 0x0080},
+{0x01EE7E, 0x0004},
+{0x01EE7F, 0x0080},
+{0x01EE80, 0x0004},
+{0x01EE8A, 0x0080},
+{0x01EE8B, 0x0004},
+{0x01EE9C, 0x0080},
+{0x01EEA1, 0x0004},
+{0x01EEA4, 0x0080},
+{0x01EEA5, 0x0004},
+{0x01EEAA, 0x0080},
+{0x01EEAB, 0x0004},
+{0x01EEBC, 0x0080},
+{0x01EEF0, 0x0040},
+{0x01EEF2, 0x0080},
+{0x01F000, 0x0040},
+{0x01F02C, 0x0080},
+{0x01F030, 0x0040},
+{0x01F094, 0x0080},
+{0x01F0A0, 0x0040},
+{0x01F0AF, 0x0080},
+{0x01F0B1, 0x0040},
+{0x01F0C0, 0x0080},
+{0x01F0C1, 0x0040},
+{0x01F0D0, 0x0080},
+{0x01F0D1, 0x0040},
+{0x01F0F6, 0x0080},
+{0x01F100, 0x0002},
+{0x01F10D, 0x0040},
+{0x01F1AE, 0x0080},
+{0x01F1E6, 0x0040},
+{0x01F203, 0x0080},
+{0x01F210, 0x0040},
+{0x01F23C, 0x0080},
+{0x01F240, 0x0040},
+{0x01F249, 0x0080},
+{0x01F250, 0x0040},
+{0x01F252, 0x0080},
+{0x01F260, 0x0040},
+{0x01F266, 0x0080},
+{0x01F300, 0x0040},
+{0x01F6D8, 0x0080},
+{0x01F6DC, 0x0040},
+{0x01F6ED, 0x0080},
+{0x01F6F0, 0x0040},
+{0x01F6FD, 0x0080},
+{0x01F700, 0x0040},
+{0x01F777, 0x0080},
+{0x01F77B, 0x0040},
+{0x01F7DA, 0x0080},
+{0x01F7E0, 0x0040},
+{0x01F7EC, 0x0080},
+{0x01F7F0, 0x0040},
+{0x01F7F1, 0x0080},
+{0x01F800, 0x0040},
+{0x01F80C, 0x0080},
+{0x01F810, 0x0040},
+{0x01F848, 0x0080},
+{0x01F850, 0x0040},
+{0x01F85A, 0x0080},
+{0x01F860, 0x0040},
+{0x01F888, 0x0080},
+{0x01F890, 0x0040},
+{0x01F8AE, 0x0080},
+{0x01F8B0, 0x0040},
+{0x01F8B2, 0x0080},
+{0x01F900, 0x0040},
+{0x01FA54, 0x0080},
+{0x01FA60, 0x0040},
+{0x01FA6E, 0x0080},
+{0x01FA70, 0x0040},
+{0x01FA7D, 0x0080},
+{0x01FA80, 0x0040},
+{0x01FA89, 0x0080},
+{0x01FA90, 0x0040},
+{0x01FABE, 0x0080},
+{0x01FABF, 0x0040},
+{0x01FAC6, 0x0080},
+{0x01FACE, 0x0040},
+{0x01FADC, 0x0080},
+{0x01FAE0, 0x0040},
+{0x01FAE9, 0x0080},
+{0x01FAF0, 0x0040},
+{0x01FAF9, 0x0080},
+{0x01FB00, 0x0040},
+{0x01FB93, 0x0080},
+{0x01FB94, 0x0040},
+{0x01FBCB, 0x0080},
+{0x01FBF0, 0x0002},
+{0x01FBFA, 0x0080},
+{0x020000, 0x0004},
+{0x02A6E0, 0x0080},
+{0x02A700, 0x0004},
+{0x02B73A, 0x0080},
+{0x02B740, 0x0004},
+{0x02B81E, 0x0080},
+{0x02B820, 0x0004},
+{0x02CEA2, 0x0080},
+{0x02CEB0, 0x0004},
+{0x02EBE1, 0x0080},
+{0x02EBF0, 0x0004},
+{0x02EE5E, 0x0080},
+{0x02F800, 0x0004},
+{0x02FA1E, 0x0080},
+{0x030000, 0x0004},
+{0x03134B, 0x0080},
+{0x031350, 0x0004},
+{0x0323B0, 0x0080},
+{0x0E0100, 0x0010},
+{0x0E01F0, 0x0080},
+{0x110000, 0x0000},
 };
 
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_letter = {
-{0x00000041, 0x0000005A}, {0x00000061, 0x0000007A}, {0x000000AA, 0x000000AA}, {0x000000B5, 0x000000B5},
-{0x000000BA, 0x000000BA}, {0x000000C0, 0x000000D6}, {0x000000D8, 0x000000F6}, {0x000000F8, 0x000002C1},
-{0x000002C6, 0x000002D1}, {0x000002E0, 0x000002E4}, {0x000002EC, 0x000002EC}, {0x000002EE, 0x000002EE},
-{0x00000370, 0x00000374}, {0x00000376, 0x00000377}, {0x0000037A, 0x0000037D}, {0x0000037F, 0x0000037F},
-{0x00000386, 0x00000386}, {0x00000388, 0x0000038A}, {0x0000038C, 0x0000038C}, {0x0000038E, 0x000003A1},
-{0x000003A3, 0x000003F5}, {0x000003F7, 0x00000481}, {0x0000048A, 0x0000052F}, {0x00000531, 0x00000556},
-{0x00000559, 0x00000559}, {0x00000560, 0x00000588}, {0x000005D0, 0x000005EA}, {0x000005EF, 0x000005F2},
-{0x00000620, 0x0000064A}, {0x0000066E, 0x0000066F}, {0x00000671, 0x000006D3}, {0x000006D5, 0x000006D5},
-{0x000006E5, 0x000006E6}, {0x000006EE, 0x000006EF}, {0x000006FA, 0x000006FC}, {0x000006FF, 0x000006FF},
-{0x00000710, 0x00000710}, {0x00000712, 0x0000072F}, {0x0000074D, 0x000007A5}, {0x000007B1, 0x000007B1},
-{0x000007CA, 0x000007EA}, {0x000007F4, 0x000007F5}, {0x000007FA, 0x000007FA}, {0x00000800, 0x00000815},
-{0x0000081A, 0x0000081A}, {0x00000824, 0x00000824}, {0x00000828, 0x00000828}, {0x00000840, 0x00000858},
-{0x00000860, 0x0000086A}, {0x00000870, 0x00000887}, {0x00000889, 0x0000088E}, {0x000008A0, 0x000008C9},
-{0x00000904, 0x00000939}, {0x0000093D, 0x0000093D}, {0x00000950, 0x00000950}, {0x00000958, 0x00000961},
-{0x00000971, 0x00000980}, {0x00000985, 0x0000098C}, {0x0000098F, 0x00000990}, {0x00000993, 0x000009A8},
-{0x000009AA, 0x000009B0}, {0x000009B2, 0x000009B2}, {0x000009B6, 0x000009B9}, {0x000009BD, 0x000009BD},
-{0x000009CE, 0x000009CE}, {0x000009DC, 0x000009DD}, {0x000009DF, 0x000009E1}, {0x000009F0, 0x000009F1},
-{0x000009FC, 0x000009FC}, {0x00000A05, 0x00000A0A}, {0x00000A0F, 0x00000A10}, {0x00000A13, 0x00000A28},
-{0x00000A2A, 0x00000A30}, {0x00000A32, 0x00000A33}, {0x00000A35, 0x00000A36}, {0x00000A38, 0x00000A39},
-{0x00000A59, 0x00000A5C}, {0x00000A5E, 0x00000A5E}, {0x00000A72, 0x00000A74}, {0x00000A85, 0x00000A8D},
-{0x00000A8F, 0x00000A91}, {0x00000A93, 0x00000AA8}, {0x00000AAA, 0x00000AB0}, {0x00000AB2, 0x00000AB3},
-{0x00000AB5, 0x00000AB9}, {0x00000ABD, 0x00000ABD}, {0x00000AD0, 0x00000AD0}, {0x00000AE0, 0x00000AE1},
-{0x00000AF9, 0x00000AF9}, {0x00000B05, 0x00000B0C}, {0x00000B0F, 0x00000B10}, {0x00000B13, 0x00000B28},
-{0x00000B2A, 0x00000B30}, {0x00000B32, 0x00000B33}, {0x00000B35, 0x00000B39}, {0x00000B3D, 0x00000B3D},
-{0x00000B5C, 0x00000B5D}, {0x00000B5F, 0x00000B61}, {0x00000B71, 0x00000B71}, {0x00000B83, 0x00000B83},
-{0x00000B85, 0x00000B8A}, {0x00000B8E, 0x00000B90}, {0x00000B92, 0x00000B95}, {0x00000B99, 0x00000B9A},
-{0x00000B9C, 0x00000B9C}, {0x00000B9E, 0x00000B9F}, {0x00000BA3, 0x00000BA4}, {0x00000BA8, 0x00000BAA},
-{0x00000BAE, 0x00000BB9}, {0x00000BD0, 0x00000BD0}, {0x00000C05, 0x00000C0C}, {0x00000C0E, 0x00000C10},
-{0x00000C12, 0x00000C28}, {0x00000C2A, 0x00000C39}, {0x00000C3D, 0x00000C3D}, {0x00000C58, 0x00000C5A},
-{0x00000C5D, 0x00000C5D}, {0x00000C60, 0x00000C61}, {0x00000C80, 0x00000C80}, {0x00000C85, 0x00000C8C},
-{0x00000C8E, 0x00000C90}, {0x00000C92, 0x00000CA8}, {0x00000CAA, 0x00000CB3}, {0x00000CB5, 0x00000CB9},
-{0x00000CBD, 0x00000CBD}, {0x00000CDD, 0x00000CDE}, {0x00000CE0, 0x00000CE1}, {0x00000CF1, 0x00000CF2},
-{0x00000D04, 0x00000D0C}, {0x00000D0E, 0x00000D10}, {0x00000D12, 0x00000D3A}, {0x00000D3D, 0x00000D3D},
-{0x00000D4E, 0x00000D4E}, {0x00000D54, 0x00000D56}, {0x00000D5F, 0x00000D61}, {0x00000D7A, 0x00000D7F},
-{0x00000D85, 0x00000D96}, {0x00000D9A, 0x00000DB1}, {0x00000DB3, 0x00000DBB}, {0x00000DBD, 0x00000DBD},
-{0x00000DC0, 0x00000DC6}, {0x00000E01, 0x00000E30}, {0x00000E32, 0x00000E33}, {0x00000E40, 0x00000E46},
-{0x00000E81, 0x00000E82}, {0x00000E84, 0x00000E84}, {0x00000E86, 0x00000E8A}, {0x00000E8C, 0x00000EA3},
-{0x00000EA5, 0x00000EA5}, {0x00000EA7, 0x00000EB0}, {0x00000EB2, 0x00000EB3}, {0x00000EBD, 0x00000EBD},
-{0x00000EC0, 0x00000EC4}, {0x00000EC6, 0x00000EC6}, {0x00000EDC, 0x00000EDF}, {0x00000F00, 0x00000F00},
-{0x00000F40, 0x00000F47}, {0x00000F49, 0x00000F6C}, {0x00000F88, 0x00000F8C}, {0x00001000, 0x0000102A},
-{0x0000103F, 0x0000103F}, {0x00001050, 0x00001055}, {0x0000105A, 0x0000105D}, {0x00001061, 0x00001061},
-{0x00001065, 0x00001066}, {0x0000106E, 0x00001070}, {0x00001075, 0x00001081}, {0x0000108E, 0x0000108E},
-{0x000010A0, 0x000010C5}, {0x000010C7, 0x000010C7}, {0x000010CD, 0x000010CD}, {0x000010D0, 0x000010FA},
-{0x000010FC, 0x00001248}, {0x0000124A, 0x0000124D}, {0x00001250, 0x00001256}, {0x00001258, 0x00001258},
-{0x0000125A, 0x0000125D}, {0x00001260, 0x00001288}, {0x0000128A, 0x0000128D}, {0x00001290, 0x000012B0},
-{0x000012B2, 0x000012B5}, {0x000012B8, 0x000012BE}, {0x000012C0, 0x000012C0}, {0x000012C2, 0x000012C5},
-{0x000012C8, 0x000012D6}, {0x000012D8, 0x00001310}, {0x00001312, 0x00001315}, {0x00001318, 0x0000135A},
-{0x00001380, 0x0000138F}, {0x000013A0, 0x000013F5}, {0x000013F8, 0x000013FD}, {0x00001401, 0x0000166C},
-{0x0000166F, 0x0000167F}, {0x00001681, 0x0000169A}, {0x000016A0, 0x000016EA}, {0x000016F1, 0x000016F8},
-{0x00001700, 0x00001711}, {0x0000171F, 0x00001731}, {0x00001740, 0x00001751}, {0x00001760, 0x0000176C},
-{0x0000176E, 0x00001770}, {0x00001780, 0x000017B3}, {0x000017D7, 0x000017D7}, {0x000017DC, 0x000017DC},
-{0x00001820, 0x00001878}, {0x00001880, 0x00001884}, {0x00001887, 0x000018A8}, {0x000018AA, 0x000018AA},
-{0x000018B0, 0x000018F5}, {0x00001900, 0x0000191E}, {0x00001950, 0x0000196D}, {0x00001970, 0x00001974},
-{0x00001980, 0x000019AB}, {0x000019B0, 0x000019C9}, {0x00001A00, 0x00001A16}, {0x00001A20, 0x00001A54},
-{0x00001AA7, 0x00001AA7}, {0x00001B05, 0x00001B33}, {0x00001B45, 0x00001B4C}, {0x00001B83, 0x00001BA0},
-{0x00001BAE, 0x00001BAF}, {0x00001BBA, 0x00001BE5}, {0x00001C00, 0x00001C23}, {0x00001C4D, 0x00001C4F},
-{0x00001C5A, 0x00001C7D}, {0x00001C80, 0x00001C88}, {0x00001C90, 0x00001CBA}, {0x00001CBD, 0x00001CBF},
-{0x00001CE9, 0x00001CEC}, {0x00001CEE, 0x00001CF3}, {0x00001CF5, 0x00001CF6}, {0x00001CFA, 0x00001CFA},
-{0x00001D00, 0x00001DBF}, {0x00001E00, 0x00001F15}, {0x00001F18, 0x00001F1D}, {0x00001F20, 0x00001F45},
-{0x00001F48, 0x00001F4D}, {0x00001F50, 0x00001F57}, {0x00001F59, 0x00001F59}, {0x00001F5B, 0x00001F5B},
-{0x00001F5D, 0x00001F5D}, {0x00001F5F, 0x00001F7D}, {0x00001F80, 0x00001FB4}, {0x00001FB6, 0x00001FBC},
-{0x00001FBE, 0x00001FBE}, {0x00001FC2, 0x00001FC4}, {0x00001FC6, 0x00001FCC}, {0x00001FD0, 0x00001FD3},
-{0x00001FD6, 0x00001FDB}, {0x00001FE0, 0x00001FEC}, {0x00001FF2, 0x00001FF4}, {0x00001FF6, 0x00001FFC},
-{0x00002071, 0x00002071}, {0x0000207F, 0x0000207F}, {0x00002090, 0x0000209C}, {0x00002102, 0x00002102},
-{0x00002107, 0x00002107}, {0x0000210A, 0x00002113}, {0x00002115, 0x00002115}, {0x00002119, 0x0000211D},
-{0x00002124, 0x00002124}, {0x00002126, 0x00002126}, {0x00002128, 0x00002128}, {0x0000212A, 0x0000212D},
-{0x0000212F, 0x00002139}, {0x0000213C, 0x0000213F}, {0x00002145, 0x00002149}, {0x0000214E, 0x0000214E},
-{0x00002183, 0x00002184}, {0x00002C00, 0x00002CE4}, {0x00002CEB, 0x00002CEE}, {0x00002CF2, 0x00002CF3},
-{0x00002D00, 0x00002D25}, {0x00002D27, 0x00002D27}, {0x00002D2D, 0x00002D2D}, {0x00002D30, 0x00002D67},
-{0x00002D6F, 0x00002D6F}, {0x00002D80, 0x00002D96}, {0x00002DA0, 0x00002DA6}, {0x00002DA8, 0x00002DAE},
-{0x00002DB0, 0x00002DB6}, {0x00002DB8, 0x00002DBE}, {0x00002DC0, 0x00002DC6}, {0x00002DC8, 0x00002DCE},
-{0x00002DD0, 0x00002DD6}, {0x00002DD8, 0x00002DDE}, {0x00002E2F, 0x00002E2F}, {0x00003005, 0x00003006},
-{0x00003031, 0x00003035}, {0x0000303B, 0x0000303C}, {0x00003041, 0x00003096}, {0x0000309D, 0x0000309F},
-{0x000030A1, 0x000030FA}, {0x000030FC, 0x000030FF}, {0x00003105, 0x0000312F}, {0x00003131, 0x0000318E},
-{0x000031A0, 0x000031BF}, {0x000031F0, 0x000031FF}, {0x00003400, 0x00004DBF}, {0x00004E00, 0x0000A48C},
-{0x0000A4D0, 0x0000A4FD}, {0x0000A500, 0x0000A60C}, {0x0000A610, 0x0000A61F}, {0x0000A62A, 0x0000A62B},
-{0x0000A640, 0x0000A66E}, {0x0000A67F, 0x0000A69D}, {0x0000A6A0, 0x0000A6E5}, {0x0000A717, 0x0000A71F},
-{0x0000A722, 0x0000A788}, {0x0000A78B, 0x0000A7CA}, {0x0000A7D0, 0x0000A7D1}, {0x0000A7D3, 0x0000A7D3},
-{0x0000A7D5, 0x0000A7D9}, {0x0000A7F2, 0x0000A801}, {0x0000A803, 0x0000A805}, {0x0000A807, 0x0000A80A},
-{0x0000A80C, 0x0000A822}, {0x0000A840, 0x0000A873}, {0x0000A882, 0x0000A8B3}, {0x0000A8F2, 0x0000A8F7},
-{0x0000A8FB, 0x0000A8FB}, {0x0000A8FD, 0x0000A8FE}, {0x0000A90A, 0x0000A925}, {0x0000A930, 0x0000A946},
-{0x0000A960, 0x0000A97C}, {0x0000A984, 0x0000A9B2}, {0x0000A9CF, 0x0000A9CF}, {0x0000A9E0, 0x0000A9E4},
-{0x0000A9E6, 0x0000A9EF}, {0x0000A9FA, 0x0000A9FE}, {0x0000AA00, 0x0000AA28}, {0x0000AA40, 0x0000AA42},
-{0x0000AA44, 0x0000AA4B}, {0x0000AA60, 0x0000AA76}, {0x0000AA7A, 0x0000AA7A}, {0x0000AA7E, 0x0000AAAF},
-{0x0000AAB1, 0x0000AAB1}, {0x0000AAB5, 0x0000AAB6}, {0x0000AAB9, 0x0000AABD}, {0x0000AAC0, 0x0000AAC0},
-{0x0000AAC2, 0x0000AAC2}, {0x0000AADB, 0x0000AADD}, {0x0000AAE0, 0x0000AAEA}, {0x0000AAF2, 0x0000AAF4},
-{0x0000AB01, 0x0000AB06}, {0x0000AB09, 0x0000AB0E}, {0x0000AB11, 0x0000AB16}, {0x0000AB20, 0x0000AB26},
-{0x0000AB28, 0x0000AB2E}, {0x0000AB30, 0x0000AB5A}, {0x0000AB5C, 0x0000AB69}, {0x0000AB70, 0x0000ABE2},
-{0x0000AC00, 0x0000D7A3}, {0x0000D7B0, 0x0000D7C6}, {0x0000D7CB, 0x0000D7FB}, {0x0000F900, 0x0000FA6D},
-{0x0000FA70, 0x0000FAD9}, {0x0000FB00, 0x0000FB06}, {0x0000FB13, 0x0000FB17}, {0x0000FB1D, 0x0000FB1D},
-{0x0000FB1F, 0x0000FB28}, {0x0000FB2A, 0x0000FB36}, {0x0000FB38, 0x0000FB3C}, {0x0000FB3E, 0x0000FB3E},
-{0x0000FB40, 0x0000FB41}, {0x0000FB43, 0x0000FB44}, {0x0000FB46, 0x0000FBB1}, {0x0000FBD3, 0x0000FD3D},
-{0x0000FD50, 0x0000FD8F}, {0x0000FD92, 0x0000FDC7}, {0x0000FDF0, 0x0000FDFB}, {0x0000FE70, 0x0000FE74},
-{0x0000FE76, 0x0000FEFC}, {0x0000FF21, 0x0000FF3A}, {0x0000FF41, 0x0000FF5A}, {0x0000FF66, 0x0000FFBE},
-{0x0000FFC2, 0x0000FFC7}, {0x0000FFCA, 0x0000FFCF}, {0x0000FFD2, 0x0000FFD7}, {0x0000FFDA, 0x0000FFDC},
-{0x00010000, 0x0001000B}, {0x0001000D, 0x00010026}, {0x00010028, 0x0001003A}, {0x0001003C, 0x0001003D},
-{0x0001003F, 0x0001004D}, {0x00010050, 0x0001005D}, {0x00010080, 0x000100FA}, {0x00010280, 0x0001029C},
-{0x000102A0, 0x000102D0}, {0x00010300, 0x0001031F}, {0x0001032D, 0x00010340}, {0x00010342, 0x00010349},
-{0x00010350, 0x00010375}, {0x00010380, 0x0001039D}, {0x000103A0, 0x000103C3}, {0x000103C8, 0x000103CF},
-{0x00010400, 0x0001049D}, {0x000104B0, 0x000104D3}, {0x000104D8, 0x000104FB}, {0x00010500, 0x00010527},
-{0x00010530, 0x00010563}, {0x00010570, 0x0001057A}, {0x0001057C, 0x0001058A}, {0x0001058C, 0x00010592},
-{0x00010594, 0x00010595}, {0x00010597, 0x000105A1}, {0x000105A3, 0x000105B1}, {0x000105B3, 0x000105B9},
-{0x000105BB, 0x000105BC}, {0x00010600, 0x00010736}, {0x00010740, 0x00010755}, {0x00010760, 0x00010767},
-{0x00010780, 0x00010785}, {0x00010787, 0x000107B0}, {0x000107B2, 0x000107BA}, {0x00010800, 0x00010805},
-{0x00010808, 0x00010808}, {0x0001080A, 0x00010835}, {0x00010837, 0x00010838}, {0x0001083C, 0x0001083C},
-{0x0001083F, 0x00010855}, {0x00010860, 0x00010876}, {0x00010880, 0x0001089E}, {0x000108E0, 0x000108F2},
-{0x000108F4, 0x000108F5}, {0x00010900, 0x00010915}, {0x00010920, 0x00010939}, {0x00010980, 0x000109B7},
-{0x000109BE, 0x000109BF}, {0x00010A00, 0x00010A00}, {0x00010A10, 0x00010A13}, {0x00010A15, 0x00010A17},
-{0x00010A19, 0x00010A35}, {0x00010A60, 0x00010A7C}, {0x00010A80, 0x00010A9C}, {0x00010AC0, 0x00010AC7},
-{0x00010AC9, 0x00010AE4}, {0x00010B00, 0x00010B35}, {0x00010B40, 0x00010B55}, {0x00010B60, 0x00010B72},
-{0x00010B80, 0x00010B91}, {0x00010C00, 0x00010C48}, {0x00010C80, 0x00010CB2}, {0x00010CC0, 0x00010CF2},
-{0x00010D00, 0x00010D23}, {0x00010E80, 0x00010EA9}, {0x00010EB0, 0x00010EB1}, {0x00010F00, 0x00010F1C},
-{0x00010F27, 0x00010F27}, {0x00010F30, 0x00010F45}, {0x00010F70, 0x00010F81}, {0x00010FB0, 0x00010FC4},
-{0x00010FE0, 0x00010FF6}, {0x00011003, 0x00011037}, {0x00011071, 0x00011072}, {0x00011075, 0x00011075},
-{0x00011083, 0x000110AF}, {0x000110D0, 0x000110E8}, {0x00011103, 0x00011126}, {0x00011144, 0x00011144},
-{0x00011147, 0x00011147}, {0x00011150, 0x00011172}, {0x00011176, 0x00011176}, {0x00011183, 0x000111B2},
-{0x000111C1, 0x000111C4}, {0x000111DA, 0x000111DA}, {0x000111DC, 0x000111DC}, {0x00011200, 0x00011211},
-{0x00011213, 0x0001122B}, {0x0001123F, 0x00011240}, {0x00011280, 0x00011286}, {0x00011288, 0x00011288},
-{0x0001128A, 0x0001128D}, {0x0001128F, 0x0001129D}, {0x0001129F, 0x000112A8}, {0x000112B0, 0x000112DE},
-{0x00011305, 0x0001130C}, {0x0001130F, 0x00011310}, {0x00011313, 0x00011328}, {0x0001132A, 0x00011330},
-{0x00011332, 0x00011333}, {0x00011335, 0x00011339}, {0x0001133D, 0x0001133D}, {0x00011350, 0x00011350},
-{0x0001135D, 0x00011361}, {0x00011400, 0x00011434}, {0x00011447, 0x0001144A}, {0x0001145F, 0x00011461},
-{0x00011480, 0x000114AF}, {0x000114C4, 0x000114C5}, {0x000114C7, 0x000114C7}, {0x00011580, 0x000115AE},
-{0x000115D8, 0x000115DB}, {0x00011600, 0x0001162F}, {0x00011644, 0x00011644}, {0x00011680, 0x000116AA},
-{0x000116B8, 0x000116B8}, {0x00011700, 0x0001171A}, {0x00011740, 0x00011746}, {0x00011800, 0x0001182B},
-{0x000118A0, 0x000118DF}, {0x000118FF, 0x00011906}, {0x00011909, 0x00011909}, {0x0001190C, 0x00011913},
-{0x00011915, 0x00011916}, {0x00011918, 0x0001192F}, {0x0001193F, 0x0001193F}, {0x00011941, 0x00011941},
-{0x000119A0, 0x000119A7}, {0x000119AA, 0x000119D0}, {0x000119E1, 0x000119E1}, {0x000119E3, 0x000119E3},
-{0x00011A00, 0x00011A00}, {0x00011A0B, 0x00011A32}, {0x00011A3A, 0x00011A3A}, {0x00011A50, 0x00011A50},
-{0x00011A5C, 0x00011A89}, {0x00011A9D, 0x00011A9D}, {0x00011AB0, 0x00011AF8}, {0x00011C00, 0x00011C08},
-{0x00011C0A, 0x00011C2E}, {0x00011C40, 0x00011C40}, {0x00011C72, 0x00011C8F}, {0x00011D00, 0x00011D06},
-{0x00011D08, 0x00011D09}, {0x00011D0B, 0x00011D30}, {0x00011D46, 0x00011D46}, {0x00011D60, 0x00011D65},
-{0x00011D67, 0x00011D68}, {0x00011D6A, 0x00011D89}, {0x00011D98, 0x00011D98}, {0x00011EE0, 0x00011EF2},
-{0x00011F02, 0x00011F02}, {0x00011F04, 0x00011F10}, {0x00011F12, 0x00011F33}, {0x00011FB0, 0x00011FB0},
-{0x00012000, 0x00012399}, {0x00012480, 0x00012543}, {0x00012F90, 0x00012FF0}, {0x00013000, 0x0001342F},
-{0x00013441, 0x00013446}, {0x00014400, 0x00014646}, {0x00016800, 0x00016A38}, {0x00016A40, 0x00016A5E},
-{0x00016A70, 0x00016ABE}, {0x00016AD0, 0x00016AED}, {0x00016B00, 0x00016B2F}, {0x00016B40, 0x00016B43},
-{0x00016B63, 0x00016B77}, {0x00016B7D, 0x00016B8F}, {0x00016E40, 0x00016E7F}, {0x00016F00, 0x00016F4A},
-{0x00016F50, 0x00016F50}, {0x00016F93, 0x00016F9F}, {0x00016FE0, 0x00016FE1}, {0x00016FE3, 0x00016FE3},
-{0x00017000, 0x000187F7}, {0x00018800, 0x00018CD5}, {0x00018D00, 0x00018D08}, {0x0001AFF0, 0x0001AFF3},
-{0x0001AFF5, 0x0001AFFB}, {0x0001AFFD, 0x0001AFFE}, {0x0001B000, 0x0001B122}, {0x0001B132, 0x0001B132},
-{0x0001B150, 0x0001B152}, {0x0001B155, 0x0001B155}, {0x0001B164, 0x0001B167}, {0x0001B170, 0x0001B2FB},
-{0x0001BC00, 0x0001BC6A}, {0x0001BC70, 0x0001BC7C}, {0x0001BC80, 0x0001BC88}, {0x0001BC90, 0x0001BC99},
-{0x0001D400, 0x0001D454}, {0x0001D456, 0x0001D49C}, {0x0001D49E, 0x0001D49F}, {0x0001D4A2, 0x0001D4A2},
-{0x0001D4A5, 0x0001D4A6}, {0x0001D4A9, 0x0001D4AC}, {0x0001D4AE, 0x0001D4B9}, {0x0001D4BB, 0x0001D4BB},
-{0x0001D4BD, 0x0001D4C3}, {0x0001D4C5, 0x0001D505}, {0x0001D507, 0x0001D50A}, {0x0001D50D, 0x0001D514},
-{0x0001D516, 0x0001D51C}, {0x0001D51E, 0x0001D539}, {0x0001D53B, 0x0001D53E}, {0x0001D540, 0x0001D544},
-{0x0001D546, 0x0001D546}, {0x0001D54A, 0x0001D550}, {0x0001D552, 0x0001D6A5}, {0x0001D6A8, 0x0001D6C0},
-{0x0001D6C2, 0x0001D6DA}, {0x0001D6DC, 0x0001D6FA}, {0x0001D6FC, 0x0001D714}, {0x0001D716, 0x0001D734},
-{0x0001D736, 0x0001D74E}, {0x0001D750, 0x0001D76E}, {0x0001D770, 0x0001D788}, {0x0001D78A, 0x0001D7A8},
-{0x0001D7AA, 0x0001D7C2}, {0x0001D7C4, 0x0001D7CB}, {0x0001DF00, 0x0001DF1E}, {0x0001DF25, 0x0001DF2A},
-{0x0001E030, 0x0001E06D}, {0x0001E100, 0x0001E12C}, {0x0001E137, 0x0001E13D}, {0x0001E14E, 0x0001E14E},
-{0x0001E290, 0x0001E2AD}, {0x0001E2C0, 0x0001E2EB}, {0x0001E4D0, 0x0001E4EB}, {0x0001E7E0, 0x0001E7E6},
-{0x0001E7E8, 0x0001E7EB}, {0x0001E7ED, 0x0001E7EE}, {0x0001E7F0, 0x0001E7FE}, {0x0001E800, 0x0001E8C4},
-{0x0001E900, 0x0001E943}, {0x0001E94B, 0x0001E94B}, {0x0001EE00, 0x0001EE03}, {0x0001EE05, 0x0001EE1F},
-{0x0001EE21, 0x0001EE22}, {0x0001EE24, 0x0001EE24}, {0x0001EE27, 0x0001EE27}, {0x0001EE29, 0x0001EE32},
-{0x0001EE34, 0x0001EE37}, {0x0001EE39, 0x0001EE39}, {0x0001EE3B, 0x0001EE3B}, {0x0001EE42, 0x0001EE42},
-{0x0001EE47, 0x0001EE47}, {0x0001EE49, 0x0001EE49}, {0x0001EE4B, 0x0001EE4B}, {0x0001EE4D, 0x0001EE4F},
-{0x0001EE51, 0x0001EE52}, {0x0001EE54, 0x0001EE54}, {0x0001EE57, 0x0001EE57}, {0x0001EE59, 0x0001EE59},
-{0x0001EE5B, 0x0001EE5B}, {0x0001EE5D, 0x0001EE5D}, {0x0001EE5F, 0x0001EE5F}, {0x0001EE61, 0x0001EE62},
-{0x0001EE64, 0x0001EE64}, {0x0001EE67, 0x0001EE6A}, {0x0001EE6C, 0x0001EE72}, {0x0001EE74, 0x0001EE77},
-{0x0001EE79, 0x0001EE7C}, {0x0001EE7E, 0x0001EE7E}, {0x0001EE80, 0x0001EE89}, {0x0001EE8B, 0x0001EE9B},
-{0x0001EEA1, 0x0001EEA3}, {0x0001EEA5, 0x0001EEA9}, {0x0001EEAB, 0x0001EEBB}, {0x00020000, 0x0002A6DF},
-{0x0002A700, 0x0002B739}, {0x0002B740, 0x0002B81D}, {0x0002B820, 0x0002CEA1}, {0x0002CEB0, 0x0002EBE0},
-{0x0002EBF0, 0x0002EE5D}, {0x0002F800, 0x0002FA1D}, {0x00030000, 0x0003134A}, {0x00031350, 0x000323AF},
+const std::unordered_set<uint32_t> unicode_set_whitespace = {
+0x000009, 0x00000A, 0x00000B, 0x00000C, 0x00000D, 0x000020, 0x000085, 0x0000A0, 0x001680, 0x002000, 0x002001, 0x002002, 0x002003, 0x002004, 0x002005, 0x002006, 0x002007, 0x002008, 0x002009, 0x00200A, 0x002028, 0x002029, 0x00202F, 0x00205F, 0x003000
 };
 
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_separator = {
-{0x00000020, 0x00000020}, {0x000000A0, 0x000000A0}, {0x00001680, 0x00001680}, {0x00002000, 0x0000200A},
-{0x00002028, 0x00002029}, {0x0000202F, 0x0000202F}, {0x0000205F, 0x0000205F}, {0x00003000, 0x00003000},
+const std::unordered_map<uint32_t, uint32_t> unicode_map_lowercase = {
+{0x000041, 0x000061},
+{0x000042, 0x000062},
+{0x000043, 0x000063},
+{0x000044, 0x000064},
+{0x000045, 0x000065},
+{0x000046, 0x000066},
+{0x000047, 0x000067},
+{0x000048, 0x000068},
+{0x000049, 0x000069},
+{0x00004A, 0x00006A},
+{0x00004B, 0x00006B},
+{0x00004C, 0x00006C},
+{0x00004D, 0x00006D},
+{0x00004E, 0x00006E},
+{0x00004F, 0x00006F},
+{0x000050, 0x000070},
+{0x000051, 0x000071},
+{0x000052, 0x000072},
+{0x000053, 0x000073},
+{0x000054, 0x000074},
+{0x000055, 0x000075},
+{0x000056, 0x000076},
+{0x000057, 0x000077},
+{0x000058, 0x000078},
+{0x000059, 0x000079},
+{0x00005A, 0x00007A},
+{0x0000C0, 0x0000E0},
+{0x0000C1, 0x0000E1},
+{0x0000C2, 0x0000E2},
+{0x0000C3, 0x0000E3},
+{0x0000C4, 0x0000E4},
+{0x0000C5, 0x0000E5},
+{0x0000C6, 0x0000E6},
+{0x0000C7, 0x0000E7},
+{0x0000C8, 0x0000E8},
+{0x0000C9, 0x0000E9},
+{0x0000CA, 0x0000EA},
+{0x0000CB, 0x0000EB},
+{0x0000CC, 0x0000EC},
+{0x0000CD, 0x0000ED},
+{0x0000CE, 0x0000EE},
+{0x0000CF, 0x0000EF},
+{0x0000D0, 0x0000F0},
+{0x0000D1, 0x0000F1},
+{0x0000D2, 0x0000F2},
+{0x0000D3, 0x0000F3},
+{0x0000D4, 0x0000F4},
+{0x0000D5, 0x0000F5},
+{0x0000D6, 0x0000F6},
+{0x0000D8, 0x0000F8},
+{0x0000D9, 0x0000F9},
+{0x0000DA, 0x0000FA},
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+{0x00A75C, 0x00A75D},
+{0x00A75E, 0x00A75F},
+{0x00A760, 0x00A761},
+{0x00A762, 0x00A763},
+{0x00A764, 0x00A765},
+{0x00A766, 0x00A767},
+{0x00A768, 0x00A769},
+{0x00A76A, 0x00A76B},
+{0x00A76C, 0x00A76D},
+{0x00A76E, 0x00A76F},
+{0x00A779, 0x00A77A},
+{0x00A77B, 0x00A77C},
+{0x00A77D, 0x001D79},
+{0x00A77E, 0x00A77F},
+{0x00A780, 0x00A781},
+{0x00A782, 0x00A783},
+{0x00A784, 0x00A785},
+{0x00A786, 0x00A787},
+{0x00A78B, 0x00A78C},
+{0x00A78D, 0x000265},
+{0x00A790, 0x00A791},
+{0x00A792, 0x00A793},
+{0x00A796, 0x00A797},
+{0x00A798, 0x00A799},
+{0x00A79A, 0x00A79B},
+{0x00A79C, 0x00A79D},
+{0x00A79E, 0x00A79F},
+{0x00A7A0, 0x00A7A1},
+{0x00A7A2, 0x00A7A3},
+{0x00A7A4, 0x00A7A5},
+{0x00A7A6, 0x00A7A7},
+{0x00A7A8, 0x00A7A9},
+{0x00A7AA, 0x000266},
+{0x00A7AB, 0x00025C},
+{0x00A7AC, 0x000261},
+{0x00A7AD, 0x00026C},
+{0x00A7AE, 0x00026A},
+{0x00A7B0, 0x00029E},
+{0x00A7B1, 0x000287},
+{0x00A7B2, 0x00029D},
+{0x00A7B3, 0x00AB53},
+{0x00A7B4, 0x00A7B5},
+{0x00A7B6, 0x00A7B7},
+{0x00A7B8, 0x00A7B9},
+{0x00A7BA, 0x00A7BB},
+{0x00A7BC, 0x00A7BD},
+{0x00A7BE, 0x00A7BF},
+{0x00A7C2, 0x00A7C3},
+{0x00A7C4, 0x00A794},
+{0x00A7C5, 0x000282},
+{0x00A7C6, 0x001D8E},
+{0x00A7C7, 0x00A7C8},
+{0x00A7C9, 0x00A7CA},
+{0x00A7F5, 0x00A7F6},
+{0x00FF21, 0x00FF41},
+{0x00FF22, 0x00FF42},
+{0x00FF23, 0x00FF43},
+{0x00FF24, 0x00FF44},
+{0x00FF25, 0x00FF45},
+{0x00FF26, 0x00FF46},
+{0x00FF27, 0x00FF47},
+{0x00FF28, 0x00FF48},
+{0x00FF29, 0x00FF49},
+{0x00FF2A, 0x00FF4A},
+{0x00FF2B, 0x00FF4B},
+{0x00FF2C, 0x00FF4C},
+{0x00FF2D, 0x00FF4D},
+{0x00FF2E, 0x00FF4E},
+{0x00FF2F, 0x00FF4F},
+{0x00FF30, 0x00FF50},
+{0x00FF31, 0x00FF51},
+{0x00FF32, 0x00FF52},
+{0x00FF33, 0x00FF53},
+{0x00FF34, 0x00FF54},
+{0x00FF35, 0x00FF55},
+{0x00FF36, 0x00FF56},
+{0x00FF37, 0x00FF57},
+{0x00FF38, 0x00FF58},
+{0x00FF39, 0x00FF59},
+{0x00FF3A, 0x00FF5A},
+{0x010400, 0x010428},
+{0x010401, 0x010429},
+{0x010402, 0x01042A},
+{0x010403, 0x01042B},
+{0x010404, 0x01042C},
+{0x010405, 0x01042D},
+{0x010406, 0x01042E},
+{0x010407, 0x01042F},
+{0x010408, 0x010430},
+{0x010409, 0x010431},
+{0x01040A, 0x010432},
+{0x01040B, 0x010433},
+{0x01040C, 0x010434},
+{0x01040D, 0x010435},
+{0x01040E, 0x010436},
+{0x01040F, 0x010437},
+{0x010410, 0x010438},
+{0x010411, 0x010439},
+{0x010412, 0x01043A},
+{0x010413, 0x01043B},
+{0x010414, 0x01043C},
+{0x010415, 0x01043D},
+{0x010416, 0x01043E},
+{0x010417, 0x01043F},
+{0x010418, 0x010440},
+{0x010419, 0x010441},
+{0x01041A, 0x010442},
+{0x01041B, 0x010443},
+{0x01041C, 0x010444},
+{0x01041D, 0x010445},
+{0x01041E, 0x010446},
+{0x01041F, 0x010447},
+{0x010420, 0x010448},
+{0x010421, 0x010449},
+{0x010422, 0x01044A},
+{0x010423, 0x01044B},
+{0x010424, 0x01044C},
+{0x010425, 0x01044D},
+{0x010426, 0x01044E},
+{0x010427, 0x01044F},
+{0x0104B0, 0x0104D8},
+{0x0104B1, 0x0104D9},
+{0x0104B2, 0x0104DA},
+{0x0104B3, 0x0104DB},
+{0x0104B4, 0x0104DC},
+{0x0104B5, 0x0104DD},
+{0x0104B6, 0x0104DE},
+{0x0104B7, 0x0104DF},
+{0x0104B8, 0x0104E0},
+{0x0104B9, 0x0104E1},
+{0x0104BA, 0x0104E2},
+{0x0104BB, 0x0104E3},
+{0x0104BC, 0x0104E4},
+{0x0104BD, 0x0104E5},
+{0x0104BE, 0x0104E6},
+{0x0104BF, 0x0104E7},
+{0x0104C0, 0x0104E8},
+{0x0104C1, 0x0104E9},
+{0x0104C2, 0x0104EA},
+{0x0104C3, 0x0104EB},
+{0x0104C4, 0x0104EC},
+{0x0104C5, 0x0104ED},
+{0x0104C6, 0x0104EE},
+{0x0104C7, 0x0104EF},
+{0x0104C8, 0x0104F0},
+{0x0104C9, 0x0104F1},
+{0x0104CA, 0x0104F2},
+{0x0104CB, 0x0104F3},
+{0x0104CC, 0x0104F4},
+{0x0104CD, 0x0104F5},
+{0x0104CE, 0x0104F6},
+{0x0104CF, 0x0104F7},
+{0x0104D0, 0x0104F8},
+{0x0104D1, 0x0104F9},
+{0x0104D2, 0x0104FA},
+{0x0104D3, 0x0104FB},
+{0x010C80, 0x010CC0},
+{0x010C81, 0x010CC1},
+{0x010C82, 0x010CC2},
+{0x010C83, 0x010CC3},
+{0x010C84, 0x010CC4},
+{0x010C85, 0x010CC5},
+{0x010C86, 0x010CC6},
+{0x010C87, 0x010CC7},
+{0x010C88, 0x010CC8},
+{0x010C89, 0x010CC9},
+{0x010C8A, 0x010CCA},
+{0x010C8B, 0x010CCB},
+{0x010C8C, 0x010CCC},
+{0x010C8D, 0x010CCD},
+{0x010C8E, 0x010CCE},
+{0x010C8F, 0x010CCF},
+{0x010C90, 0x010CD0},
+{0x010C91, 0x010CD1},
+{0x010C92, 0x010CD2},
+{0x010C93, 0x010CD3},
+{0x010C94, 0x010CD4},
+{0x010C95, 0x010CD5},
+{0x010C96, 0x010CD6},
+{0x010C97, 0x010CD7},
+{0x010C98, 0x010CD8},
+{0x010C99, 0x010CD9},
+{0x010C9A, 0x010CDA},
+{0x010C9B, 0x010CDB},
+{0x010C9C, 0x010CDC},
+{0x010C9D, 0x010CDD},
+{0x010C9E, 0x010CDE},
+{0x010C9F, 0x010CDF},
+{0x010CA0, 0x010CE0},
+{0x010CA1, 0x010CE1},
+{0x010CA2, 0x010CE2},
+{0x010CA3, 0x010CE3},
+{0x010CA4, 0x010CE4},
+{0x010CA5, 0x010CE5},
+{0x010CA6, 0x010CE6},
+{0x010CA7, 0x010CE7},
+{0x010CA8, 0x010CE8},
+{0x010CA9, 0x010CE9},
+{0x010CAA, 0x010CEA},
+{0x010CAB, 0x010CEB},
+{0x010CAC, 0x010CEC},
+{0x010CAD, 0x010CED},
+{0x010CAE, 0x010CEE},
+{0x010CAF, 0x010CEF},
+{0x010CB0, 0x010CF0},
+{0x010CB1, 0x010CF1},
+{0x010CB2, 0x010CF2},
+{0x0118A0, 0x0118C0},
+{0x0118A1, 0x0118C1},
+{0x0118A2, 0x0118C2},
+{0x0118A3, 0x0118C3},
+{0x0118A4, 0x0118C4},
+{0x0118A5, 0x0118C5},
+{0x0118A6, 0x0118C6},
+{0x0118A7, 0x0118C7},
+{0x0118A8, 0x0118C8},
+{0x0118A9, 0x0118C9},
+{0x0118AA, 0x0118CA},
+{0x0118AB, 0x0118CB},
+{0x0118AC, 0x0118CC},
+{0x0118AD, 0x0118CD},
+{0x0118AE, 0x0118CE},
+{0x0118AF, 0x0118CF},
+{0x0118B0, 0x0118D0},
+{0x0118B1, 0x0118D1},
+{0x0118B2, 0x0118D2},
+{0x0118B3, 0x0118D3},
+{0x0118B4, 0x0118D4},
+{0x0118B5, 0x0118D5},
+{0x0118B6, 0x0118D6},
+{0x0118B7, 0x0118D7},
+{0x0118B8, 0x0118D8},
+{0x0118B9, 0x0118D9},
+{0x0118BA, 0x0118DA},
+{0x0118BB, 0x0118DB},
+{0x0118BC, 0x0118DC},
+{0x0118BD, 0x0118DD},
+{0x0118BE, 0x0118DE},
+{0x0118BF, 0x0118DF},
+{0x016E40, 0x016E60},
+{0x016E41, 0x016E61},
+{0x016E42, 0x016E62},
+{0x016E43, 0x016E63},
+{0x016E44, 0x016E64},
+{0x016E45, 0x016E65},
+{0x016E46, 0x016E66},
+{0x016E47, 0x016E67},
+{0x016E48, 0x016E68},
+{0x016E49, 0x016E69},
+{0x016E4A, 0x016E6A},
+{0x016E4B, 0x016E6B},
+{0x016E4C, 0x016E6C},
+{0x016E4D, 0x016E6D},
+{0x016E4E, 0x016E6E},
+{0x016E4F, 0x016E6F},
+{0x016E50, 0x016E70},
+{0x016E51, 0x016E71},
+{0x016E52, 0x016E72},
+{0x016E53, 0x016E73},
+{0x016E54, 0x016E74},
+{0x016E55, 0x016E75},
+{0x016E56, 0x016E76},
+{0x016E57, 0x016E77},
+{0x016E58, 0x016E78},
+{0x016E59, 0x016E79},
+{0x016E5A, 0x016E7A},
+{0x016E5B, 0x016E7B},
+{0x016E5C, 0x016E7C},
+{0x016E5D, 0x016E7D},
+{0x016E5E, 0x016E7E},
+{0x016E5F, 0x016E7F},
+{0x01E900, 0x01E922},
+{0x01E901, 0x01E923},
+{0x01E902, 0x01E924},
+{0x01E903, 0x01E925},
+{0x01E904, 0x01E926},
+{0x01E905, 0x01E927},
+{0x01E906, 0x01E928},
+{0x01E907, 0x01E929},
+{0x01E908, 0x01E92A},
+{0x01E909, 0x01E92B},
+{0x01E90A, 0x01E92C},
+{0x01E90B, 0x01E92D},
+{0x01E90C, 0x01E92E},
+{0x01E90D, 0x01E92F},
+{0x01E90E, 0x01E930},
+{0x01E90F, 0x01E931},
+{0x01E910, 0x01E932},
+{0x01E911, 0x01E933},
+{0x01E912, 0x01E934},
+{0x01E913, 0x01E935},
+{0x01E914, 0x01E936},
+{0x01E915, 0x01E937},
+{0x01E916, 0x01E938},
+{0x01E917, 0x01E939},
+{0x01E918, 0x01E93A},
+{0x01E919, 0x01E93B},
+{0x01E91A, 0x01E93C},
+{0x01E91B, 0x01E93D},
+{0x01E91C, 0x01E93E},
+{0x01E91D, 0x01E93F},
+{0x01E91E, 0x01E940},
+{0x01E91F, 0x01E941},
+{0x01E920, 0x01E942},
+{0x01E921, 0x01E943},
 };
 
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_whitespace = {
-{0x00000009, 0x0000000D}, {0x00000020, 0x00000020}, {0x00000085, 0x00000085}, {0x000000A0, 0x000000A0},
-{0x00001680, 0x00001680}, {0x00002000, 0x0000200A}, {0x00002028, 0x00002029}, {0x0000202F, 0x0000202F},
-{0x0000205F, 0x0000205F}, {0x00003000, 0x00003000},
+const std::unordered_map<uint32_t, uint32_t> unicode_map_uppercase = {
+{0x000061, 0x000041},
+{0x000062, 0x000042},
+{0x000063, 0x000043},
+{0x000064, 0x000044},
+{0x000065, 0x000045},
+{0x000066, 0x000046},
+{0x000067, 0x000047},
+{0x000068, 0x000048},
+{0x000069, 0x000049},
+{0x00006A, 0x00004A},
+{0x00006B, 0x00004B},
+{0x00006C, 0x00004C},
+{0x00006D, 0x00004D},
+{0x00006E, 0x00004E},
+{0x00006F, 0x00004F},
+{0x000070, 0x000050},
+{0x000071, 0x000051},
+{0x000072, 0x000052},
+{0x000073, 0x000053},
+{0x000074, 0x000054},
+{0x000075, 0x000055},
+{0x000076, 0x000056},
+{0x000077, 0x000057},
+{0x000078, 0x000058},
+{0x000079, 0x000059},
+{0x00007A, 0x00005A},
+{0x0000B5, 0x00039C},
+{0x0000DF, 0x000053},
+{0x0000E0, 0x0000C0},
+{0x0000E1, 0x0000C1},
+{0x0000E2, 0x0000C2},
+{0x0000E3, 0x0000C3},
+{0x0000E4, 0x0000C4},
+{0x0000E5, 0x0000C5},
+{0x0000E6, 0x0000C6},
+{0x0000E7, 0x0000C7},
+{0x0000E8, 0x0000C8},
+{0x0000E9, 0x0000C9},
+{0x0000EA, 0x0000CA},
+{0x0000EB, 0x0000CB},
+{0x0000EC, 0x0000CC},
+{0x0000ED, 0x0000CD},
+{0x0000EE, 0x0000CE},
+{0x0000EF, 0x0000CF},
+{0x0000F0, 0x0000D0},
+{0x0000F1, 0x0000D1},
+{0x0000F2, 0x0000D2},
+{0x0000F3, 0x0000D3},
+{0x0000F4, 0x0000D4},
+{0x0000F5, 0x0000D5},
+{0x0000F6, 0x0000D6},
+{0x0000F8, 0x0000D8},
+{0x0000F9, 0x0000D9},
+{0x0000FA, 0x0000DA},
+{0x0000FB, 0x0000DB},
+{0x0000FC, 0x0000DC},
+{0x0000FD, 0x0000DD},
+{0x0000FE, 0x0000DE},
+{0x0000FF, 0x000178},
+{0x000101, 0x000100},
+{0x000103, 0x000102},
+{0x000105, 0x000104},
+{0x000107, 0x000106},
+{0x000109, 0x000108},
+{0x00010B, 0x00010A},
+{0x00010D, 0x00010C},
+{0x00010F, 0x00010E},
+{0x000111, 0x000110},
+{0x000113, 0x000112},
+{0x000115, 0x000114},
+{0x000117, 0x000116},
+{0x000119, 0x000118},
+{0x00011B, 0x00011A},
+{0x00011D, 0x00011C},
+{0x00011F, 0x00011E},
+{0x000121, 0x000120},
+{0x000123, 0x000122},
+{0x000125, 0x000124},
+{0x000127, 0x000126},
+{0x000129, 0x000128},
+{0x00012B, 0x00012A},
+{0x00012D, 0x00012C},
+{0x00012F, 0x00012E},
+{0x000131, 0x000049},
+{0x000133, 0x000132},
+{0x000135, 0x000134},
+{0x000137, 0x000136},
+{0x00013A, 0x000139},
+{0x00013C, 0x00013B},
+{0x00013E, 0x00013D},
+{0x000140, 0x00013F},
+{0x000142, 0x000141},
+{0x000144, 0x000143},
+{0x000146, 0x000145},
+{0x000148, 0x000147},
+{0x000149, 0x0002BC},
+{0x00014B, 0x00014A},
+{0x00014D, 0x00014C},
+{0x00014F, 0x00014E},
+{0x000151, 0x000150},
+{0x000153, 0x000152},
+{0x000155, 0x000154},
+{0x000157, 0x000156},
+{0x000159, 0x000158},
+{0x00015B, 0x00015A},
+{0x00015D, 0x00015C},
+{0x00015F, 0x00015E},
+{0x000161, 0x000160},
+{0x000163, 0x000162},
+{0x000165, 0x000164},
+{0x000167, 0x000166},
+{0x000169, 0x000168},
+{0x00016B, 0x00016A},
+{0x00016D, 0x00016C},
+{0x00016F, 0x00016E},
+{0x000171, 0x000170},
+{0x000173, 0x000172},
+{0x000175, 0x000174},
+{0x000177, 0x000176},
+{0x00017A, 0x000179},
+{0x00017C, 0x00017B},
+{0x00017E, 0x00017D},
+{0x00017F, 0x000053},
+{0x000180, 0x000243},
+{0x000183, 0x000182},
+{0x000185, 0x000184},
+{0x000188, 0x000187},
+{0x00018C, 0x00018B},
+{0x000192, 0x000191},
+{0x000195, 0x0001F6},
+{0x000199, 0x000198},
+{0x00019A, 0x00023D},
+{0x00019E, 0x000220},
+{0x0001A1, 0x0001A0},
+{0x0001A3, 0x0001A2},
+{0x0001A5, 0x0001A4},
+{0x0001A8, 0x0001A7},
+{0x0001AD, 0x0001AC},
+{0x0001B0, 0x0001AF},
+{0x0001B4, 0x0001B3},
+{0x0001B6, 0x0001B5},
+{0x0001B9, 0x0001B8},
+{0x0001BD, 0x0001BC},
+{0x0001BF, 0x0001F7},
+{0x0001C5, 0x0001C4},
+{0x0001C6, 0x0001C4},
+{0x0001C8, 0x0001C7},
+{0x0001C9, 0x0001C7},
+{0x0001CB, 0x0001CA},
+{0x0001CC, 0x0001CA},
+{0x0001CE, 0x0001CD},
+{0x0001D0, 0x0001CF},
+{0x0001D2, 0x0001D1},
+{0x0001D4, 0x0001D3},
+{0x0001D6, 0x0001D5},
+{0x0001D8, 0x0001D7},
+{0x0001DA, 0x0001D9},
+{0x0001DC, 0x0001DB},
+{0x0001DD, 0x00018E},
+{0x0001DF, 0x0001DE},
+{0x0001E1, 0x0001E0},
+{0x0001E3, 0x0001E2},
+{0x0001E5, 0x0001E4},
+{0x0001E7, 0x0001E6},
+{0x0001E9, 0x0001E8},
+{0x0001EB, 0x0001EA},
+{0x0001ED, 0x0001EC},
+{0x0001EF, 0x0001EE},
+{0x0001F0, 0x00004A},
+{0x0001F2, 0x0001F1},
+{0x0001F3, 0x0001F1},
+{0x0001F5, 0x0001F4},
+{0x0001F9, 0x0001F8},
+{0x0001FB, 0x0001FA},
+{0x0001FD, 0x0001FC},
+{0x0001FF, 0x0001FE},
+{0x000201, 0x000200},
+{0x000203, 0x000202},
+{0x000205, 0x000204},
+{0x000207, 0x000206},
+{0x000209, 0x000208},
+{0x00020B, 0x00020A},
+{0x00020D, 0x00020C},
+{0x00020F, 0x00020E},
+{0x000211, 0x000210},
+{0x000213, 0x000212},
+{0x000215, 0x000214},
+{0x000217, 0x000216},
+{0x000219, 0x000218},
+{0x00021B, 0x00021A},
+{0x00021D, 0x00021C},
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+{0x00ABB5, 0x0013E5},
+{0x00ABB6, 0x0013E6},
+{0x00ABB7, 0x0013E7},
+{0x00ABB8, 0x0013E8},
+{0x00ABB9, 0x0013E9},
+{0x00ABBA, 0x0013EA},
+{0x00ABBB, 0x0013EB},
+{0x00ABBC, 0x0013EC},
+{0x00ABBD, 0x0013ED},
+{0x00ABBE, 0x0013EE},
+{0x00ABBF, 0x0013EF},
+{0x00FB00, 0x000046},
+{0x00FB01, 0x000046},
+{0x00FB02, 0x000046},
+{0x00FB03, 0x000046},
+{0x00FB04, 0x000046},
+{0x00FB05, 0x000053},
+{0x00FB06, 0x000053},
+{0x00FB13, 0x000544},
+{0x00FB14, 0x000544},
+{0x00FB15, 0x000544},
+{0x00FB16, 0x00054E},
+{0x00FB17, 0x000544},
+{0x00FF41, 0x00FF21},
+{0x00FF42, 0x00FF22},
+{0x00FF43, 0x00FF23},
+{0x00FF44, 0x00FF24},
+{0x00FF45, 0x00FF25},
+{0x00FF46, 0x00FF26},
+{0x00FF47, 0x00FF27},
+{0x00FF48, 0x00FF28},
+{0x00FF49, 0x00FF29},
+{0x00FF4A, 0x00FF2A},
+{0x00FF4B, 0x00FF2B},
+{0x00FF4C, 0x00FF2C},
+{0x00FF4D, 0x00FF2D},
+{0x00FF4E, 0x00FF2E},
+{0x00FF4F, 0x00FF2F},
+{0x00FF50, 0x00FF30},
+{0x00FF51, 0x00FF31},
+{0x00FF52, 0x00FF32},
+{0x00FF53, 0x00FF33},
+{0x00FF54, 0x00FF34},
+{0x00FF55, 0x00FF35},
+{0x00FF56, 0x00FF36},
+{0x00FF57, 0x00FF37},
+{0x00FF58, 0x00FF38},
+{0x00FF59, 0x00FF39},
+{0x00FF5A, 0x00FF3A},
+{0x010428, 0x010400},
+{0x010429, 0x010401},
+{0x01042A, 0x010402},
+{0x01042B, 0x010403},
+{0x01042C, 0x010404},
+{0x01042D, 0x010405},
+{0x01042E, 0x010406},
+{0x01042F, 0x010407},
+{0x010430, 0x010408},
+{0x010431, 0x010409},
+{0x010432, 0x01040A},
+{0x010433, 0x01040B},
+{0x010434, 0x01040C},
+{0x010435, 0x01040D},
+{0x010436, 0x01040E},
+{0x010437, 0x01040F},
+{0x010438, 0x010410},
+{0x010439, 0x010411},
+{0x01043A, 0x010412},
+{0x01043B, 0x010413},
+{0x01043C, 0x010414},
+{0x01043D, 0x010415},
+{0x01043E, 0x010416},
+{0x01043F, 0x010417},
+{0x010440, 0x010418},
+{0x010441, 0x010419},
+{0x010442, 0x01041A},
+{0x010443, 0x01041B},
+{0x010444, 0x01041C},
+{0x010445, 0x01041D},
+{0x010446, 0x01041E},
+{0x010447, 0x01041F},
+{0x010448, 0x010420},
+{0x010449, 0x010421},
+{0x01044A, 0x010422},
+{0x01044B, 0x010423},
+{0x01044C, 0x010424},
+{0x01044D, 0x010425},
+{0x01044E, 0x010426},
+{0x01044F, 0x010427},
+{0x0104D8, 0x0104B0},
+{0x0104D9, 0x0104B1},
+{0x0104DA, 0x0104B2},
+{0x0104DB, 0x0104B3},
+{0x0104DC, 0x0104B4},
+{0x0104DD, 0x0104B5},
+{0x0104DE, 0x0104B6},
+{0x0104DF, 0x0104B7},
+{0x0104E0, 0x0104B8},
+{0x0104E1, 0x0104B9},
+{0x0104E2, 0x0104BA},
+{0x0104E3, 0x0104BB},
+{0x0104E4, 0x0104BC},
+{0x0104E5, 0x0104BD},
+{0x0104E6, 0x0104BE},
+{0x0104E7, 0x0104BF},
+{0x0104E8, 0x0104C0},
+{0x0104E9, 0x0104C1},
+{0x0104EA, 0x0104C2},
+{0x0104EB, 0x0104C3},
+{0x0104EC, 0x0104C4},
+{0x0104ED, 0x0104C5},
+{0x0104EE, 0x0104C6},
+{0x0104EF, 0x0104C7},
+{0x0104F0, 0x0104C8},
+{0x0104F1, 0x0104C9},
+{0x0104F2, 0x0104CA},
+{0x0104F3, 0x0104CB},
+{0x0104F4, 0x0104CC},
+{0x0104F5, 0x0104CD},
+{0x0104F6, 0x0104CE},
+{0x0104F7, 0x0104CF},
+{0x0104F8, 0x0104D0},
+{0x0104F9, 0x0104D1},
+{0x0104FA, 0x0104D2},
+{0x0104FB, 0x0104D3},
+{0x010CC0, 0x010C80},
+{0x010CC1, 0x010C81},
+{0x010CC2, 0x010C82},
+{0x010CC3, 0x010C83},
+{0x010CC4, 0x010C84},
+{0x010CC5, 0x010C85},
+{0x010CC6, 0x010C86},
+{0x010CC7, 0x010C87},
+{0x010CC8, 0x010C88},
+{0x010CC9, 0x010C89},
+{0x010CCA, 0x010C8A},
+{0x010CCB, 0x010C8B},
+{0x010CCC, 0x010C8C},
+{0x010CCD, 0x010C8D},
+{0x010CCE, 0x010C8E},
+{0x010CCF, 0x010C8F},
+{0x010CD0, 0x010C90},
+{0x010CD1, 0x010C91},
+{0x010CD2, 0x010C92},
+{0x010CD3, 0x010C93},
+{0x010CD4, 0x010C94},
+{0x010CD5, 0x010C95},
+{0x010CD6, 0x010C96},
+{0x010CD7, 0x010C97},
+{0x010CD8, 0x010C98},
+{0x010CD9, 0x010C99},
+{0x010CDA, 0x010C9A},
+{0x010CDB, 0x010C9B},
+{0x010CDC, 0x010C9C},
+{0x010CDD, 0x010C9D},
+{0x010CDE, 0x010C9E},
+{0x010CDF, 0x010C9F},
+{0x010CE0, 0x010CA0},
+{0x010CE1, 0x010CA1},
+{0x010CE2, 0x010CA2},
+{0x010CE3, 0x010CA3},
+{0x010CE4, 0x010CA4},
+{0x010CE5, 0x010CA5},
+{0x010CE6, 0x010CA6},
+{0x010CE7, 0x010CA7},
+{0x010CE8, 0x010CA8},
+{0x010CE9, 0x010CA9},
+{0x010CEA, 0x010CAA},
+{0x010CEB, 0x010CAB},
+{0x010CEC, 0x010CAC},
+{0x010CED, 0x010CAD},
+{0x010CEE, 0x010CAE},
+{0x010CEF, 0x010CAF},
+{0x010CF0, 0x010CB0},
+{0x010CF1, 0x010CB1},
+{0x010CF2, 0x010CB2},
+{0x0118C0, 0x0118A0},
+{0x0118C1, 0x0118A1},
+{0x0118C2, 0x0118A2},
+{0x0118C3, 0x0118A3},
+{0x0118C4, 0x0118A4},
+{0x0118C5, 0x0118A5},
+{0x0118C6, 0x0118A6},
+{0x0118C7, 0x0118A7},
+{0x0118C8, 0x0118A8},
+{0x0118C9, 0x0118A9},
+{0x0118CA, 0x0118AA},
+{0x0118CB, 0x0118AB},
+{0x0118CC, 0x0118AC},
+{0x0118CD, 0x0118AD},
+{0x0118CE, 0x0118AE},
+{0x0118CF, 0x0118AF},
+{0x0118D0, 0x0118B0},
+{0x0118D1, 0x0118B1},
+{0x0118D2, 0x0118B2},
+{0x0118D3, 0x0118B3},
+{0x0118D4, 0x0118B4},
+{0x0118D5, 0x0118B5},
+{0x0118D6, 0x0118B6},
+{0x0118D7, 0x0118B7},
+{0x0118D8, 0x0118B8},
+{0x0118D9, 0x0118B9},
+{0x0118DA, 0x0118BA},
+{0x0118DB, 0x0118BB},
+{0x0118DC, 0x0118BC},
+{0x0118DD, 0x0118BD},
+{0x0118DE, 0x0118BE},
+{0x0118DF, 0x0118BF},
+{0x016E60, 0x016E40},
+{0x016E61, 0x016E41},
+{0x016E62, 0x016E42},
+{0x016E63, 0x016E43},
+{0x016E64, 0x016E44},
+{0x016E65, 0x016E45},
+{0x016E66, 0x016E46},
+{0x016E67, 0x016E47},
+{0x016E68, 0x016E48},
+{0x016E69, 0x016E49},
+{0x016E6A, 0x016E4A},
+{0x016E6B, 0x016E4B},
+{0x016E6C, 0x016E4C},
+{0x016E6D, 0x016E4D},
+{0x016E6E, 0x016E4E},
+{0x016E6F, 0x016E4F},
+{0x016E70, 0x016E50},
+{0x016E71, 0x016E51},
+{0x016E72, 0x016E52},
+{0x016E73, 0x016E53},
+{0x016E74, 0x016E54},
+{0x016E75, 0x016E55},
+{0x016E76, 0x016E56},
+{0x016E77, 0x016E57},
+{0x016E78, 0x016E58},
+{0x016E79, 0x016E59},
+{0x016E7A, 0x016E5A},
+{0x016E7B, 0x016E5B},
+{0x016E7C, 0x016E5C},
+{0x016E7D, 0x016E5D},
+{0x016E7E, 0x016E5E},
+{0x016E7F, 0x016E5F},
+{0x01E922, 0x01E900},
+{0x01E923, 0x01E901},
+{0x01E924, 0x01E902},
+{0x01E925, 0x01E903},
+{0x01E926, 0x01E904},
+{0x01E927, 0x01E905},
+{0x01E928, 0x01E906},
+{0x01E929, 0x01E907},
+{0x01E92A, 0x01E908},
+{0x01E92B, 0x01E909},
+{0x01E92C, 0x01E90A},
+{0x01E92D, 0x01E90B},
+{0x01E92E, 0x01E90C},
+{0x01E92F, 0x01E90D},
+{0x01E930, 0x01E90E},
+{0x01E931, 0x01E90F},
+{0x01E932, 0x01E910},
+{0x01E933, 0x01E911},
+{0x01E934, 0x01E912},
+{0x01E935, 0x01E913},
+{0x01E936, 0x01E914},
+{0x01E937, 0x01E915},
+{0x01E938, 0x01E916},
+{0x01E939, 0x01E917},
+{0x01E93A, 0x01E918},
+{0x01E93B, 0x01E919},
+{0x01E93C, 0x01E91A},
+{0x01E93D, 0x01E91B},
+{0x01E93E, 0x01E91C},
+{0x01E93F, 0x01E91D},
+{0x01E940, 0x01E91E},
+{0x01E941, 0x01E91F},
+{0x01E942, 0x01E920},
+{0x01E943, 0x01E921},
 };
 
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_accent_mark = {
-{0x00000300, 0x0000036F}, {0x00000483, 0x00000489}, {0x00000591, 0x000005BD}, {0x000005BF, 0x000005BF},
-{0x000005C1, 0x000005C2}, {0x000005C4, 0x000005C5}, {0x000005C7, 0x000005C7}, {0x00000610, 0x0000061A},
-{0x0000064B, 0x0000065F}, {0x00000670, 0x00000670}, {0x000006D6, 0x000006DC}, {0x000006DF, 0x000006E4},
-{0x000006E7, 0x000006E8}, {0x000006EA, 0x000006ED}, {0x00000711, 0x00000711}, {0x00000730, 0x0000074A},
-{0x000007A6, 0x000007B0}, {0x000007EB, 0x000007F3}, {0x000007FD, 0x000007FD}, {0x00000816, 0x00000819},
-{0x0000081B, 0x00000823}, {0x00000825, 0x00000827}, {0x00000829, 0x0000082D}, {0x00000859, 0x0000085B},
-{0x00000898, 0x0000089F}, {0x000008CA, 0x000008E1}, {0x000008E3, 0x00000903}, {0x0000093A, 0x0000093C},
-{0x0000093E, 0x0000094F}, {0x00000951, 0x00000957}, {0x00000962, 0x00000963}, {0x00000981, 0x00000983},
-{0x000009BC, 0x000009BC}, {0x000009BE, 0x000009C4}, {0x000009C7, 0x000009C8}, {0x000009CB, 0x000009CD},
-{0x000009D7, 0x000009D7}, {0x000009E2, 0x000009E3}, {0x000009FE, 0x000009FE}, {0x00000A01, 0x00000A03},
-{0x00000A3C, 0x00000A3C}, {0x00000A3E, 0x00000A42}, {0x00000A47, 0x00000A48}, {0x00000A4B, 0x00000A4D},
-{0x00000A51, 0x00000A51}, {0x00000A70, 0x00000A71}, {0x00000A75, 0x00000A75}, {0x00000A81, 0x00000A83},
-{0x00000ABC, 0x00000ABC}, {0x00000ABE, 0x00000AC5}, {0x00000AC7, 0x00000AC9}, {0x00000ACB, 0x00000ACD},
-{0x00000AE2, 0x00000AE3}, {0x00000AFA, 0x00000AFF}, {0x00000B01, 0x00000B03}, {0x00000B3C, 0x00000B3C},
-{0x00000B3E, 0x00000B44}, {0x00000B47, 0x00000B48}, {0x00000B4B, 0x00000B4D}, {0x00000B55, 0x00000B57},
-{0x00000B62, 0x00000B63}, {0x00000B82, 0x00000B82}, {0x00000BBE, 0x00000BC2}, {0x00000BC6, 0x00000BC8},
-{0x00000BCA, 0x00000BCD}, {0x00000BD7, 0x00000BD7}, {0x00000C00, 0x00000C04}, {0x00000C3C, 0x00000C3C},
-{0x00000C3E, 0x00000C44}, {0x00000C46, 0x00000C48}, {0x00000C4A, 0x00000C4D}, {0x00000C55, 0x00000C56},
-{0x00000C62, 0x00000C63}, {0x00000C81, 0x00000C83}, {0x00000CBC, 0x00000CBC}, {0x00000CBE, 0x00000CC4},
-{0x00000CC6, 0x00000CC8}, {0x00000CCA, 0x00000CCD}, {0x00000CD5, 0x00000CD6}, {0x00000CE2, 0x00000CE3},
-{0x00000CF3, 0x00000CF3}, {0x00000D00, 0x00000D03}, {0x00000D3B, 0x00000D3C}, {0x00000D3E, 0x00000D44},
-{0x00000D46, 0x00000D48}, {0x00000D4A, 0x00000D4D}, {0x00000D57, 0x00000D57}, {0x00000D62, 0x00000D63},
-{0x00000D81, 0x00000D83}, {0x00000DCA, 0x00000DCA}, {0x00000DCF, 0x00000DD4}, {0x00000DD6, 0x00000DD6},
-{0x00000DD8, 0x00000DDF}, {0x00000DF2, 0x00000DF3}, {0x00000E31, 0x00000E31}, {0x00000E34, 0x00000E3A},
-{0x00000E47, 0x00000E4E}, {0x00000EB1, 0x00000EB1}, {0x00000EB4, 0x00000EBC}, {0x00000EC8, 0x00000ECE},
-{0x00000F18, 0x00000F19}, {0x00000F35, 0x00000F35}, {0x00000F37, 0x00000F37}, {0x00000F39, 0x00000F39},
-{0x00000F3E, 0x00000F3F}, {0x00000F71, 0x00000F84}, {0x00000F86, 0x00000F87}, {0x00000F8D, 0x00000F97},
-{0x00000F99, 0x00000FBC}, {0x00000FC6, 0x00000FC6}, {0x0000102B, 0x0000103E}, {0x00001056, 0x00001059},
-{0x0000105E, 0x00001060}, {0x00001062, 0x00001064}, {0x00001067, 0x0000106D}, {0x00001071, 0x00001074},
-{0x00001082, 0x0000108D}, {0x0000108F, 0x0000108F}, {0x0000109A, 0x0000109D}, {0x0000135D, 0x0000135F},
-{0x00001712, 0x00001715}, {0x00001732, 0x00001734}, {0x00001752, 0x00001753}, {0x00001772, 0x00001773},
-{0x000017B4, 0x000017D3}, {0x000017DD, 0x000017DD}, {0x0000180B, 0x0000180D}, {0x0000180F, 0x0000180F},
-{0x00001885, 0x00001886}, {0x000018A9, 0x000018A9}, {0x00001920, 0x0000192B}, {0x00001930, 0x0000193B},
-{0x00001A17, 0x00001A1B}, {0x00001A55, 0x00001A5E}, {0x00001A60, 0x00001A7C}, {0x00001A7F, 0x00001A7F},
-{0x00001AB0, 0x00001ACE}, {0x00001B00, 0x00001B04}, {0x00001B34, 0x00001B44}, {0x00001B6B, 0x00001B73},
-{0x00001B80, 0x00001B82}, {0x00001BA1, 0x00001BAD}, {0x00001BE6, 0x00001BF3}, {0x00001C24, 0x00001C37},
-{0x00001CD0, 0x00001CD2}, {0x00001CD4, 0x00001CE8}, {0x00001CED, 0x00001CED}, {0x00001CF4, 0x00001CF4},
-{0x00001CF7, 0x00001CF9}, {0x00001DC0, 0x00001DFF}, {0x000020D0, 0x000020F0}, {0x00002CEF, 0x00002CF1},
-{0x00002D7F, 0x00002D7F}, {0x00002DE0, 0x00002DFF}, {0x0000302A, 0x0000302F}, {0x00003099, 0x0000309A},
-{0x0000A66F, 0x0000A672}, {0x0000A674, 0x0000A67D}, {0x0000A69E, 0x0000A69F}, {0x0000A6F0, 0x0000A6F1},
-{0x0000A802, 0x0000A802}, {0x0000A806, 0x0000A806}, {0x0000A80B, 0x0000A80B}, {0x0000A823, 0x0000A827},
-{0x0000A82C, 0x0000A82C}, {0x0000A880, 0x0000A881}, {0x0000A8B4, 0x0000A8C5}, {0x0000A8E0, 0x0000A8F1},
-{0x0000A8FF, 0x0000A8FF}, {0x0000A926, 0x0000A92D}, {0x0000A947, 0x0000A953}, {0x0000A980, 0x0000A983},
-{0x0000A9B3, 0x0000A9C0}, {0x0000A9E5, 0x0000A9E5}, {0x0000AA29, 0x0000AA36}, {0x0000AA43, 0x0000AA43},
-{0x0000AA4C, 0x0000AA4D}, {0x0000AA7B, 0x0000AA7D}, {0x0000AAB0, 0x0000AAB0}, {0x0000AAB2, 0x0000AAB4},
-{0x0000AAB7, 0x0000AAB8}, {0x0000AABE, 0x0000AABF}, {0x0000AAC1, 0x0000AAC1}, {0x0000AAEB, 0x0000AAEF},
-{0x0000AAF5, 0x0000AAF6}, {0x0000ABE3, 0x0000ABEA}, {0x0000ABEC, 0x0000ABED}, {0x0000FB1E, 0x0000FB1E},
-{0x0000FE00, 0x0000FE0F}, {0x0000FE20, 0x0000FE2F}, {0x000101FD, 0x000101FD}, {0x000102E0, 0x000102E0},
-{0x00010376, 0x0001037A}, {0x00010A01, 0x00010A03}, {0x00010A05, 0x00010A06}, {0x00010A0C, 0x00010A0F},
-{0x00010A38, 0x00010A3A}, {0x00010A3F, 0x00010A3F}, {0x00010AE5, 0x00010AE6}, {0x00010D24, 0x00010D27},
-{0x00010EAB, 0x00010EAC}, {0x00010EFD, 0x00010EFF}, {0x00010F46, 0x00010F50}, {0x00010F82, 0x00010F85},
-{0x00011000, 0x00011002}, {0x00011038, 0x00011046}, {0x00011070, 0x00011070}, {0x00011073, 0x00011074},
-{0x0001107F, 0x00011082}, {0x000110B0, 0x000110BA}, {0x000110C2, 0x000110C2}, {0x00011100, 0x00011102},
-{0x00011127, 0x00011134}, {0x00011145, 0x00011146}, {0x00011173, 0x00011173}, {0x00011180, 0x00011182},
-{0x000111B3, 0x000111C0}, {0x000111C9, 0x000111CC}, {0x000111CE, 0x000111CF}, {0x0001122C, 0x00011237},
-{0x0001123E, 0x0001123E}, {0x00011241, 0x00011241}, {0x000112DF, 0x000112EA}, {0x00011300, 0x00011303},
-{0x0001133B, 0x0001133C}, {0x0001133E, 0x00011344}, {0x00011347, 0x00011348}, {0x0001134B, 0x0001134D},
-{0x00011357, 0x00011357}, {0x00011362, 0x00011363}, {0x00011366, 0x0001136C}, {0x00011370, 0x00011374},
-{0x00011435, 0x00011446}, {0x0001145E, 0x0001145E}, {0x000114B0, 0x000114C3}, {0x000115AF, 0x000115B5},
-{0x000115B8, 0x000115C0}, {0x000115DC, 0x000115DD}, {0x00011630, 0x00011640}, {0x000116AB, 0x000116B7},
-{0x0001171D, 0x0001172B}, {0x0001182C, 0x0001183A}, {0x00011930, 0x00011935}, {0x00011937, 0x00011938},
-{0x0001193B, 0x0001193E}, {0x00011940, 0x00011940}, {0x00011942, 0x00011943}, {0x000119D1, 0x000119D7},
-{0x000119DA, 0x000119E0}, {0x000119E4, 0x000119E4}, {0x00011A01, 0x00011A0A}, {0x00011A33, 0x00011A39},
-{0x00011A3B, 0x00011A3E}, {0x00011A47, 0x00011A47}, {0x00011A51, 0x00011A5B}, {0x00011A8A, 0x00011A99},
-{0x00011C2F, 0x00011C36}, {0x00011C38, 0x00011C3F}, {0x00011C92, 0x00011CA7}, {0x00011CA9, 0x00011CB6},
-{0x00011D31, 0x00011D36}, {0x00011D3A, 0x00011D3A}, {0x00011D3C, 0x00011D3D}, {0x00011D3F, 0x00011D45},
-{0x00011D47, 0x00011D47}, {0x00011D8A, 0x00011D8E}, {0x00011D90, 0x00011D91}, {0x00011D93, 0x00011D97},
-{0x00011EF3, 0x00011EF6}, {0x00011F00, 0x00011F01}, {0x00011F03, 0x00011F03}, {0x00011F34, 0x00011F3A},
-{0x00011F3E, 0x00011F42}, {0x00013440, 0x00013440}, {0x00013447, 0x00013455}, {0x00016AF0, 0x00016AF4},
-{0x00016B30, 0x00016B36}, {0x00016F4F, 0x00016F4F}, {0x00016F51, 0x00016F87}, {0x00016F8F, 0x00016F92},
-{0x00016FE4, 0x00016FE4}, {0x00016FF0, 0x00016FF1}, {0x0001BC9D, 0x0001BC9E}, {0x0001CF00, 0x0001CF2D},
-{0x0001CF30, 0x0001CF46}, {0x0001D165, 0x0001D169}, {0x0001D16D, 0x0001D172}, {0x0001D17B, 0x0001D182},
-{0x0001D185, 0x0001D18B}, {0x0001D1AA, 0x0001D1AD}, {0x0001D242, 0x0001D244}, {0x0001DA00, 0x0001DA36},
-{0x0001DA3B, 0x0001DA6C}, {0x0001DA75, 0x0001DA75}, {0x0001DA84, 0x0001DA84}, {0x0001DA9B, 0x0001DA9F},
-{0x0001DAA1, 0x0001DAAF}, {0x0001E000, 0x0001E006}, {0x0001E008, 0x0001E018}, {0x0001E01B, 0x0001E021},
-{0x0001E023, 0x0001E024}, {0x0001E026, 0x0001E02A}, {0x0001E08F, 0x0001E08F}, {0x0001E130, 0x0001E136},
-{0x0001E2AE, 0x0001E2AE}, {0x0001E2EC, 0x0001E2EF}, {0x0001E4EC, 0x0001E4EF}, {0x0001E8D0, 0x0001E8D6},
-{0x0001E944, 0x0001E94A}, {0x000E0100, 0x000E01EF},
+const std::vector<range_nfd> unicode_ranges_nfd = {  // start, last, nfd
+{0x000000, 0x000000, 0x000000},
+{0x0000C0, 0x0000C5, 0x000041},
+{0x0000C7, 0x0000C7, 0x000043},
+{0x0000C8, 0x0000CB, 0x000045},
+{0x0000CC, 0x0000CF, 0x000049},
+{0x0000D1, 0x0000D1, 0x00004E},
+{0x0000D2, 0x0000D6, 0x00004F},
+{0x0000D9, 0x0000DC, 0x000055},
+{0x0000DD, 0x0000DD, 0x000059},
+{0x0000E0, 0x0000E5, 0x000061},
+{0x0000E7, 0x0000E7, 0x000063},
+{0x0000E8, 0x0000EB, 0x000065},
+{0x0000EC, 0x0000EF, 0x000069},
+{0x0000F1, 0x0000F1, 0x00006E},
+{0x0000F2, 0x0000F6, 0x00006F},
+{0x0000F9, 0x0000FC, 0x000075},
+{0x0000FD, 0x0000FD, 0x000079},
+{0x0000FF, 0x0000FF, 0x000079},
+{0x000100, 0x000100, 0x000041},
+{0x000101, 0x000101, 0x000061},
+{0x000102, 0x000102, 0x000041},
+{0x000103, 0x000103, 0x000061},
+{0x000104, 0x000104, 0x000041},
+{0x000105, 0x000105, 0x000061},
+{0x000106, 0x000106, 0x000043},
+{0x000107, 0x000107, 0x000063},
+{0x000108, 0x000108, 0x000043},
+{0x000109, 0x000109, 0x000063},
+{0x00010A, 0x00010A, 0x000043},
+{0x00010B, 0x00010B, 0x000063},
+{0x00010C, 0x00010C, 0x000043},
+{0x00010D, 0x00010D, 0x000063},
+{0x00010E, 0x00010E, 0x000044},
+{0x00010F, 0x00010F, 0x000064},
+{0x000112, 0x000112, 0x000045},
+{0x000113, 0x000113, 0x000065},
+{0x000114, 0x000114, 0x000045},
+{0x000115, 0x000115, 0x000065},
+{0x000116, 0x000116, 0x000045},
+{0x000117, 0x000117, 0x000065},
+{0x000118, 0x000118, 0x000045},
+{0x000119, 0x000119, 0x000065},
+{0x00011A, 0x00011A, 0x000045},
+{0x00011B, 0x00011B, 0x000065},
+{0x00011C, 0x00011C, 0x000047},
+{0x00011D, 0x00011D, 0x000067},
+{0x00011E, 0x00011E, 0x000047},
+{0x00011F, 0x00011F, 0x000067},
+{0x000120, 0x000120, 0x000047},
+{0x000121, 0x000121, 0x000067},
+{0x000122, 0x000122, 0x000047},
+{0x000123, 0x000123, 0x000067},
+{0x000124, 0x000124, 0x000048},
+{0x000125, 0x000125, 0x000068},
+{0x000128, 0x000128, 0x000049},
+{0x000129, 0x000129, 0x000069},
+{0x00012A, 0x00012A, 0x000049},
+{0x00012B, 0x00012B, 0x000069},
+{0x00012C, 0x00012C, 0x000049},
+{0x00012D, 0x00012D, 0x000069},
+{0x00012E, 0x00012E, 0x000049},
+{0x00012F, 0x00012F, 0x000069},
+{0x000130, 0x000130, 0x000049},
+{0x000134, 0x000134, 0x00004A},
+{0x000135, 0x000135, 0x00006A},
+{0x000136, 0x000136, 0x00004B},
+{0x000137, 0x000137, 0x00006B},
+{0x000139, 0x000139, 0x00004C},
+{0x00013A, 0x00013A, 0x00006C},
+{0x00013B, 0x00013B, 0x00004C},
+{0x00013C, 0x00013C, 0x00006C},
+{0x00013D, 0x00013D, 0x00004C},
+{0x00013E, 0x00013E, 0x00006C},
+{0x000143, 0x000143, 0x00004E},
+{0x000144, 0x000144, 0x00006E},
+{0x000145, 0x000145, 0x00004E},
+{0x000146, 0x000146, 0x00006E},
+{0x000147, 0x000147, 0x00004E},
+{0x000148, 0x000148, 0x00006E},
+{0x00014C, 0x00014C, 0x00004F},
+{0x00014D, 0x00014D, 0x00006F},
+{0x00014E, 0x00014E, 0x00004F},
+{0x00014F, 0x00014F, 0x00006F},
+{0x000150, 0x000150, 0x00004F},
+{0x000151, 0x000151, 0x00006F},
+{0x000154, 0x000154, 0x000052},
+{0x000155, 0x000155, 0x000072},
+{0x000156, 0x000156, 0x000052},
+{0x000157, 0x000157, 0x000072},
+{0x000158, 0x000158, 0x000052},
+{0x000159, 0x000159, 0x000072},
+{0x00015A, 0x00015A, 0x000053},
+{0x00015B, 0x00015B, 0x000073},
+{0x00015C, 0x00015C, 0x000053},
+{0x00015D, 0x00015D, 0x000073},
+{0x00015E, 0x00015E, 0x000053},
+{0x00015F, 0x00015F, 0x000073},
+{0x000160, 0x000160, 0x000053},
+{0x000161, 0x000161, 0x000073},
+{0x000162, 0x000162, 0x000054},
+{0x000163, 0x000163, 0x000074},
+{0x000164, 0x000164, 0x000054},
+{0x000165, 0x000165, 0x000074},
+{0x000168, 0x000168, 0x000055},
+{0x000169, 0x000169, 0x000075},
+{0x00016A, 0x00016A, 0x000055},
+{0x00016B, 0x00016B, 0x000075},
+{0x00016C, 0x00016C, 0x000055},
+{0x00016D, 0x00016D, 0x000075},
+{0x00016E, 0x00016E, 0x000055},
+{0x00016F, 0x00016F, 0x000075},
+{0x000170, 0x000170, 0x000055},
+{0x000171, 0x000171, 0x000075},
+{0x000172, 0x000172, 0x000055},
+{0x000173, 0x000173, 0x000075},
+{0x000174, 0x000174, 0x000057},
+{0x000175, 0x000175, 0x000077},
+{0x000176, 0x000176, 0x000059},
+{0x000177, 0x000177, 0x000079},
+{0x000178, 0x000178, 0x000059},
+{0x000179, 0x000179, 0x00005A},
+{0x00017A, 0x00017A, 0x00007A},
+{0x00017B, 0x00017B, 0x00005A},
+{0x00017C, 0x00017C, 0x00007A},
+{0x00017D, 0x00017D, 0x00005A},
+{0x00017E, 0x00017E, 0x00007A},
+{0x0001A0, 0x0001A0, 0x00004F},
+{0x0001A1, 0x0001A1, 0x00006F},
+{0x0001AF, 0x0001AF, 0x000055},
+{0x0001B0, 0x0001B0, 0x000075},
+{0x0001CD, 0x0001CD, 0x000041},
+{0x0001CE, 0x0001CE, 0x000061},
+{0x0001CF, 0x0001CF, 0x000049},
+{0x0001D0, 0x0001D0, 0x000069},
+{0x0001D1, 0x0001D1, 0x00004F},
+{0x0001D2, 0x0001D2, 0x00006F},
+{0x0001D3, 0x0001D3, 0x000055},
+{0x0001D4, 0x0001D4, 0x000075},
+{0x0001D5, 0x0001D5, 0x000055},
+{0x0001D6, 0x0001D6, 0x000075},
+{0x0001D7, 0x0001D7, 0x000055},
+{0x0001D8, 0x0001D8, 0x000075},
+{0x0001D9, 0x0001D9, 0x000055},
+{0x0001DA, 0x0001DA, 0x000075},
+{0x0001DB, 0x0001DB, 0x000055},
+{0x0001DC, 0x0001DC, 0x000075},
+{0x0001DE, 0x0001DE, 0x000041},
+{0x0001DF, 0x0001DF, 0x000061},
+{0x0001E0, 0x0001E0, 0x000041},
+{0x0001E1, 0x0001E1, 0x000061},
+{0x0001E2, 0x0001E2, 0x0000C6},
+{0x0001E3, 0x0001E3, 0x0000E6},
+{0x0001E6, 0x0001E6, 0x000047},
+{0x0001E7, 0x0001E7, 0x000067},
+{0x0001E8, 0x0001E8, 0x00004B},
+{0x0001E9, 0x0001E9, 0x00006B},
+{0x0001EA, 0x0001EA, 0x00004F},
+{0x0001EB, 0x0001EB, 0x00006F},
+{0x0001EC, 0x0001EC, 0x00004F},
+{0x0001ED, 0x0001ED, 0x00006F},
+{0x0001EE, 0x0001EE, 0x0001B7},
+{0x0001EF, 0x0001EF, 0x000292},
+{0x0001F0, 0x0001F0, 0x00006A},
+{0x0001F4, 0x0001F4, 0x000047},
+{0x0001F5, 0x0001F5, 0x000067},
+{0x0001F8, 0x0001F8, 0x00004E},
+{0x0001F9, 0x0001F9, 0x00006E},
+{0x0001FA, 0x0001FA, 0x000041},
+{0x0001FB, 0x0001FB, 0x000061},
+{0x0001FC, 0x0001FC, 0x0000C6},
+{0x0001FD, 0x0001FD, 0x0000E6},
+{0x0001FE, 0x0001FE, 0x0000D8},
+{0x0001FF, 0x0001FF, 0x0000F8},
+{0x000200, 0x000200, 0x000041},
+{0x000201, 0x000201, 0x000061},
+{0x000202, 0x000202, 0x000041},
+{0x000203, 0x000203, 0x000061},
+{0x000204, 0x000204, 0x000045},
+{0x000205, 0x000205, 0x000065},
+{0x000206, 0x000206, 0x000045},
+{0x000207, 0x000207, 0x000065},
+{0x000208, 0x000208, 0x000049},
+{0x000209, 0x000209, 0x000069},
+{0x00020A, 0x00020A, 0x000049},
+{0x00020B, 0x00020B, 0x000069},
+{0x00020C, 0x00020C, 0x00004F},
+{0x00020D, 0x00020D, 0x00006F},
+{0x00020E, 0x00020E, 0x00004F},
+{0x00020F, 0x00020F, 0x00006F},
+{0x000210, 0x000210, 0x000052},
+{0x000211, 0x000211, 0x000072},
+{0x000212, 0x000212, 0x000052},
+{0x000213, 0x000213, 0x000072},
+{0x000214, 0x000214, 0x000055},
+{0x000215, 0x000215, 0x000075},
+{0x000216, 0x000216, 0x000055},
+{0x000217, 0x000217, 0x000075},
+{0x000218, 0x000218, 0x000053},
+{0x000219, 0x000219, 0x000073},
+{0x00021A, 0x00021A, 0x000054},
+{0x00021B, 0x00021B, 0x000074},
+{0x00021E, 0x00021E, 0x000048},
+{0x00021F, 0x00021F, 0x000068},
+{0x000226, 0x000226, 0x000041},
+{0x000227, 0x000227, 0x000061},
+{0x000228, 0x000228, 0x000045},
+{0x000229, 0x000229, 0x000065},
+{0x00022A, 0x00022A, 0x00004F},
+{0x00022B, 0x00022B, 0x00006F},
+{0x00022C, 0x00022C, 0x00004F},
+{0x00022D, 0x00022D, 0x00006F},
+{0x00022E, 0x00022E, 0x00004F},
+{0x00022F, 0x00022F, 0x00006F},
+{0x000230, 0x000230, 0x00004F},
+{0x000231, 0x000231, 0x00006F},
+{0x000232, 0x000232, 0x000059},
+{0x000233, 0x000233, 0x000079},
+{0x000340, 0x000340, 0x000300},
+{0x000341, 0x000341, 0x000301},
+{0x000343, 0x000343, 0x000313},
+{0x000344, 0x000344, 0x000308},
+{0x000374, 0x000374, 0x0002B9},
+{0x00037E, 0x00037E, 0x00003B},
+{0x000385, 0x000385, 0x0000A8},
+{0x000386, 0x000386, 0x000391},
+{0x000387, 0x000387, 0x0000B7},
+{0x000388, 0x000388, 0x000395},
+{0x000389, 0x000389, 0x000397},
+{0x00038A, 0x00038A, 0x000399},
+{0x00038C, 0x00038C, 0x00039F},
+{0x00038E, 0x00038E, 0x0003A5},
+{0x00038F, 0x00038F, 0x0003A9},
+{0x000390, 0x000390, 0x0003B9},
+{0x0003AA, 0x0003AA, 0x000399},
+{0x0003AB, 0x0003AB, 0x0003A5},
+{0x0003AC, 0x0003AC, 0x0003B1},
+{0x0003AD, 0x0003AD, 0x0003B5},
+{0x0003AE, 0x0003AE, 0x0003B7},
+{0x0003AF, 0x0003AF, 0x0003B9},
+{0x0003B0, 0x0003B0, 0x0003C5},
+{0x0003CA, 0x0003CA, 0x0003B9},
+{0x0003CB, 0x0003CB, 0x0003C5},
+{0x0003CC, 0x0003CC, 0x0003BF},
+{0x0003CD, 0x0003CD, 0x0003C5},
+{0x0003CE, 0x0003CE, 0x0003C9},
+{0x0003D3, 0x0003D4, 0x0003D2},
+{0x000400, 0x000401, 0x000415},
+{0x000403, 0x000403, 0x000413},
+{0x000407, 0x000407, 0x000406},
+{0x00040C, 0x00040C, 0x00041A},
+{0x00040D, 0x00040D, 0x000418},
+{0x00040E, 0x00040E, 0x000423},
+{0x000419, 0x000419, 0x000418},
+{0x000439, 0x000439, 0x000438},
+{0x000450, 0x000451, 0x000435},
+{0x000453, 0x000453, 0x000433},
+{0x000457, 0x000457, 0x000456},
+{0x00045C, 0x00045C, 0x00043A},
+{0x00045D, 0x00045D, 0x000438},
+{0x00045E, 0x00045E, 0x000443},
+{0x000476, 0x000476, 0x000474},
+{0x000477, 0x000477, 0x000475},
+{0x0004C1, 0x0004C1, 0x000416},
+{0x0004C2, 0x0004C2, 0x000436},
+{0x0004D0, 0x0004D0, 0x000410},
+{0x0004D1, 0x0004D1, 0x000430},
+{0x0004D2, 0x0004D2, 0x000410},
+{0x0004D3, 0x0004D3, 0x000430},
+{0x0004D6, 0x0004D6, 0x000415},
+{0x0004D7, 0x0004D7, 0x000435},
+{0x0004DA, 0x0004DA, 0x0004D8},
+{0x0004DB, 0x0004DB, 0x0004D9},
+{0x0004DC, 0x0004DC, 0x000416},
+{0x0004DD, 0x0004DD, 0x000436},
+{0x0004DE, 0x0004DE, 0x000417},
+{0x0004DF, 0x0004DF, 0x000437},
+{0x0004E2, 0x0004E2, 0x000418},
+{0x0004E3, 0x0004E3, 0x000438},
+{0x0004E4, 0x0004E4, 0x000418},
+{0x0004E5, 0x0004E5, 0x000438},
+{0x0004E6, 0x0004E6, 0x00041E},
+{0x0004E7, 0x0004E7, 0x00043E},
+{0x0004EA, 0x0004EA, 0x0004E8},
+{0x0004EB, 0x0004EB, 0x0004E9},
+{0x0004EC, 0x0004EC, 0x00042D},
+{0x0004ED, 0x0004ED, 0x00044D},
+{0x0004EE, 0x0004EE, 0x000423},
+{0x0004EF, 0x0004EF, 0x000443},
+{0x0004F0, 0x0004F0, 0x000423},
+{0x0004F1, 0x0004F1, 0x000443},
+{0x0004F2, 0x0004F2, 0x000423},
+{0x0004F3, 0x0004F3, 0x000443},
+{0x0004F4, 0x0004F4, 0x000427},
+{0x0004F5, 0x0004F5, 0x000447},
+{0x0004F8, 0x0004F8, 0x00042B},
+{0x0004F9, 0x0004F9, 0x00044B},
+{0x000622, 0x000623, 0x000627},
+{0x000624, 0x000624, 0x000648},
+{0x000625, 0x000625, 0x000627},
+{0x000626, 0x000626, 0x00064A},
+{0x0006C0, 0x0006C0, 0x0006D5},
+{0x0006C2, 0x0006C2, 0x0006C1},
+{0x0006D3, 0x0006D3, 0x0006D2},
+{0x000929, 0x000929, 0x000928},
+{0x000931, 0x000931, 0x000930},
+{0x000934, 0x000934, 0x000933},
+{0x000958, 0x000958, 0x000915},
+{0x000959, 0x000959, 0x000916},
+{0x00095A, 0x00095A, 0x000917},
+{0x00095B, 0x00095B, 0x00091C},
+{0x00095C, 0x00095C, 0x000921},
+{0x00095D, 0x00095D, 0x000922},
+{0x00095E, 0x00095E, 0x00092B},
+{0x00095F, 0x00095F, 0x00092F},
+{0x0009CB, 0x0009CC, 0x0009C7},
+{0x0009DC, 0x0009DC, 0x0009A1},
+{0x0009DD, 0x0009DD, 0x0009A2},
+{0x0009DF, 0x0009DF, 0x0009AF},
+{0x000A33, 0x000A33, 0x000A32},
+{0x000A36, 0x000A36, 0x000A38},
+{0x000A59, 0x000A59, 0x000A16},
+{0x000A5A, 0x000A5A, 0x000A17},
+{0x000A5B, 0x000A5B, 0x000A1C},
+{0x000A5E, 0x000A5E, 0x000A2B},
+{0x000B48, 0x000B48, 0x000B47},
+{0x000B4B, 0x000B4C, 0x000B47},
+{0x000B5C, 0x000B5C, 0x000B21},
+{0x000B5D, 0x000B5D, 0x000B22},
+{0x000B94, 0x000B94, 0x000B92},
+{0x000BCA, 0x000BCA, 0x000BC6},
+{0x000BCB, 0x000BCB, 0x000BC7},
+{0x000BCC, 0x000BCC, 0x000BC6},
+{0x000C48, 0x000C48, 0x000C46},
+{0x000CC0, 0x000CC0, 0x000CBF},
+{0x000CC7, 0x000CC8, 0x000CC6},
+{0x000CCA, 0x000CCB, 0x000CC6},
+{0x000D4A, 0x000D4A, 0x000D46},
+{0x000D4B, 0x000D4B, 0x000D47},
+{0x000D4C, 0x000D4C, 0x000D46},
+{0x000DDA, 0x000DDA, 0x000DD9},
+{0x000DDC, 0x000DDE, 0x000DD9},
+{0x000F43, 0x000F43, 0x000F42},
+{0x000F4D, 0x000F4D, 0x000F4C},
+{0x000F52, 0x000F52, 0x000F51},
+{0x000F57, 0x000F57, 0x000F56},
+{0x000F5C, 0x000F5C, 0x000F5B},
+{0x000F69, 0x000F69, 0x000F40},
+{0x000F73, 0x000F73, 0x000F71},
+{0x000F75, 0x000F75, 0x000F71},
+{0x000F76, 0x000F76, 0x000FB2},
+{0x000F78, 0x000F78, 0x000FB3},
+{0x000F81, 0x000F81, 0x000F71},
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+{0x02F9DC, 0x02F9DC, 0x008DF0},
+{0x02F9DD, 0x02F9DD, 0x0208DE},
+{0x02F9DE, 0x02F9DE, 0x008ED4},
+{0x02F9DF, 0x02F9DF, 0x008F38},
+{0x02F9E0, 0x02F9E0, 0x0285D2},
+{0x02F9E1, 0x02F9E1, 0x0285ED},
+{0x02F9E2, 0x02F9E2, 0x009094},
+{0x02F9E3, 0x02F9E3, 0x0090F1},
+{0x02F9E4, 0x02F9E4, 0x009111},
+{0x02F9E5, 0x02F9E5, 0x02872E},
+{0x02F9E6, 0x02F9E6, 0x00911B},
+{0x02F9E7, 0x02F9E7, 0x009238},
+{0x02F9E8, 0x02F9E8, 0x0092D7},
+{0x02F9E9, 0x02F9E9, 0x0092D8},
+{0x02F9EA, 0x02F9EA, 0x00927C},
+{0x02F9EB, 0x02F9EB, 0x0093F9},
+{0x02F9EC, 0x02F9EC, 0x009415},
+{0x02F9ED, 0x02F9ED, 0x028BFA},
+{0x02F9EE, 0x02F9EE, 0x00958B},
+{0x02F9EF, 0x02F9EF, 0x004995},
+{0x02F9F0, 0x02F9F0, 0x0095B7},
+{0x02F9F1, 0x02F9F1, 0x028D77},
+{0x02F9F2, 0x02F9F2, 0x0049E6},
+{0x02F9F3, 0x02F9F3, 0x0096C3},
+{0x02F9F4, 0x02F9F4, 0x005DB2},
+{0x02F9F5, 0x02F9F5, 0x009723},
+{0x02F9F6, 0x02F9F6, 0x029145},
+{0x02F9F7, 0x02F9F7, 0x02921A},
+{0x02F9F8, 0x02F9F8, 0x004A6E},
+{0x02F9F9, 0x02F9F9, 0x004A76},
+{0x02F9FA, 0x02F9FA, 0x0097E0},
+{0x02F9FB, 0x02F9FB, 0x02940A},
+{0x02F9FC, 0x02F9FC, 0x004AB2},
+{0x02F9FD, 0x02F9FD, 0x029496},
+{0x02F9FE, 0x02F9FF, 0x00980B},
+{0x02FA00, 0x02FA00, 0x009829},
+{0x02FA01, 0x02FA01, 0x0295B6},
+{0x02FA02, 0x02FA02, 0x0098E2},
+{0x02FA03, 0x02FA03, 0x004B33},
+{0x02FA04, 0x02FA04, 0x009929},
+{0x02FA05, 0x02FA05, 0x0099A7},
+{0x02FA06, 0x02FA06, 0x0099C2},
+{0x02FA07, 0x02FA07, 0x0099FE},
+{0x02FA08, 0x02FA08, 0x004BCE},
+{0x02FA09, 0x02FA09, 0x029B30},
+{0x02FA0A, 0x02FA0A, 0x009B12},
+{0x02FA0B, 0x02FA0B, 0x009C40},
+{0x02FA0C, 0x02FA0C, 0x009CFD},
+{0x02FA0D, 0x02FA0D, 0x004CCE},
+{0x02FA0E, 0x02FA0E, 0x004CED},
+{0x02FA0F, 0x02FA0F, 0x009D67},
+{0x02FA10, 0x02FA10, 0x02A0CE},
+{0x02FA11, 0x02FA11, 0x004CF8},
+{0x02FA12, 0x02FA12, 0x02A105},
+{0x02FA13, 0x02FA13, 0x02A20E},
+{0x02FA14, 0x02FA14, 0x02A291},
+{0x02FA15, 0x02FA15, 0x009EBB},
+{0x02FA16, 0x02FA16, 0x004D56},
+{0x02FA17, 0x02FA17, 0x009EF9},
+{0x02FA18, 0x02FA18, 0x009EFE},
+{0x02FA19, 0x02FA19, 0x009F05},
+{0x02FA1A, 0x02FA1A, 0x009F0F},
+{0x02FA1B, 0x02FA1B, 0x009F16},
+{0x02FA1C, 0x02FA1C, 0x009F3B},
+{0x02FA1D, 0x02FA1D, 0x02A600},
 };
 
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_punctuation = {
-{0x00000021, 0x00000023}, {0x00000025, 0x0000002A}, {0x0000002C, 0x0000002F}, {0x0000003A, 0x0000003B},
-{0x0000003F, 0x00000040}, {0x0000005B, 0x0000005D}, {0x0000005F, 0x0000005F}, {0x0000007B, 0x0000007B},
-{0x0000007D, 0x0000007D}, {0x000000A1, 0x000000A1}, {0x000000A7, 0x000000A7}, {0x000000AB, 0x000000AB},
-{0x000000B6, 0x000000B7}, {0x000000BB, 0x000000BB}, {0x000000BF, 0x000000BF}, {0x0000037E, 0x0000037E},
-{0x00000387, 0x00000387}, {0x0000055A, 0x0000055F}, {0x00000589, 0x0000058A}, {0x000005BE, 0x000005BE},
-{0x000005C0, 0x000005C0}, {0x000005C3, 0x000005C3}, {0x000005C6, 0x000005C6}, {0x000005F3, 0x000005F4},
-{0x00000609, 0x0000060A}, {0x0000060C, 0x0000060D}, {0x0000061B, 0x0000061B}, {0x0000061D, 0x0000061F},
-{0x0000066A, 0x0000066D}, {0x000006D4, 0x000006D4}, {0x00000700, 0x0000070D}, {0x000007F7, 0x000007F9},
-{0x00000830, 0x0000083E}, {0x0000085E, 0x0000085E}, {0x00000964, 0x00000965}, {0x00000970, 0x00000970},
-{0x000009FD, 0x000009FD}, {0x00000A76, 0x00000A76}, {0x00000AF0, 0x00000AF0}, {0x00000C77, 0x00000C77},
-{0x00000C84, 0x00000C84}, {0x00000DF4, 0x00000DF4}, {0x00000E4F, 0x00000E4F}, {0x00000E5A, 0x00000E5B},
-{0x00000F04, 0x00000F12}, {0x00000F14, 0x00000F14}, {0x00000F3A, 0x00000F3D}, {0x00000F85, 0x00000F85},
-{0x00000FD0, 0x00000FD4}, {0x00000FD9, 0x00000FDA}, {0x0000104A, 0x0000104F}, {0x000010FB, 0x000010FB},
-{0x00001360, 0x00001368}, {0x00001400, 0x00001400}, {0x0000166E, 0x0000166E}, {0x0000169B, 0x0000169C},
-{0x000016EB, 0x000016ED}, {0x00001735, 0x00001736}, {0x000017D4, 0x000017D6}, {0x000017D8, 0x000017DA},
-{0x00001800, 0x0000180A}, {0x00001944, 0x00001945}, {0x00001A1E, 0x00001A1F}, {0x00001AA0, 0x00001AA6},
-{0x00001AA8, 0x00001AAD}, {0x00001B5A, 0x00001B60}, {0x00001B7D, 0x00001B7E}, {0x00001BFC, 0x00001BFF},
-{0x00001C3B, 0x00001C3F}, {0x00001C7E, 0x00001C7F}, {0x00001CC0, 0x00001CC7}, {0x00001CD3, 0x00001CD3},
-{0x00002010, 0x00002027}, {0x00002030, 0x00002043}, {0x00002045, 0x00002051}, {0x00002053, 0x0000205E},
-{0x0000207D, 0x0000207E}, {0x0000208D, 0x0000208E}, {0x00002308, 0x0000230B}, {0x00002329, 0x0000232A},
-{0x00002768, 0x00002775}, {0x000027C5, 0x000027C6}, {0x000027E6, 0x000027EF}, {0x00002983, 0x00002998},
-{0x000029D8, 0x000029DB}, {0x000029FC, 0x000029FD}, {0x00002CF9, 0x00002CFC}, {0x00002CFE, 0x00002CFF},
-{0x00002D70, 0x00002D70}, {0x00002E00, 0x00002E2E}, {0x00002E30, 0x00002E4F}, {0x00002E52, 0x00002E5D},
-{0x00003001, 0x00003003}, {0x00003008, 0x00003011}, {0x00003014, 0x0000301F}, {0x00003030, 0x00003030},
-{0x0000303D, 0x0000303D}, {0x000030A0, 0x000030A0}, {0x000030FB, 0x000030FB}, {0x0000A4FE, 0x0000A4FF},
-{0x0000A60D, 0x0000A60F}, {0x0000A673, 0x0000A673}, {0x0000A67E, 0x0000A67E}, {0x0000A6F2, 0x0000A6F7},
-{0x0000A874, 0x0000A877}, {0x0000A8CE, 0x0000A8CF}, {0x0000A8F8, 0x0000A8FA}, {0x0000A8FC, 0x0000A8FC},
-{0x0000A92E, 0x0000A92F}, {0x0000A95F, 0x0000A95F}, {0x0000A9C1, 0x0000A9CD}, {0x0000A9DE, 0x0000A9DF},
-{0x0000AA5C, 0x0000AA5F}, {0x0000AADE, 0x0000AADF}, {0x0000AAF0, 0x0000AAF1}, {0x0000ABEB, 0x0000ABEB},
-{0x0000FD3E, 0x0000FD3F}, {0x0000FE10, 0x0000FE19}, {0x0000FE30, 0x0000FE52}, {0x0000FE54, 0x0000FE61},
-{0x0000FE63, 0x0000FE63}, {0x0000FE68, 0x0000FE68}, {0x0000FE6A, 0x0000FE6B}, {0x0000FF01, 0x0000FF03},
-{0x0000FF05, 0x0000FF0A}, {0x0000FF0C, 0x0000FF0F}, {0x0000FF1A, 0x0000FF1B}, {0x0000FF1F, 0x0000FF20},
-{0x0000FF3B, 0x0000FF3D}, {0x0000FF3F, 0x0000FF3F}, {0x0000FF5B, 0x0000FF5B}, {0x0000FF5D, 0x0000FF5D},
-{0x0000FF5F, 0x0000FF65}, {0x00010100, 0x00010102}, {0x0001039F, 0x0001039F}, {0x000103D0, 0x000103D0},
-{0x0001056F, 0x0001056F}, {0x00010857, 0x00010857}, {0x0001091F, 0x0001091F}, {0x0001093F, 0x0001093F},
-{0x00010A50, 0x00010A58}, {0x00010A7F, 0x00010A7F}, {0x00010AF0, 0x00010AF6}, {0x00010B39, 0x00010B3F},
-{0x00010B99, 0x00010B9C}, {0x00010EAD, 0x00010EAD}, {0x00010F55, 0x00010F59}, {0x00010F86, 0x00010F89},
-{0x00011047, 0x0001104D}, {0x000110BB, 0x000110BC}, {0x000110BE, 0x000110C1}, {0x00011140, 0x00011143},
-{0x00011174, 0x00011175}, {0x000111C5, 0x000111C8}, {0x000111CD, 0x000111CD}, {0x000111DB, 0x000111DB},
-{0x000111DD, 0x000111DF}, {0x00011238, 0x0001123D}, {0x000112A9, 0x000112A9}, {0x0001144B, 0x0001144F},
-{0x0001145A, 0x0001145B}, {0x0001145D, 0x0001145D}, {0x000114C6, 0x000114C6}, {0x000115C1, 0x000115D7},
-{0x00011641, 0x00011643}, {0x00011660, 0x0001166C}, {0x000116B9, 0x000116B9}, {0x0001173C, 0x0001173E},
-{0x0001183B, 0x0001183B}, {0x00011944, 0x00011946}, {0x000119E2, 0x000119E2}, {0x00011A3F, 0x00011A46},
-{0x00011A9A, 0x00011A9C}, {0x00011A9E, 0x00011AA2}, {0x00011B00, 0x00011B09}, {0x00011C41, 0x00011C45},
-{0x00011C70, 0x00011C71}, {0x00011EF7, 0x00011EF8}, {0x00011F43, 0x00011F4F}, {0x00011FFF, 0x00011FFF},
-{0x00012470, 0x00012474}, {0x00012FF1, 0x00012FF2}, {0x00016A6E, 0x00016A6F}, {0x00016AF5, 0x00016AF5},
-{0x00016B37, 0x00016B3B}, {0x00016B44, 0x00016B44}, {0x00016E97, 0x00016E9A}, {0x00016FE2, 0x00016FE2},
-{0x0001BC9F, 0x0001BC9F}, {0x0001DA87, 0x0001DA8B}, {0x0001E95E, 0x0001E95F},
-};
-
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_symbol = {
-{0x00000024, 0x00000024}, {0x0000002B, 0x0000002B}, {0x0000003C, 0x0000003E}, {0x0000005E, 0x0000005E},
-{0x00000060, 0x00000060}, {0x0000007C, 0x0000007C}, {0x0000007E, 0x0000007E}, {0x000000A2, 0x000000A6},
-{0x000000A8, 0x000000A9}, {0x000000AC, 0x000000AC}, {0x000000AE, 0x000000B1}, {0x000000B4, 0x000000B4},
-{0x000000B8, 0x000000B8}, {0x000000D7, 0x000000D7}, {0x000000F7, 0x000000F7}, {0x000002C2, 0x000002C5},
-{0x000002D2, 0x000002DF}, {0x000002E5, 0x000002EB}, {0x000002ED, 0x000002ED}, {0x000002EF, 0x000002FF},
-{0x00000375, 0x00000375}, {0x00000384, 0x00000385}, {0x000003F6, 0x000003F6}, {0x00000482, 0x00000482},
-{0x0000058D, 0x0000058F}, {0x00000606, 0x00000608}, {0x0000060B, 0x0000060B}, {0x0000060E, 0x0000060F},
-{0x000006DE, 0x000006DE}, {0x000006E9, 0x000006E9}, {0x000006FD, 0x000006FE}, {0x000007F6, 0x000007F6},
-{0x000007FE, 0x000007FF}, {0x00000888, 0x00000888}, {0x000009F2, 0x000009F3}, {0x000009FA, 0x000009FB},
-{0x00000AF1, 0x00000AF1}, {0x00000B70, 0x00000B70}, {0x00000BF3, 0x00000BFA}, {0x00000C7F, 0x00000C7F},
-{0x00000D4F, 0x00000D4F}, {0x00000D79, 0x00000D79}, {0x00000E3F, 0x00000E3F}, {0x00000F01, 0x00000F03},
-{0x00000F13, 0x00000F13}, {0x00000F15, 0x00000F17}, {0x00000F1A, 0x00000F1F}, {0x00000F34, 0x00000F34},
-{0x00000F36, 0x00000F36}, {0x00000F38, 0x00000F38}, {0x00000FBE, 0x00000FC5}, {0x00000FC7, 0x00000FCC},
-{0x00000FCE, 0x00000FCF}, {0x00000FD5, 0x00000FD8}, {0x0000109E, 0x0000109F}, {0x00001390, 0x00001399},
-{0x0000166D, 0x0000166D}, {0x000017DB, 0x000017DB}, {0x00001940, 0x00001940}, {0x000019DE, 0x000019FF},
-{0x00001B61, 0x00001B6A}, {0x00001B74, 0x00001B7C}, {0x00001FBD, 0x00001FBD}, {0x00001FBF, 0x00001FC1},
-{0x00001FCD, 0x00001FCF}, {0x00001FDD, 0x00001FDF}, {0x00001FED, 0x00001FEF}, {0x00001FFD, 0x00001FFE},
-{0x00002044, 0x00002044}, {0x00002052, 0x00002052}, {0x0000207A, 0x0000207C}, {0x0000208A, 0x0000208C},
-{0x000020A0, 0x000020C0}, {0x00002100, 0x00002101}, {0x00002103, 0x00002106}, {0x00002108, 0x00002109},
-{0x00002114, 0x00002114}, {0x00002116, 0x00002118}, {0x0000211E, 0x00002123}, {0x00002125, 0x00002125},
-{0x00002127, 0x00002127}, {0x00002129, 0x00002129}, {0x0000212E, 0x0000212E}, {0x0000213A, 0x0000213B},
-{0x00002140, 0x00002144}, {0x0000214A, 0x0000214D}, {0x0000214F, 0x0000214F}, {0x0000218A, 0x0000218B},
-{0x00002190, 0x00002307}, {0x0000230C, 0x00002328}, {0x0000232B, 0x00002426}, {0x00002440, 0x0000244A},
-{0x0000249C, 0x000024E9}, {0x00002500, 0x00002767}, {0x00002794, 0x000027C4}, {0x000027C7, 0x000027E5},
-{0x000027F0, 0x00002982}, {0x00002999, 0x000029D7}, {0x000029DC, 0x000029FB}, {0x000029FE, 0x00002B73},
-{0x00002B76, 0x00002B95}, {0x00002B97, 0x00002BFF}, {0x00002CE5, 0x00002CEA}, {0x00002E50, 0x00002E51},
-{0x00002E80, 0x00002E99}, {0x00002E9B, 0x00002EF3}, {0x00002F00, 0x00002FD5}, {0x00002FF0, 0x00002FFF},
-{0x00003004, 0x00003004}, {0x00003012, 0x00003013}, {0x00003020, 0x00003020}, {0x00003036, 0x00003037},
-{0x0000303E, 0x0000303F}, {0x0000309B, 0x0000309C}, {0x00003190, 0x00003191}, {0x00003196, 0x0000319F},
-{0x000031C0, 0x000031E3}, {0x000031EF, 0x000031EF}, {0x00003200, 0x0000321E}, {0x0000322A, 0x00003247},
-{0x00003250, 0x00003250}, {0x00003260, 0x0000327F}, {0x0000328A, 0x000032B0}, {0x000032C0, 0x000033FF},
-{0x00004DC0, 0x00004DFF}, {0x0000A490, 0x0000A4C6}, {0x0000A700, 0x0000A716}, {0x0000A720, 0x0000A721},
-{0x0000A789, 0x0000A78A}, {0x0000A828, 0x0000A82B}, {0x0000A836, 0x0000A839}, {0x0000AA77, 0x0000AA79},
-{0x0000AB5B, 0x0000AB5B}, {0x0000AB6A, 0x0000AB6B}, {0x0000FB29, 0x0000FB29}, {0x0000FBB2, 0x0000FBC2},
-{0x0000FD40, 0x0000FD4F}, {0x0000FDCF, 0x0000FDCF}, {0x0000FDFC, 0x0000FDFF}, {0x0000FE62, 0x0000FE62},
-{0x0000FE64, 0x0000FE66}, {0x0000FE69, 0x0000FE69}, {0x0000FF04, 0x0000FF04}, {0x0000FF0B, 0x0000FF0B},
-{0x0000FF1C, 0x0000FF1E}, {0x0000FF3E, 0x0000FF3E}, {0x0000FF40, 0x0000FF40}, {0x0000FF5C, 0x0000FF5C},
-{0x0000FF5E, 0x0000FF5E}, {0x0000FFE0, 0x0000FFE6}, {0x0000FFE8, 0x0000FFEE}, {0x0000FFFC, 0x0000FFFD},
-{0x00010137, 0x0001013F}, {0x00010179, 0x00010189}, {0x0001018C, 0x0001018E}, {0x00010190, 0x0001019C},
-{0x000101A0, 0x000101A0}, {0x000101D0, 0x000101FC}, {0x00010877, 0x00010878}, {0x00010AC8, 0x00010AC8},
-{0x0001173F, 0x0001173F}, {0x00011FD5, 0x00011FF1}, {0x00016B3C, 0x00016B3F}, {0x00016B45, 0x00016B45},
-{0x0001BC9C, 0x0001BC9C}, {0x0001CF50, 0x0001CFC3}, {0x0001D000, 0x0001D0F5}, {0x0001D100, 0x0001D126},
-{0x0001D129, 0x0001D164}, {0x0001D16A, 0x0001D16C}, {0x0001D183, 0x0001D184}, {0x0001D18C, 0x0001D1A9},
-{0x0001D1AE, 0x0001D1EA}, {0x0001D200, 0x0001D241}, {0x0001D245, 0x0001D245}, {0x0001D300, 0x0001D356},
-{0x0001D6C1, 0x0001D6C1}, {0x0001D6DB, 0x0001D6DB}, {0x0001D6FB, 0x0001D6FB}, {0x0001D715, 0x0001D715},
-{0x0001D735, 0x0001D735}, {0x0001D74F, 0x0001D74F}, {0x0001D76F, 0x0001D76F}, {0x0001D789, 0x0001D789},
-{0x0001D7A9, 0x0001D7A9}, {0x0001D7C3, 0x0001D7C3}, {0x0001D800, 0x0001D9FF}, {0x0001DA37, 0x0001DA3A},
-{0x0001DA6D, 0x0001DA74}, {0x0001DA76, 0x0001DA83}, {0x0001DA85, 0x0001DA86}, {0x0001E14F, 0x0001E14F},
-{0x0001E2FF, 0x0001E2FF}, {0x0001ECAC, 0x0001ECAC}, {0x0001ECB0, 0x0001ECB0}, {0x0001ED2E, 0x0001ED2E},
-{0x0001EEF0, 0x0001EEF1}, {0x0001F000, 0x0001F02B}, {0x0001F030, 0x0001F093}, {0x0001F0A0, 0x0001F0AE},
-{0x0001F0B1, 0x0001F0BF}, {0x0001F0C1, 0x0001F0CF}, {0x0001F0D1, 0x0001F0F5}, {0x0001F10D, 0x0001F1AD},
-{0x0001F1E6, 0x0001F202}, {0x0001F210, 0x0001F23B}, {0x0001F240, 0x0001F248}, {0x0001F250, 0x0001F251},
-{0x0001F260, 0x0001F265}, {0x0001F300, 0x0001F6D7}, {0x0001F6DC, 0x0001F6EC}, {0x0001F6F0, 0x0001F6FC},
-{0x0001F700, 0x0001F776}, {0x0001F77B, 0x0001F7D9}, {0x0001F7E0, 0x0001F7EB}, {0x0001F7F0, 0x0001F7F0},
-{0x0001F800, 0x0001F80B}, {0x0001F810, 0x0001F847}, {0x0001F850, 0x0001F859}, {0x0001F860, 0x0001F887},
-{0x0001F890, 0x0001F8AD}, {0x0001F8B0, 0x0001F8B1}, {0x0001F900, 0x0001FA53}, {0x0001FA60, 0x0001FA6D},
-{0x0001FA70, 0x0001FA7C}, {0x0001FA80, 0x0001FA88}, {0x0001FA90, 0x0001FABD}, {0x0001FABF, 0x0001FAC5},
-{0x0001FACE, 0x0001FADB}, {0x0001FAE0, 0x0001FAE8}, {0x0001FAF0, 0x0001FAF8}, {0x0001FB00, 0x0001FB92},
-{0x0001FB94, 0x0001FBCA},
-};
-
-const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_control = {
-{0x00000000, 0x0000001F}, {0x0000007F, 0x0000009F}, {0x000000AD, 0x000000AD}, {0x00000378, 0x00000379},
-{0x00000380, 0x00000383}, {0x0000038B, 0x0000038B}, {0x0000038D, 0x0000038D}, {0x000003A2, 0x000003A2},
-{0x00000530, 0x00000530}, {0x00000557, 0x00000558}, {0x0000058B, 0x0000058C}, {0x00000590, 0x00000590},
-{0x000005C8, 0x000005CF}, {0x000005EB, 0x000005EE}, {0x000005F5, 0x00000605}, {0x0000061C, 0x0000061C},
-{0x000006DD, 0x000006DD}, {0x0000070E, 0x0000070F}, {0x0000074B, 0x0000074C}, {0x000007B2, 0x000007BF},
-{0x000007FB, 0x000007FC}, {0x0000082E, 0x0000082F}, {0x0000083F, 0x0000083F}, {0x0000085C, 0x0000085D},
-{0x0000085F, 0x0000085F}, {0x0000086B, 0x0000086F}, {0x0000088F, 0x00000897}, {0x000008E2, 0x000008E2},
-{0x00000984, 0x00000984}, {0x0000098D, 0x0000098E}, {0x00000991, 0x00000992}, {0x000009A9, 0x000009A9},
-{0x000009B1, 0x000009B1}, {0x000009B3, 0x000009B5}, {0x000009BA, 0x000009BB}, {0x000009C5, 0x000009C6},
-{0x000009C9, 0x000009CA}, {0x000009CF, 0x000009D6}, {0x000009D8, 0x000009DB}, {0x000009DE, 0x000009DE},
-{0x000009E4, 0x000009E5}, {0x000009FF, 0x00000A00}, {0x00000A04, 0x00000A04}, {0x00000A0B, 0x00000A0E},
-{0x00000A11, 0x00000A12}, {0x00000A29, 0x00000A29}, {0x00000A31, 0x00000A31}, {0x00000A34, 0x00000A34},
-{0x00000A37, 0x00000A37}, {0x00000A3A, 0x00000A3B}, {0x00000A3D, 0x00000A3D}, {0x00000A43, 0x00000A46},
-{0x00000A49, 0x00000A4A}, {0x00000A4E, 0x00000A50}, {0x00000A52, 0x00000A58}, {0x00000A5D, 0x00000A5D},
-{0x00000A5F, 0x00000A65}, {0x00000A77, 0x00000A80}, {0x00000A84, 0x00000A84}, {0x00000A8E, 0x00000A8E},
-{0x00000A92, 0x00000A92}, {0x00000AA9, 0x00000AA9}, {0x00000AB1, 0x00000AB1}, {0x00000AB4, 0x00000AB4},
-{0x00000ABA, 0x00000ABB}, {0x00000AC6, 0x00000AC6}, {0x00000ACA, 0x00000ACA}, {0x00000ACE, 0x00000ACF},
-{0x00000AD1, 0x00000ADF}, {0x00000AE4, 0x00000AE5}, {0x00000AF2, 0x00000AF8}, {0x00000B00, 0x00000B00},
-{0x00000B04, 0x00000B04}, {0x00000B0D, 0x00000B0E}, {0x00000B11, 0x00000B12}, {0x00000B29, 0x00000B29},
-{0x00000B31, 0x00000B31}, {0x00000B34, 0x00000B34}, {0x00000B3A, 0x00000B3B}, {0x00000B45, 0x00000B46},
-{0x00000B49, 0x00000B4A}, {0x00000B4E, 0x00000B54}, {0x00000B58, 0x00000B5B}, {0x00000B5E, 0x00000B5E},
-{0x00000B64, 0x00000B65}, {0x00000B78, 0x00000B81}, {0x00000B84, 0x00000B84}, {0x00000B8B, 0x00000B8D},
-{0x00000B91, 0x00000B91}, {0x00000B96, 0x00000B98}, {0x00000B9B, 0x00000B9B}, {0x00000B9D, 0x00000B9D},
-{0x00000BA0, 0x00000BA2}, {0x00000BA5, 0x00000BA7}, {0x00000BAB, 0x00000BAD}, {0x00000BBA, 0x00000BBD},
-{0x00000BC3, 0x00000BC5}, {0x00000BC9, 0x00000BC9}, {0x00000BCE, 0x00000BCF}, {0x00000BD1, 0x00000BD6},
-{0x00000BD8, 0x00000BE5}, {0x00000BFB, 0x00000BFF}, {0x00000C0D, 0x00000C0D}, {0x00000C11, 0x00000C11},
-{0x00000C29, 0x00000C29}, {0x00000C3A, 0x00000C3B}, {0x00000C45, 0x00000C45}, {0x00000C49, 0x00000C49},
-{0x00000C4E, 0x00000C54}, {0x00000C57, 0x00000C57}, {0x00000C5B, 0x00000C5C}, {0x00000C5E, 0x00000C5F},
-{0x00000C64, 0x00000C65}, {0x00000C70, 0x00000C76}, {0x00000C8D, 0x00000C8D}, {0x00000C91, 0x00000C91},
-{0x00000CA9, 0x00000CA9}, {0x00000CB4, 0x00000CB4}, {0x00000CBA, 0x00000CBB}, {0x00000CC5, 0x00000CC5},
-{0x00000CC9, 0x00000CC9}, {0x00000CCE, 0x00000CD4}, {0x00000CD7, 0x00000CDC}, {0x00000CDF, 0x00000CDF},
-{0x00000CE4, 0x00000CE5}, {0x00000CF0, 0x00000CF0}, {0x00000CF4, 0x00000CFF}, {0x00000D0D, 0x00000D0D},
-{0x00000D11, 0x00000D11}, {0x00000D45, 0x00000D45}, {0x00000D49, 0x00000D49}, {0x00000D50, 0x00000D53},
-{0x00000D64, 0x00000D65}, {0x00000D80, 0x00000D80}, {0x00000D84, 0x00000D84}, {0x00000D97, 0x00000D99},
-{0x00000DB2, 0x00000DB2}, {0x00000DBC, 0x00000DBC}, {0x00000DBE, 0x00000DBF}, {0x00000DC7, 0x00000DC9},
-{0x00000DCB, 0x00000DCE}, {0x00000DD5, 0x00000DD5}, {0x00000DD7, 0x00000DD7}, {0x00000DE0, 0x00000DE5},
-{0x00000DF0, 0x00000DF1}, {0x00000DF5, 0x00000E00}, {0x00000E3B, 0x00000E3E}, {0x00000E5C, 0x00000E80},
-{0x00000E83, 0x00000E83}, {0x00000E85, 0x00000E85}, {0x00000E8B, 0x00000E8B}, {0x00000EA4, 0x00000EA4},
-{0x00000EA6, 0x00000EA6}, {0x00000EBE, 0x00000EBF}, {0x00000EC5, 0x00000EC5}, {0x00000EC7, 0x00000EC7},
-{0x00000ECF, 0x00000ECF}, {0x00000EDA, 0x00000EDB}, {0x00000EE0, 0x00000EFF}, {0x00000F48, 0x00000F48},
-{0x00000F6D, 0x00000F70}, {0x00000F98, 0x00000F98}, {0x00000FBD, 0x00000FBD}, {0x00000FCD, 0x00000FCD},
-{0x00000FDB, 0x00000FFF}, {0x000010C6, 0x000010C6}, {0x000010C8, 0x000010CC}, {0x000010CE, 0x000010CF},
-{0x00001249, 0x00001249}, {0x0000124E, 0x0000124F}, {0x00001257, 0x00001257}, {0x00001259, 0x00001259},
-{0x0000125E, 0x0000125F}, {0x00001289, 0x00001289}, {0x0000128E, 0x0000128F}, {0x000012B1, 0x000012B1},
-{0x000012B6, 0x000012B7}, {0x000012BF, 0x000012BF}, {0x000012C1, 0x000012C1}, {0x000012C6, 0x000012C7},
-{0x000012D7, 0x000012D7}, {0x00001311, 0x00001311}, {0x00001316, 0x00001317}, {0x0000135B, 0x0000135C},
-{0x0000137D, 0x0000137F}, {0x0000139A, 0x0000139F}, {0x000013F6, 0x000013F7}, {0x000013FE, 0x000013FF},
-{0x0000169D, 0x0000169F}, {0x000016F9, 0x000016FF}, {0x00001716, 0x0000171E}, {0x00001737, 0x0000173F},
-{0x00001754, 0x0000175F}, {0x0000176D, 0x0000176D}, {0x00001771, 0x00001771}, {0x00001774, 0x0000177F},
-{0x000017DE, 0x000017DF}, {0x000017EA, 0x000017EF}, {0x000017FA, 0x000017FF}, {0x0000180E, 0x0000180E},
-{0x0000181A, 0x0000181F}, {0x00001879, 0x0000187F}, {0x000018AB, 0x000018AF}, {0x000018F6, 0x000018FF},
-{0x0000191F, 0x0000191F}, {0x0000192C, 0x0000192F}, {0x0000193C, 0x0000193F}, {0x00001941, 0x00001943},
-{0x0000196E, 0x0000196F}, {0x00001975, 0x0000197F}, {0x000019AC, 0x000019AF}, {0x000019CA, 0x000019CF},
-{0x000019DB, 0x000019DD}, {0x00001A1C, 0x00001A1D}, {0x00001A5F, 0x00001A5F}, {0x00001A7D, 0x00001A7E},
-{0x00001A8A, 0x00001A8F}, {0x00001A9A, 0x00001A9F}, {0x00001AAE, 0x00001AAF}, {0x00001ACF, 0x00001AFF},
-{0x00001B4D, 0x00001B4F}, {0x00001B7F, 0x00001B7F}, {0x00001BF4, 0x00001BFB}, {0x00001C38, 0x00001C3A},
-{0x00001C4A, 0x00001C4C}, {0x00001C89, 0x00001C8F}, {0x00001CBB, 0x00001CBC}, {0x00001CC8, 0x00001CCF},
-{0x00001CFB, 0x00001CFF}, {0x00001F16, 0x00001F17}, {0x00001F1E, 0x00001F1F}, {0x00001F46, 0x00001F47},
-{0x00001F4E, 0x00001F4F}, {0x00001F58, 0x00001F58}, {0x00001F5A, 0x00001F5A}, {0x00001F5C, 0x00001F5C},
-{0x00001F5E, 0x00001F5E}, {0x00001F7E, 0x00001F7F}, {0x00001FB5, 0x00001FB5}, {0x00001FC5, 0x00001FC5},
-{0x00001FD4, 0x00001FD5}, {0x00001FDC, 0x00001FDC}, {0x00001FF0, 0x00001FF1}, {0x00001FF5, 0x00001FF5},
-{0x00001FFF, 0x00001FFF}, {0x0000200B, 0x0000200F}, {0x0000202A, 0x0000202E}, {0x00002060, 0x0000206F},
-{0x00002072, 0x00002073}, {0x0000208F, 0x0000208F}, {0x0000209D, 0x0000209F}, {0x000020C1, 0x000020CF},
-{0x000020F1, 0x000020FF}, {0x0000218C, 0x0000218F}, {0x00002427, 0x0000243F}, {0x0000244B, 0x0000245F},
-{0x00002B74, 0x00002B75}, {0x00002B96, 0x00002B96}, {0x00002CF4, 0x00002CF8}, {0x00002D26, 0x00002D26},
-{0x00002D28, 0x00002D2C}, {0x00002D2E, 0x00002D2F}, {0x00002D68, 0x00002D6E}, {0x00002D71, 0x00002D7E},
-{0x00002D97, 0x00002D9F}, {0x00002DA7, 0x00002DA7}, {0x00002DAF, 0x00002DAF}, {0x00002DB7, 0x00002DB7},
-{0x00002DBF, 0x00002DBF}, {0x00002DC7, 0x00002DC7}, {0x00002DCF, 0x00002DCF}, {0x00002DD7, 0x00002DD7},
-{0x00002DDF, 0x00002DDF}, {0x00002E5E, 0x00002E7F}, {0x00002E9A, 0x00002E9A}, {0x00002EF4, 0x00002EFF},
-{0x00002FD6, 0x00002FEF}, {0x00003040, 0x00003040}, {0x00003097, 0x00003098}, {0x00003100, 0x00003104},
-{0x00003130, 0x00003130}, {0x0000318F, 0x0000318F}, {0x000031E4, 0x000031EE}, {0x0000321F, 0x0000321F},
-{0x0000A48D, 0x0000A48F}, {0x0000A4C7, 0x0000A4CF}, {0x0000A62C, 0x0000A63F}, {0x0000A6F8, 0x0000A6FF},
-{0x0000A7CB, 0x0000A7CF}, {0x0000A7D2, 0x0000A7D2}, {0x0000A7D4, 0x0000A7D4}, {0x0000A7DA, 0x0000A7F1},
-{0x0000A82D, 0x0000A82F}, {0x0000A83A, 0x0000A83F}, {0x0000A878, 0x0000A87F}, {0x0000A8C6, 0x0000A8CD},
-{0x0000A8DA, 0x0000A8DF}, {0x0000A954, 0x0000A95E}, {0x0000A97D, 0x0000A97F}, {0x0000A9CE, 0x0000A9CE},
-{0x0000A9DA, 0x0000A9DD}, {0x0000A9FF, 0x0000A9FF}, {0x0000AA37, 0x0000AA3F}, {0x0000AA4E, 0x0000AA4F},
-{0x0000AA5A, 0x0000AA5B}, {0x0000AAC3, 0x0000AADA}, {0x0000AAF7, 0x0000AB00}, {0x0000AB07, 0x0000AB08},
-{0x0000AB0F, 0x0000AB10}, {0x0000AB17, 0x0000AB1F}, {0x0000AB27, 0x0000AB27}, {0x0000AB2F, 0x0000AB2F},
-{0x0000AB6C, 0x0000AB6F}, {0x0000ABEE, 0x0000ABEF}, {0x0000ABFA, 0x0000ABFF}, {0x0000D7A4, 0x0000D7AF},
-{0x0000D7C7, 0x0000D7CA}, {0x0000D7FC, 0x0000F8FF}, {0x0000FA6E, 0x0000FA6F}, {0x0000FADA, 0x0000FAFF},
-{0x0000FB07, 0x0000FB12}, {0x0000FB18, 0x0000FB1C}, {0x0000FB37, 0x0000FB37}, {0x0000FB3D, 0x0000FB3D},
-{0x0000FB3F, 0x0000FB3F}, {0x0000FB42, 0x0000FB42}, {0x0000FB45, 0x0000FB45}, {0x0000FBC3, 0x0000FBD2},
-{0x0000FD90, 0x0000FD91}, {0x0000FDC8, 0x0000FDCE}, {0x0000FDD0, 0x0000FDEF}, {0x0000FE1A, 0x0000FE1F},
-{0x0000FE53, 0x0000FE53}, {0x0000FE67, 0x0000FE67}, {0x0000FE6C, 0x0000FE6F}, {0x0000FE75, 0x0000FE75},
-{0x0000FEFD, 0x0000FF00}, {0x0000FFBF, 0x0000FFC1}, {0x0000FFC8, 0x0000FFC9}, {0x0000FFD0, 0x0000FFD1},
-{0x0000FFD8, 0x0000FFD9}, {0x0000FFDD, 0x0000FFDF}, {0x0000FFE7, 0x0000FFE7}, {0x0000FFEF, 0x0000FFFB},
-{0x0000FFFE, 0x0000FFFF}, {0x0001000C, 0x0001000C}, {0x00010027, 0x00010027}, {0x0001003B, 0x0001003B},
-{0x0001003E, 0x0001003E}, {0x0001004E, 0x0001004F}, {0x0001005E, 0x0001007F}, {0x000100FB, 0x000100FF},
-{0x00010103, 0x00010106}, {0x00010134, 0x00010136}, {0x0001018F, 0x0001018F}, {0x0001019D, 0x0001019F},
-{0x000101A1, 0x000101CF}, {0x000101FE, 0x0001027F}, {0x0001029D, 0x0001029F}, {0x000102D1, 0x000102DF},
-{0x000102FC, 0x000102FF}, {0x00010324, 0x0001032C}, {0x0001034B, 0x0001034F}, {0x0001037B, 0x0001037F},
-{0x0001039E, 0x0001039E}, {0x000103C4, 0x000103C7}, {0x000103D6, 0x000103FF}, {0x0001049E, 0x0001049F},
-{0x000104AA, 0x000104AF}, {0x000104D4, 0x000104D7}, {0x000104FC, 0x000104FF}, {0x00010528, 0x0001052F},
-{0x00010564, 0x0001056E}, {0x0001057B, 0x0001057B}, {0x0001058B, 0x0001058B}, {0x00010593, 0x00010593},
-{0x00010596, 0x00010596}, {0x000105A2, 0x000105A2}, {0x000105B2, 0x000105B2}, {0x000105BA, 0x000105BA},
-{0x000105BD, 0x000105FF}, {0x00010737, 0x0001073F}, {0x00010756, 0x0001075F}, {0x00010768, 0x0001077F},
-{0x00010786, 0x00010786}, {0x000107B1, 0x000107B1}, {0x000107BB, 0x000107FF}, {0x00010806, 0x00010807},
-{0x00010809, 0x00010809}, {0x00010836, 0x00010836}, {0x00010839, 0x0001083B}, {0x0001083D, 0x0001083E},
-{0x00010856, 0x00010856}, {0x0001089F, 0x000108A6}, {0x000108B0, 0x000108DF}, {0x000108F3, 0x000108F3},
-{0x000108F6, 0x000108FA}, {0x0001091C, 0x0001091E}, {0x0001093A, 0x0001093E}, {0x00010940, 0x0001097F},
-{0x000109B8, 0x000109BB}, {0x000109D0, 0x000109D1}, {0x00010A04, 0x00010A04}, {0x00010A07, 0x00010A0B},
-{0x00010A14, 0x00010A14}, {0x00010A18, 0x00010A18}, {0x00010A36, 0x00010A37}, {0x00010A3B, 0x00010A3E},
-{0x00010A49, 0x00010A4F}, {0x00010A59, 0x00010A5F}, {0x00010AA0, 0x00010ABF}, {0x00010AE7, 0x00010AEA},
-{0x00010AF7, 0x00010AFF}, {0x00010B36, 0x00010B38}, {0x00010B56, 0x00010B57}, {0x00010B73, 0x00010B77},
-{0x00010B92, 0x00010B98}, {0x00010B9D, 0x00010BA8}, {0x00010BB0, 0x00010BFF}, {0x00010C49, 0x00010C7F},
-{0x00010CB3, 0x00010CBF}, {0x00010CF3, 0x00010CF9}, {0x00010D28, 0x00010D2F}, {0x00010D3A, 0x00010E5F},
-{0x00010E7F, 0x00010E7F}, {0x00010EAA, 0x00010EAA}, {0x00010EAE, 0x00010EAF}, {0x00010EB2, 0x00010EFC},
-{0x00010F28, 0x00010F2F}, {0x00010F5A, 0x00010F6F}, {0x00010F8A, 0x00010FAF}, {0x00010FCC, 0x00010FDF},
-{0x00010FF7, 0x00010FFF}, {0x0001104E, 0x00011051}, {0x00011076, 0x0001107E}, {0x000110BD, 0x000110BD},
-{0x000110C3, 0x000110CF}, {0x000110E9, 0x000110EF}, {0x000110FA, 0x000110FF}, {0x00011135, 0x00011135},
-{0x00011148, 0x0001114F}, {0x00011177, 0x0001117F}, {0x000111E0, 0x000111E0}, {0x000111F5, 0x000111FF},
-{0x00011212, 0x00011212}, {0x00011242, 0x0001127F}, {0x00011287, 0x00011287}, {0x00011289, 0x00011289},
-{0x0001128E, 0x0001128E}, {0x0001129E, 0x0001129E}, {0x000112AA, 0x000112AF}, {0x000112EB, 0x000112EF},
-{0x000112FA, 0x000112FF}, {0x00011304, 0x00011304}, {0x0001130D, 0x0001130E}, {0x00011311, 0x00011312},
-{0x00011329, 0x00011329}, {0x00011331, 0x00011331}, {0x00011334, 0x00011334}, {0x0001133A, 0x0001133A},
-{0x00011345, 0x00011346}, {0x00011349, 0x0001134A}, {0x0001134E, 0x0001134F}, {0x00011351, 0x00011356},
-{0x00011358, 0x0001135C}, {0x00011364, 0x00011365}, {0x0001136D, 0x0001136F}, {0x00011375, 0x000113FF},
-{0x0001145C, 0x0001145C}, {0x00011462, 0x0001147F}, {0x000114C8, 0x000114CF}, {0x000114DA, 0x0001157F},
-{0x000115B6, 0x000115B7}, {0x000115DE, 0x000115FF}, {0x00011645, 0x0001164F}, {0x0001165A, 0x0001165F},
-{0x0001166D, 0x0001167F}, {0x000116BA, 0x000116BF}, {0x000116CA, 0x000116FF}, {0x0001171B, 0x0001171C},
-{0x0001172C, 0x0001172F}, {0x00011747, 0x000117FF}, {0x0001183C, 0x0001189F}, {0x000118F3, 0x000118FE},
-{0x00011907, 0x00011908}, {0x0001190A, 0x0001190B}, {0x00011914, 0x00011914}, {0x00011917, 0x00011917},
-{0x00011936, 0x00011936}, {0x00011939, 0x0001193A}, {0x00011947, 0x0001194F}, {0x0001195A, 0x0001199F},
-{0x000119A8, 0x000119A9}, {0x000119D8, 0x000119D9}, {0x000119E5, 0x000119FF}, {0x00011A48, 0x00011A4F},
-{0x00011AA3, 0x00011AAF}, {0x00011AF9, 0x00011AFF}, {0x00011B0A, 0x00011BFF}, {0x00011C09, 0x00011C09},
-{0x00011C37, 0x00011C37}, {0x00011C46, 0x00011C4F}, {0x00011C6D, 0x00011C6F}, {0x00011C90, 0x00011C91},
-{0x00011CA8, 0x00011CA8}, {0x00011CB7, 0x00011CFF}, {0x00011D07, 0x00011D07}, {0x00011D0A, 0x00011D0A},
-{0x00011D37, 0x00011D39}, {0x00011D3B, 0x00011D3B}, {0x00011D3E, 0x00011D3E}, {0x00011D48, 0x00011D4F},
-{0x00011D5A, 0x00011D5F}, {0x00011D66, 0x00011D66}, {0x00011D69, 0x00011D69}, {0x00011D8F, 0x00011D8F},
-{0x00011D92, 0x00011D92}, {0x00011D99, 0x00011D9F}, {0x00011DAA, 0x00011EDF}, {0x00011EF9, 0x00011EFF},
-{0x00011F11, 0x00011F11}, {0x00011F3B, 0x00011F3D}, {0x00011F5A, 0x00011FAF}, {0x00011FB1, 0x00011FBF},
-{0x00011FF2, 0x00011FFE}, {0x0001239A, 0x000123FF}, {0x0001246F, 0x0001246F}, {0x00012475, 0x0001247F},
-{0x00012544, 0x00012F8F}, {0x00012FF3, 0x00012FFF}, {0x00013430, 0x0001343F}, {0x00013456, 0x000143FF},
-{0x00014647, 0x000167FF}, {0x00016A39, 0x00016A3F}, {0x00016A5F, 0x00016A5F}, {0x00016A6A, 0x00016A6D},
-{0x00016ABF, 0x00016ABF}, {0x00016ACA, 0x00016ACF}, {0x00016AEE, 0x00016AEF}, {0x00016AF6, 0x00016AFF},
-{0x00016B46, 0x00016B4F}, {0x00016B5A, 0x00016B5A}, {0x00016B62, 0x00016B62}, {0x00016B78, 0x00016B7C},
-{0x00016B90, 0x00016E3F}, {0x00016E9B, 0x00016EFF}, {0x00016F4B, 0x00016F4E}, {0x00016F88, 0x00016F8E},
-{0x00016FA0, 0x00016FDF}, {0x00016FE5, 0x00016FEF}, {0x00016FF2, 0x00016FFF}, {0x000187F8, 0x000187FF},
-{0x00018CD6, 0x00018CFF}, {0x00018D09, 0x0001AFEF}, {0x0001AFF4, 0x0001AFF4}, {0x0001AFFC, 0x0001AFFC},
-{0x0001AFFF, 0x0001AFFF}, {0x0001B123, 0x0001B131}, {0x0001B133, 0x0001B14F}, {0x0001B153, 0x0001B154},
-{0x0001B156, 0x0001B163}, {0x0001B168, 0x0001B16F}, {0x0001B2FC, 0x0001BBFF}, {0x0001BC6B, 0x0001BC6F},
-{0x0001BC7D, 0x0001BC7F}, {0x0001BC89, 0x0001BC8F}, {0x0001BC9A, 0x0001BC9B}, {0x0001BCA0, 0x0001CEFF},
-{0x0001CF2E, 0x0001CF2F}, {0x0001CF47, 0x0001CF4F}, {0x0001CFC4, 0x0001CFFF}, {0x0001D0F6, 0x0001D0FF},
-{0x0001D127, 0x0001D128}, {0x0001D173, 0x0001D17A}, {0x0001D1EB, 0x0001D1FF}, {0x0001D246, 0x0001D2BF},
-{0x0001D2D4, 0x0001D2DF}, {0x0001D2F4, 0x0001D2FF}, {0x0001D357, 0x0001D35F}, {0x0001D379, 0x0001D3FF},
-{0x0001D455, 0x0001D455}, {0x0001D49D, 0x0001D49D}, {0x0001D4A0, 0x0001D4A1}, {0x0001D4A3, 0x0001D4A4},
-{0x0001D4A7, 0x0001D4A8}, {0x0001D4AD, 0x0001D4AD}, {0x0001D4BA, 0x0001D4BA}, {0x0001D4BC, 0x0001D4BC},
-{0x0001D4C4, 0x0001D4C4}, {0x0001D506, 0x0001D506}, {0x0001D50B, 0x0001D50C}, {0x0001D515, 0x0001D515},
-{0x0001D51D, 0x0001D51D}, {0x0001D53A, 0x0001D53A}, {0x0001D53F, 0x0001D53F}, {0x0001D545, 0x0001D545},
-{0x0001D547, 0x0001D549}, {0x0001D551, 0x0001D551}, {0x0001D6A6, 0x0001D6A7}, {0x0001D7CC, 0x0001D7CD},
-{0x0001DA8C, 0x0001DA9A}, {0x0001DAA0, 0x0001DAA0}, {0x0001DAB0, 0x0001DEFF}, {0x0001DF1F, 0x0001DF24},
-{0x0001DF2B, 0x0001DFFF}, {0x0001E007, 0x0001E007}, {0x0001E019, 0x0001E01A}, {0x0001E022, 0x0001E022},
-{0x0001E025, 0x0001E025}, {0x0001E02B, 0x0001E02F}, {0x0001E06E, 0x0001E08E}, {0x0001E090, 0x0001E0FF},
-{0x0001E12D, 0x0001E12F}, {0x0001E13E, 0x0001E13F}, {0x0001E14A, 0x0001E14D}, {0x0001E150, 0x0001E28F},
-{0x0001E2AF, 0x0001E2BF}, {0x0001E2FA, 0x0001E2FE}, {0x0001E300, 0x0001E4CF}, {0x0001E4FA, 0x0001E7DF},
-{0x0001E7E7, 0x0001E7E7}, {0x0001E7EC, 0x0001E7EC}, {0x0001E7EF, 0x0001E7EF}, {0x0001E7FF, 0x0001E7FF},
-{0x0001E8C5, 0x0001E8C6}, {0x0001E8D7, 0x0001E8FF}, {0x0001E94C, 0x0001E94F}, {0x0001E95A, 0x0001E95D},
-{0x0001E960, 0x0001EC70}, {0x0001ECB5, 0x0001ED00}, {0x0001ED3E, 0x0001EDFF}, {0x0001EE04, 0x0001EE04},
-{0x0001EE20, 0x0001EE20}, {0x0001EE23, 0x0001EE23}, {0x0001EE25, 0x0001EE26}, {0x0001EE28, 0x0001EE28},
-{0x0001EE33, 0x0001EE33}, {0x0001EE38, 0x0001EE38}, {0x0001EE3A, 0x0001EE3A}, {0x0001EE3C, 0x0001EE41},
-{0x0001EE43, 0x0001EE46}, {0x0001EE48, 0x0001EE48}, {0x0001EE4A, 0x0001EE4A}, {0x0001EE4C, 0x0001EE4C},
-{0x0001EE50, 0x0001EE50}, {0x0001EE53, 0x0001EE53}, {0x0001EE55, 0x0001EE56}, {0x0001EE58, 0x0001EE58},
-{0x0001EE5A, 0x0001EE5A}, {0x0001EE5C, 0x0001EE5C}, {0x0001EE5E, 0x0001EE5E}, {0x0001EE60, 0x0001EE60},
-{0x0001EE63, 0x0001EE63}, {0x0001EE65, 0x0001EE66}, {0x0001EE6B, 0x0001EE6B}, {0x0001EE73, 0x0001EE73},
-{0x0001EE78, 0x0001EE78}, {0x0001EE7D, 0x0001EE7D}, {0x0001EE7F, 0x0001EE7F}, {0x0001EE8A, 0x0001EE8A},
-{0x0001EE9C, 0x0001EEA0}, {0x0001EEA4, 0x0001EEA4}, {0x0001EEAA, 0x0001EEAA}, {0x0001EEBC, 0x0001EEEF},
-{0x0001EEF2, 0x0001EFFF}, {0x0001F02C, 0x0001F02F}, {0x0001F094, 0x0001F09F}, {0x0001F0AF, 0x0001F0B0},
-{0x0001F0C0, 0x0001F0C0}, {0x0001F0D0, 0x0001F0D0}, {0x0001F0F6, 0x0001F0FF}, {0x0001F1AE, 0x0001F1E5},
-{0x0001F203, 0x0001F20F}, {0x0001F23C, 0x0001F23F}, {0x0001F249, 0x0001F24F}, {0x0001F252, 0x0001F25F},
-{0x0001F266, 0x0001F2FF}, {0x0001F6D8, 0x0001F6DB}, {0x0001F6ED, 0x0001F6EF}, {0x0001F6FD, 0x0001F6FF},
-{0x0001F777, 0x0001F77A}, {0x0001F7DA, 0x0001F7DF}, {0x0001F7EC, 0x0001F7EF}, {0x0001F7F1, 0x0001F7FF},
-{0x0001F80C, 0x0001F80F}, {0x0001F848, 0x0001F84F}, {0x0001F85A, 0x0001F85F}, {0x0001F888, 0x0001F88F},
-{0x0001F8AE, 0x0001F8AF}, {0x0001F8B2, 0x0001F8FF}, {0x0001FA54, 0x0001FA5F}, {0x0001FA6E, 0x0001FA6F},
-{0x0001FA7D, 0x0001FA7F}, {0x0001FA89, 0x0001FA8F}, {0x0001FABE, 0x0001FABE}, {0x0001FAC6, 0x0001FACD},
-{0x0001FADC, 0x0001FADF}, {0x0001FAE9, 0x0001FAEF}, {0x0001FAF9, 0x0001FAFF}, {0x0001FB93, 0x0001FB93},
-{0x0001FBCB, 0x0001FBEF}, {0x0001FBFA, 0x0001FFFF}, {0x0002A6E0, 0x0002A6FF}, {0x0002B73A, 0x0002B73F},
-{0x0002B81E, 0x0002B81F}, {0x0002CEA2, 0x0002CEAF}, {0x0002EBE1, 0x0002EBEF}, {0x0002EE5E, 0x0002F7FF},
-{0x0002FA1E, 0x0002FFFF}, {0x0003134B, 0x0003134F}, {0x000323B0, 0x000E00FF}, {0x000E01F0, 0x0010FFFF},
-};
-
-const std::map<char32_t, char32_t> unicode_map_lowercase = {
-{0x00000041, 0x00000061}, {0x00000042, 0x00000062}, {0x00000043, 0x00000063}, {0x00000044, 0x00000064},
-{0x00000045, 0x00000065}, {0x00000046, 0x00000066}, {0x00000047, 0x00000067}, {0x00000048, 0x00000068},
-{0x00000049, 0x00000069}, {0x0000004A, 0x0000006A}, {0x0000004B, 0x0000006B}, {0x0000004C, 0x0000006C},
-{0x0000004D, 0x0000006D}, {0x0000004E, 0x0000006E}, {0x0000004F, 0x0000006F}, {0x00000050, 0x00000070},
-{0x00000051, 0x00000071}, {0x00000052, 0x00000072}, {0x00000053, 0x00000073}, {0x00000054, 0x00000074},
-{0x00000055, 0x00000075}, {0x00000056, 0x00000076}, {0x00000057, 0x00000077}, {0x00000058, 0x00000078},
-{0x00000059, 0x00000079}, {0x0000005A, 0x0000007A}, {0x000000C0, 0x000000E0}, {0x000000C1, 0x000000E1},
-{0x000000C2, 0x000000E2}, {0x000000C3, 0x000000E3}, {0x000000C4, 0x000000E4}, {0x000000C5, 0x000000E5},
-{0x000000C6, 0x000000E6}, {0x000000C7, 0x000000E7}, {0x000000C8, 0x000000E8}, {0x000000C9, 0x000000E9},
-{0x000000CA, 0x000000EA}, {0x000000CB, 0x000000EB}, {0x000000CC, 0x000000EC}, {0x000000CD, 0x000000ED},
-{0x000000CE, 0x000000EE}, {0x000000CF, 0x000000EF}, {0x000000D0, 0x000000F0}, {0x000000D1, 0x000000F1},
-{0x000000D2, 0x000000F2}, {0x000000D3, 0x000000F3}, {0x000000D4, 0x000000F4}, {0x000000D5, 0x000000F5},
-{0x000000D6, 0x000000F6}, {0x000000D8, 0x000000F8}, {0x000000D9, 0x000000F9}, {0x000000DA, 0x000000FA},
-{0x000000DB, 0x000000FB}, {0x000000DC, 0x000000FC}, {0x000000DD, 0x000000FD}, {0x000000DE, 0x000000FE},
-{0x00000100, 0x00000101}, {0x00000102, 0x00000103}, {0x00000104, 0x00000105}, {0x00000106, 0x00000107},
-{0x00000108, 0x00000109}, {0x0000010A, 0x0000010B}, {0x0000010C, 0x0000010D}, {0x0000010E, 0x0000010F},
-{0x00000110, 0x00000111}, {0x00000112, 0x00000113}, {0x00000114, 0x00000115}, {0x00000116, 0x00000117},
-{0x00000118, 0x00000119}, {0x0000011A, 0x0000011B}, {0x0000011C, 0x0000011D}, {0x0000011E, 0x0000011F},
-{0x00000120, 0x00000121}, {0x00000122, 0x00000123}, {0x00000124, 0x00000125}, {0x00000126, 0x00000127},
-{0x00000128, 0x00000129}, {0x0000012A, 0x0000012B}, {0x0000012C, 0x0000012D}, {0x0000012E, 0x0000012F},
-{0x00000130, 0x00000069}, {0x00000132, 0x00000133}, {0x00000134, 0x00000135}, {0x00000136, 0x00000137},
-{0x00000139, 0x0000013A}, {0x0000013B, 0x0000013C}, {0x0000013D, 0x0000013E}, {0x0000013F, 0x00000140},
-{0x00000141, 0x00000142}, {0x00000143, 0x00000144}, {0x00000145, 0x00000146}, {0x00000147, 0x00000148},
-{0x0000014A, 0x0000014B}, {0x0000014C, 0x0000014D}, {0x0000014E, 0x0000014F}, {0x00000150, 0x00000151},
-{0x00000152, 0x00000153}, {0x00000154, 0x00000155}, {0x00000156, 0x00000157}, {0x00000158, 0x00000159},
-{0x0000015A, 0x0000015B}, {0x0000015C, 0x0000015D}, {0x0000015E, 0x0000015F}, {0x00000160, 0x00000161},
-{0x00000162, 0x00000163}, {0x00000164, 0x00000165}, {0x00000166, 0x00000167}, {0x00000168, 0x00000169},
-{0x0000016A, 0x0000016B}, {0x0000016C, 0x0000016D}, {0x0000016E, 0x0000016F}, {0x00000170, 0x00000171},
-{0x00000172, 0x00000173}, {0x00000174, 0x00000175}, {0x00000176, 0x00000177}, {0x00000178, 0x000000FF},
-{0x00000179, 0x0000017A}, {0x0000017B, 0x0000017C}, {0x0000017D, 0x0000017E}, {0x00000181, 0x00000253},
-{0x00000182, 0x00000183}, {0x00000184, 0x00000185}, {0x00000186, 0x00000254}, {0x00000187, 0x00000188},
-{0x00000189, 0x00000256}, {0x0000018A, 0x00000257}, {0x0000018B, 0x0000018C}, {0x0000018E, 0x000001DD},
-{0x0000018F, 0x00000259}, {0x00000190, 0x0000025B}, {0x00000191, 0x00000192}, {0x00000193, 0x00000260},
-{0x00000194, 0x00000263}, {0x00000196, 0x00000269}, {0x00000197, 0x00000268}, {0x00000198, 0x00000199},
-{0x0000019C, 0x0000026F}, {0x0000019D, 0x00000272}, {0x0000019F, 0x00000275}, {0x000001A0, 0x000001A1},
-{0x000001A2, 0x000001A3}, {0x000001A4, 0x000001A5}, {0x000001A6, 0x00000280}, {0x000001A7, 0x000001A8},
-{0x000001A9, 0x00000283}, {0x000001AC, 0x000001AD}, {0x000001AE, 0x00000288}, {0x000001AF, 0x000001B0},
-{0x000001B1, 0x0000028A}, {0x000001B2, 0x0000028B}, {0x000001B3, 0x000001B4}, {0x000001B5, 0x000001B6},
-{0x000001B7, 0x00000292}, {0x000001B8, 0x000001B9}, {0x000001BC, 0x000001BD}, {0x000001C4, 0x000001C6},
-{0x000001C5, 0x000001C6}, {0x000001C7, 0x000001C9}, {0x000001C8, 0x000001C9}, {0x000001CA, 0x000001CC},
-{0x000001CB, 0x000001CC}, {0x000001CD, 0x000001CE}, {0x000001CF, 0x000001D0}, {0x000001D1, 0x000001D2},
-{0x000001D3, 0x000001D4}, {0x000001D5, 0x000001D6}, {0x000001D7, 0x000001D8}, {0x000001D9, 0x000001DA},
-{0x000001DB, 0x000001DC}, {0x000001DE, 0x000001DF}, {0x000001E0, 0x000001E1}, {0x000001E2, 0x000001E3},
-{0x000001E4, 0x000001E5}, {0x000001E6, 0x000001E7}, {0x000001E8, 0x000001E9}, {0x000001EA, 0x000001EB},
-{0x000001EC, 0x000001ED}, {0x000001EE, 0x000001EF}, {0x000001F1, 0x000001F3}, {0x000001F2, 0x000001F3},
-{0x000001F4, 0x000001F5}, {0x000001F6, 0x00000195}, {0x000001F7, 0x000001BF}, {0x000001F8, 0x000001F9},
-{0x000001FA, 0x000001FB}, {0x000001FC, 0x000001FD}, {0x000001FE, 0x000001FF}, {0x00000200, 0x00000201},
-{0x00000202, 0x00000203}, {0x00000204, 0x00000205}, {0x00000206, 0x00000207}, {0x00000208, 0x00000209},
-{0x0000020A, 0x0000020B}, {0x0000020C, 0x0000020D}, {0x0000020E, 0x0000020F}, {0x00000210, 0x00000211},
-{0x00000212, 0x00000213}, {0x00000214, 0x00000215}, {0x00000216, 0x00000217}, {0x00000218, 0x00000219},
-{0x0000021A, 0x0000021B}, {0x0000021C, 0x0000021D}, {0x0000021E, 0x0000021F}, {0x00000220, 0x0000019E},
-{0x00000222, 0x00000223}, {0x00000224, 0x00000225}, {0x00000226, 0x00000227}, {0x00000228, 0x00000229},
-{0x0000022A, 0x0000022B}, {0x0000022C, 0x0000022D}, {0x0000022E, 0x0000022F}, {0x00000230, 0x00000231},
-{0x00000232, 0x00000233}, {0x0000023A, 0x00002C65}, {0x0000023B, 0x0000023C}, {0x0000023D, 0x0000019A},
-{0x0000023E, 0x00002C66}, {0x00000241, 0x00000242}, {0x00000243, 0x00000180}, {0x00000244, 0x00000289},
-{0x00000245, 0x0000028C}, {0x00000246, 0x00000247}, {0x00000248, 0x00000249}, {0x0000024A, 0x0000024B},
-{0x0000024C, 0x0000024D}, {0x0000024E, 0x0000024F}, {0x00000370, 0x00000371}, {0x00000372, 0x00000373},
-{0x00000376, 0x00000377}, {0x0000037F, 0x000003F3}, {0x00000386, 0x000003AC}, {0x00000388, 0x000003AD},
-{0x00000389, 0x000003AE}, {0x0000038A, 0x000003AF}, {0x0000038C, 0x000003CC}, {0x0000038E, 0x000003CD},
-{0x0000038F, 0x000003CE}, {0x00000391, 0x000003B1}, {0x00000392, 0x000003B2}, {0x00000393, 0x000003B3},
-{0x00000394, 0x000003B4}, {0x00000395, 0x000003B5}, {0x00000396, 0x000003B6}, {0x00000397, 0x000003B7},
-{0x00000398, 0x000003B8}, {0x00000399, 0x000003B9}, {0x0000039A, 0x000003BA}, {0x0000039B, 0x000003BB},
-{0x0000039C, 0x000003BC}, {0x0000039D, 0x000003BD}, {0x0000039E, 0x000003BE}, {0x0000039F, 0x000003BF},
-{0x000003A0, 0x000003C0}, {0x000003A1, 0x000003C1}, {0x000003A3, 0x000003C3}, {0x000003A4, 0x000003C4},
-{0x000003A5, 0x000003C5}, {0x000003A6, 0x000003C6}, {0x000003A7, 0x000003C7}, {0x000003A8, 0x000003C8},
-{0x000003A9, 0x000003C9}, {0x000003AA, 0x000003CA}, {0x000003AB, 0x000003CB}, {0x000003CF, 0x000003D7},
-{0x000003D8, 0x000003D9}, {0x000003DA, 0x000003DB}, {0x000003DC, 0x000003DD}, {0x000003DE, 0x000003DF},
-{0x000003E0, 0x000003E1}, {0x000003E2, 0x000003E3}, {0x000003E4, 0x000003E5}, {0x000003E6, 0x000003E7},
-{0x000003E8, 0x000003E9}, {0x000003EA, 0x000003EB}, {0x000003EC, 0x000003ED}, {0x000003EE, 0x000003EF},
-{0x000003F4, 0x000003B8}, {0x000003F7, 0x000003F8}, {0x000003F9, 0x000003F2}, {0x000003FA, 0x000003FB},
-{0x000003FD, 0x0000037B}, {0x000003FE, 0x0000037C}, {0x000003FF, 0x0000037D}, {0x00000400, 0x00000450},
-{0x00000401, 0x00000451}, {0x00000402, 0x00000452}, {0x00000403, 0x00000453}, {0x00000404, 0x00000454},
-{0x00000405, 0x00000455}, {0x00000406, 0x00000456}, {0x00000407, 0x00000457}, {0x00000408, 0x00000458},
-{0x00000409, 0x00000459}, {0x0000040A, 0x0000045A}, {0x0000040B, 0x0000045B}, {0x0000040C, 0x0000045C},
-{0x0000040D, 0x0000045D}, {0x0000040E, 0x0000045E}, {0x0000040F, 0x0000045F}, {0x00000410, 0x00000430},
-{0x00000411, 0x00000431}, {0x00000412, 0x00000432}, {0x00000413, 0x00000433}, {0x00000414, 0x00000434},
-{0x00000415, 0x00000435}, {0x00000416, 0x00000436}, {0x00000417, 0x00000437}, {0x00000418, 0x00000438},
-{0x00000419, 0x00000439}, {0x0000041A, 0x0000043A}, {0x0000041B, 0x0000043B}, {0x0000041C, 0x0000043C},
-{0x0000041D, 0x0000043D}, {0x0000041E, 0x0000043E}, {0x0000041F, 0x0000043F}, {0x00000420, 0x00000440},
-{0x00000421, 0x00000441}, {0x00000422, 0x00000442}, {0x00000423, 0x00000443}, {0x00000424, 0x00000444},
-{0x00000425, 0x00000445}, {0x00000426, 0x00000446}, {0x00000427, 0x00000447}, {0x00000428, 0x00000448},
-{0x00000429, 0x00000449}, {0x0000042A, 0x0000044A}, {0x0000042B, 0x0000044B}, {0x0000042C, 0x0000044C},
-{0x0000042D, 0x0000044D}, {0x0000042E, 0x0000044E}, {0x0000042F, 0x0000044F}, {0x00000460, 0x00000461},
-{0x00000462, 0x00000463}, {0x00000464, 0x00000465}, {0x00000466, 0x00000467}, {0x00000468, 0x00000469},
-{0x0000046A, 0x0000046B}, {0x0000046C, 0x0000046D}, {0x0000046E, 0x0000046F}, {0x00000470, 0x00000471},
-{0x00000472, 0x00000473}, {0x00000474, 0x00000475}, {0x00000476, 0x00000477}, {0x00000478, 0x00000479},
-{0x0000047A, 0x0000047B}, {0x0000047C, 0x0000047D}, {0x0000047E, 0x0000047F}, {0x00000480, 0x00000481},
-{0x0000048A, 0x0000048B}, {0x0000048C, 0x0000048D}, {0x0000048E, 0x0000048F}, {0x00000490, 0x00000491},
-{0x00000492, 0x00000493}, {0x00000494, 0x00000495}, {0x00000496, 0x00000497}, {0x00000498, 0x00000499},
-{0x0000049A, 0x0000049B}, {0x0000049C, 0x0000049D}, {0x0000049E, 0x0000049F}, {0x000004A0, 0x000004A1},
-{0x000004A2, 0x000004A3}, {0x000004A4, 0x000004A5}, {0x000004A6, 0x000004A7}, {0x000004A8, 0x000004A9},
-{0x000004AA, 0x000004AB}, {0x000004AC, 0x000004AD}, {0x000004AE, 0x000004AF}, {0x000004B0, 0x000004B1},
-{0x000004B2, 0x000004B3}, {0x000004B4, 0x000004B5}, {0x000004B6, 0x000004B7}, {0x000004B8, 0x000004B9},
-{0x000004BA, 0x000004BB}, {0x000004BC, 0x000004BD}, {0x000004BE, 0x000004BF}, {0x000004C0, 0x000004CF},
-{0x000004C1, 0x000004C2}, {0x000004C3, 0x000004C4}, {0x000004C5, 0x000004C6}, {0x000004C7, 0x000004C8},
-{0x000004C9, 0x000004CA}, {0x000004CB, 0x000004CC}, {0x000004CD, 0x000004CE}, {0x000004D0, 0x000004D1},
-{0x000004D2, 0x000004D3}, {0x000004D4, 0x000004D5}, {0x000004D6, 0x000004D7}, {0x000004D8, 0x000004D9},
-{0x000004DA, 0x000004DB}, {0x000004DC, 0x000004DD}, {0x000004DE, 0x000004DF}, {0x000004E0, 0x000004E1},
-{0x000004E2, 0x000004E3}, {0x000004E4, 0x000004E5}, {0x000004E6, 0x000004E7}, {0x000004E8, 0x000004E9},
-{0x000004EA, 0x000004EB}, {0x000004EC, 0x000004ED}, {0x000004EE, 0x000004EF}, {0x000004F0, 0x000004F1},
-{0x000004F2, 0x000004F3}, {0x000004F4, 0x000004F5}, {0x000004F6, 0x000004F7}, {0x000004F8, 0x000004F9},
-{0x000004FA, 0x000004FB}, {0x000004FC, 0x000004FD}, {0x000004FE, 0x000004FF}, {0x00000500, 0x00000501},
-{0x00000502, 0x00000503}, {0x00000504, 0x00000505}, {0x00000506, 0x00000507}, {0x00000508, 0x00000509},
-{0x0000050A, 0x0000050B}, {0x0000050C, 0x0000050D}, {0x0000050E, 0x0000050F}, {0x00000510, 0x00000511},
-{0x00000512, 0x00000513}, {0x00000514, 0x00000515}, {0x00000516, 0x00000517}, {0x00000518, 0x00000519},
-{0x0000051A, 0x0000051B}, {0x0000051C, 0x0000051D}, {0x0000051E, 0x0000051F}, {0x00000520, 0x00000521},
-{0x00000522, 0x00000523}, {0x00000524, 0x00000525}, {0x00000526, 0x00000527}, {0x00000528, 0x00000529},
-{0x0000052A, 0x0000052B}, {0x0000052C, 0x0000052D}, {0x0000052E, 0x0000052F}, {0x00000531, 0x00000561},
-{0x00000532, 0x00000562}, {0x00000533, 0x00000563}, {0x00000534, 0x00000564}, {0x00000535, 0x00000565},
-{0x00000536, 0x00000566}, {0x00000537, 0x00000567}, {0x00000538, 0x00000568}, {0x00000539, 0x00000569},
-{0x0000053A, 0x0000056A}, {0x0000053B, 0x0000056B}, {0x0000053C, 0x0000056C}, {0x0000053D, 0x0000056D},
-{0x0000053E, 0x0000056E}, {0x0000053F, 0x0000056F}, {0x00000540, 0x00000570}, {0x00000541, 0x00000571},
-{0x00000542, 0x00000572}, {0x00000543, 0x00000573}, {0x00000544, 0x00000574}, {0x00000545, 0x00000575},
-{0x00000546, 0x00000576}, {0x00000547, 0x00000577}, {0x00000548, 0x00000578}, {0x00000549, 0x00000579},
-{0x0000054A, 0x0000057A}, {0x0000054B, 0x0000057B}, {0x0000054C, 0x0000057C}, {0x0000054D, 0x0000057D},
-{0x0000054E, 0x0000057E}, {0x0000054F, 0x0000057F}, {0x00000550, 0x00000580}, {0x00000551, 0x00000581},
-{0x00000552, 0x00000582}, {0x00000553, 0x00000583}, {0x00000554, 0x00000584}, {0x00000555, 0x00000585},
-{0x00000556, 0x00000586}, {0x000010A0, 0x00002D00}, {0x000010A1, 0x00002D01}, {0x000010A2, 0x00002D02},
-{0x000010A3, 0x00002D03}, {0x000010A4, 0x00002D04}, {0x000010A5, 0x00002D05}, {0x000010A6, 0x00002D06},
-{0x000010A7, 0x00002D07}, {0x000010A8, 0x00002D08}, {0x000010A9, 0x00002D09}, {0x000010AA, 0x00002D0A},
-{0x000010AB, 0x00002D0B}, {0x000010AC, 0x00002D0C}, {0x000010AD, 0x00002D0D}, {0x000010AE, 0x00002D0E},
-{0x000010AF, 0x00002D0F}, {0x000010B0, 0x00002D10}, {0x000010B1, 0x00002D11}, {0x000010B2, 0x00002D12},
-{0x000010B3, 0x00002D13}, {0x000010B4, 0x00002D14}, {0x000010B5, 0x00002D15}, {0x000010B6, 0x00002D16},
-{0x000010B7, 0x00002D17}, {0x000010B8, 0x00002D18}, {0x000010B9, 0x00002D19}, {0x000010BA, 0x00002D1A},
-{0x000010BB, 0x00002D1B}, {0x000010BC, 0x00002D1C}, {0x000010BD, 0x00002D1D}, {0x000010BE, 0x00002D1E},
-{0x000010BF, 0x00002D1F}, {0x000010C0, 0x00002D20}, {0x000010C1, 0x00002D21}, {0x000010C2, 0x00002D22},
-{0x000010C3, 0x00002D23}, {0x000010C4, 0x00002D24}, {0x000010C5, 0x00002D25}, {0x000010C7, 0x00002D27},
-{0x000010CD, 0x00002D2D}, {0x000013A0, 0x0000AB70}, {0x000013A1, 0x0000AB71}, {0x000013A2, 0x0000AB72},
-{0x000013A3, 0x0000AB73}, {0x000013A4, 0x0000AB74}, {0x000013A5, 0x0000AB75}, {0x000013A6, 0x0000AB76},
-{0x000013A7, 0x0000AB77}, {0x000013A8, 0x0000AB78}, {0x000013A9, 0x0000AB79}, {0x000013AA, 0x0000AB7A},
-{0x000013AB, 0x0000AB7B}, {0x000013AC, 0x0000AB7C}, {0x000013AD, 0x0000AB7D}, {0x000013AE, 0x0000AB7E},
-{0x000013AF, 0x0000AB7F}, {0x000013B0, 0x0000AB80}, {0x000013B1, 0x0000AB81}, {0x000013B2, 0x0000AB82},
-{0x000013B3, 0x0000AB83}, {0x000013B4, 0x0000AB84}, {0x000013B5, 0x0000AB85}, {0x000013B6, 0x0000AB86},
-{0x000013B7, 0x0000AB87}, {0x000013B8, 0x0000AB88}, {0x000013B9, 0x0000AB89}, {0x000013BA, 0x0000AB8A},
-{0x000013BB, 0x0000AB8B}, {0x000013BC, 0x0000AB8C}, {0x000013BD, 0x0000AB8D}, {0x000013BE, 0x0000AB8E},
-{0x000013BF, 0x0000AB8F}, {0x000013C0, 0x0000AB90}, {0x000013C1, 0x0000AB91}, {0x000013C2, 0x0000AB92},
-{0x000013C3, 0x0000AB93}, {0x000013C4, 0x0000AB94}, {0x000013C5, 0x0000AB95}, {0x000013C6, 0x0000AB96},
-{0x000013C7, 0x0000AB97}, {0x000013C8, 0x0000AB98}, {0x000013C9, 0x0000AB99}, {0x000013CA, 0x0000AB9A},
-{0x000013CB, 0x0000AB9B}, {0x000013CC, 0x0000AB9C}, {0x000013CD, 0x0000AB9D}, {0x000013CE, 0x0000AB9E},
-{0x000013CF, 0x0000AB9F}, {0x000013D0, 0x0000ABA0}, {0x000013D1, 0x0000ABA1}, {0x000013D2, 0x0000ABA2},
-{0x000013D3, 0x0000ABA3}, {0x000013D4, 0x0000ABA4}, {0x000013D5, 0x0000ABA5}, {0x000013D6, 0x0000ABA6},
-{0x000013D7, 0x0000ABA7}, {0x000013D8, 0x0000ABA8}, {0x000013D9, 0x0000ABA9}, {0x000013DA, 0x0000ABAA},
-{0x000013DB, 0x0000ABAB}, {0x000013DC, 0x0000ABAC}, {0x000013DD, 0x0000ABAD}, {0x000013DE, 0x0000ABAE},
-{0x000013DF, 0x0000ABAF}, {0x000013E0, 0x0000ABB0}, {0x000013E1, 0x0000ABB1}, {0x000013E2, 0x0000ABB2},
-{0x000013E3, 0x0000ABB3}, {0x000013E4, 0x0000ABB4}, {0x000013E5, 0x0000ABB5}, {0x000013E6, 0x0000ABB6},
-{0x000013E7, 0x0000ABB7}, {0x000013E8, 0x0000ABB8}, {0x000013E9, 0x0000ABB9}, {0x000013EA, 0x0000ABBA},
-{0x000013EB, 0x0000ABBB}, {0x000013EC, 0x0000ABBC}, {0x000013ED, 0x0000ABBD}, {0x000013EE, 0x0000ABBE},
-{0x000013EF, 0x0000ABBF}, {0x000013F0, 0x000013F8}, {0x000013F1, 0x000013F9}, {0x000013F2, 0x000013FA},
-{0x000013F3, 0x000013FB}, {0x000013F4, 0x000013FC}, {0x000013F5, 0x000013FD}, {0x00001C90, 0x000010D0},
-{0x00001C91, 0x000010D1}, {0x00001C92, 0x000010D2}, {0x00001C93, 0x000010D3}, {0x00001C94, 0x000010D4},
-{0x00001C95, 0x000010D5}, {0x00001C96, 0x000010D6}, {0x00001C97, 0x000010D7}, {0x00001C98, 0x000010D8},
-{0x00001C99, 0x000010D9}, {0x00001C9A, 0x000010DA}, {0x00001C9B, 0x000010DB}, {0x00001C9C, 0x000010DC},
-{0x00001C9D, 0x000010DD}, {0x00001C9E, 0x000010DE}, {0x00001C9F, 0x000010DF}, {0x00001CA0, 0x000010E0},
-{0x00001CA1, 0x000010E1}, {0x00001CA2, 0x000010E2}, {0x00001CA3, 0x000010E3}, {0x00001CA4, 0x000010E4},
-{0x00001CA5, 0x000010E5}, {0x00001CA6, 0x000010E6}, {0x00001CA7, 0x000010E7}, {0x00001CA8, 0x000010E8},
-{0x00001CA9, 0x000010E9}, {0x00001CAA, 0x000010EA}, {0x00001CAB, 0x000010EB}, {0x00001CAC, 0x000010EC},
-{0x00001CAD, 0x000010ED}, {0x00001CAE, 0x000010EE}, {0x00001CAF, 0x000010EF}, {0x00001CB0, 0x000010F0},
-{0x00001CB1, 0x000010F1}, {0x00001CB2, 0x000010F2}, {0x00001CB3, 0x000010F3}, {0x00001CB4, 0x000010F4},
-{0x00001CB5, 0x000010F5}, {0x00001CB6, 0x000010F6}, {0x00001CB7, 0x000010F7}, {0x00001CB8, 0x000010F8},
-{0x00001CB9, 0x000010F9}, {0x00001CBA, 0x000010FA}, {0x00001CBD, 0x000010FD}, {0x00001CBE, 0x000010FE},
-{0x00001CBF, 0x000010FF}, {0x00001E00, 0x00001E01}, {0x00001E02, 0x00001E03}, {0x00001E04, 0x00001E05},
-{0x00001E06, 0x00001E07}, {0x00001E08, 0x00001E09}, {0x00001E0A, 0x00001E0B}, {0x00001E0C, 0x00001E0D},
-{0x00001E0E, 0x00001E0F}, {0x00001E10, 0x00001E11}, {0x00001E12, 0x00001E13}, {0x00001E14, 0x00001E15},
-{0x00001E16, 0x00001E17}, {0x00001E18, 0x00001E19}, {0x00001E1A, 0x00001E1B}, {0x00001E1C, 0x00001E1D},
-{0x00001E1E, 0x00001E1F}, {0x00001E20, 0x00001E21}, {0x00001E22, 0x00001E23}, {0x00001E24, 0x00001E25},
-{0x00001E26, 0x00001E27}, {0x00001E28, 0x00001E29}, {0x00001E2A, 0x00001E2B}, {0x00001E2C, 0x00001E2D},
-{0x00001E2E, 0x00001E2F}, {0x00001E30, 0x00001E31}, {0x00001E32, 0x00001E33}, {0x00001E34, 0x00001E35},
-{0x00001E36, 0x00001E37}, {0x00001E38, 0x00001E39}, {0x00001E3A, 0x00001E3B}, {0x00001E3C, 0x00001E3D},
-{0x00001E3E, 0x00001E3F}, {0x00001E40, 0x00001E41}, {0x00001E42, 0x00001E43}, {0x00001E44, 0x00001E45},
-{0x00001E46, 0x00001E47}, {0x00001E48, 0x00001E49}, {0x00001E4A, 0x00001E4B}, {0x00001E4C, 0x00001E4D},
-{0x00001E4E, 0x00001E4F}, {0x00001E50, 0x00001E51}, {0x00001E52, 0x00001E53}, {0x00001E54, 0x00001E55},
-{0x00001E56, 0x00001E57}, {0x00001E58, 0x00001E59}, {0x00001E5A, 0x00001E5B}, {0x00001E5C, 0x00001E5D},
-{0x00001E5E, 0x00001E5F}, {0x00001E60, 0x00001E61}, {0x00001E62, 0x00001E63}, {0x00001E64, 0x00001E65},
-{0x00001E66, 0x00001E67}, {0x00001E68, 0x00001E69}, {0x00001E6A, 0x00001E6B}, {0x00001E6C, 0x00001E6D},
-{0x00001E6E, 0x00001E6F}, {0x00001E70, 0x00001E71}, {0x00001E72, 0x00001E73}, {0x00001E74, 0x00001E75},
-{0x00001E76, 0x00001E77}, {0x00001E78, 0x00001E79}, {0x00001E7A, 0x00001E7B}, {0x00001E7C, 0x00001E7D},
-{0x00001E7E, 0x00001E7F}, {0x00001E80, 0x00001E81}, {0x00001E82, 0x00001E83}, {0x00001E84, 0x00001E85},
-{0x00001E86, 0x00001E87}, {0x00001E88, 0x00001E89}, {0x00001E8A, 0x00001E8B}, {0x00001E8C, 0x00001E8D},
-{0x00001E8E, 0x00001E8F}, {0x00001E90, 0x00001E91}, {0x00001E92, 0x00001E93}, {0x00001E94, 0x00001E95},
-{0x00001E9E, 0x000000DF}, {0x00001EA0, 0x00001EA1}, {0x00001EA2, 0x00001EA3}, {0x00001EA4, 0x00001EA5},
-{0x00001EA6, 0x00001EA7}, {0x00001EA8, 0x00001EA9}, {0x00001EAA, 0x00001EAB}, {0x00001EAC, 0x00001EAD},
-{0x00001EAE, 0x00001EAF}, {0x00001EB0, 0x00001EB1}, {0x00001EB2, 0x00001EB3}, {0x00001EB4, 0x00001EB5},
-{0x00001EB6, 0x00001EB7}, {0x00001EB8, 0x00001EB9}, {0x00001EBA, 0x00001EBB}, {0x00001EBC, 0x00001EBD},
-{0x00001EBE, 0x00001EBF}, {0x00001EC0, 0x00001EC1}, {0x00001EC2, 0x00001EC3}, {0x00001EC4, 0x00001EC5},
-{0x00001EC6, 0x00001EC7}, {0x00001EC8, 0x00001EC9}, {0x00001ECA, 0x00001ECB}, {0x00001ECC, 0x00001ECD},
-{0x00001ECE, 0x00001ECF}, {0x00001ED0, 0x00001ED1}, {0x00001ED2, 0x00001ED3}, {0x00001ED4, 0x00001ED5},
-{0x00001ED6, 0x00001ED7}, {0x00001ED8, 0x00001ED9}, {0x00001EDA, 0x00001EDB}, {0x00001EDC, 0x00001EDD},
-{0x00001EDE, 0x00001EDF}, {0x00001EE0, 0x00001EE1}, {0x00001EE2, 0x00001EE3}, {0x00001EE4, 0x00001EE5},
-{0x00001EE6, 0x00001EE7}, {0x00001EE8, 0x00001EE9}, {0x00001EEA, 0x00001EEB}, {0x00001EEC, 0x00001EED},
-{0x00001EEE, 0x00001EEF}, {0x00001EF0, 0x00001EF1}, {0x00001EF2, 0x00001EF3}, {0x00001EF4, 0x00001EF5},
-{0x00001EF6, 0x00001EF7}, {0x00001EF8, 0x00001EF9}, {0x00001EFA, 0x00001EFB}, {0x00001EFC, 0x00001EFD},
-{0x00001EFE, 0x00001EFF}, {0x00001F08, 0x00001F00}, {0x00001F09, 0x00001F01}, {0x00001F0A, 0x00001F02},
-{0x00001F0B, 0x00001F03}, {0x00001F0C, 0x00001F04}, {0x00001F0D, 0x00001F05}, {0x00001F0E, 0x00001F06},
-{0x00001F0F, 0x00001F07}, {0x00001F18, 0x00001F10}, {0x00001F19, 0x00001F11}, {0x00001F1A, 0x00001F12},
-{0x00001F1B, 0x00001F13}, {0x00001F1C, 0x00001F14}, {0x00001F1D, 0x00001F15}, {0x00001F28, 0x00001F20},
-{0x00001F29, 0x00001F21}, {0x00001F2A, 0x00001F22}, {0x00001F2B, 0x00001F23}, {0x00001F2C, 0x00001F24},
-{0x00001F2D, 0x00001F25}, {0x00001F2E, 0x00001F26}, {0x00001F2F, 0x00001F27}, {0x00001F38, 0x00001F30},
-{0x00001F39, 0x00001F31}, {0x00001F3A, 0x00001F32}, {0x00001F3B, 0x00001F33}, {0x00001F3C, 0x00001F34},
-{0x00001F3D, 0x00001F35}, {0x00001F3E, 0x00001F36}, {0x00001F3F, 0x00001F37}, {0x00001F48, 0x00001F40},
-{0x00001F49, 0x00001F41}, {0x00001F4A, 0x00001F42}, {0x00001F4B, 0x00001F43}, {0x00001F4C, 0x00001F44},
-{0x00001F4D, 0x00001F45}, {0x00001F59, 0x00001F51}, {0x00001F5B, 0x00001F53}, {0x00001F5D, 0x00001F55},
-{0x00001F5F, 0x00001F57}, {0x00001F68, 0x00001F60}, {0x00001F69, 0x00001F61}, {0x00001F6A, 0x00001F62},
-{0x00001F6B, 0x00001F63}, {0x00001F6C, 0x00001F64}, {0x00001F6D, 0x00001F65}, {0x00001F6E, 0x00001F66},
-{0x00001F6F, 0x00001F67}, {0x00001F88, 0x00001F80}, {0x00001F89, 0x00001F81}, {0x00001F8A, 0x00001F82},
-{0x00001F8B, 0x00001F83}, {0x00001F8C, 0x00001F84}, {0x00001F8D, 0x00001F85}, {0x00001F8E, 0x00001F86},
-{0x00001F8F, 0x00001F87}, {0x00001F98, 0x00001F90}, {0x00001F99, 0x00001F91}, {0x00001F9A, 0x00001F92},
-{0x00001F9B, 0x00001F93}, {0x00001F9C, 0x00001F94}, {0x00001F9D, 0x00001F95}, {0x00001F9E, 0x00001F96},
-{0x00001F9F, 0x00001F97}, {0x00001FA8, 0x00001FA0}, {0x00001FA9, 0x00001FA1}, {0x00001FAA, 0x00001FA2},
-{0x00001FAB, 0x00001FA3}, {0x00001FAC, 0x00001FA4}, {0x00001FAD, 0x00001FA5}, {0x00001FAE, 0x00001FA6},
-{0x00001FAF, 0x00001FA7}, {0x00001FB8, 0x00001FB0}, {0x00001FB9, 0x00001FB1}, {0x00001FBA, 0x00001F70},
-{0x00001FBB, 0x00001F71}, {0x00001FBC, 0x00001FB3}, {0x00001FC8, 0x00001F72}, {0x00001FC9, 0x00001F73},
-{0x00001FCA, 0x00001F74}, {0x00001FCB, 0x00001F75}, {0x00001FCC, 0x00001FC3}, {0x00001FD8, 0x00001FD0},
-{0x00001FD9, 0x00001FD1}, {0x00001FDA, 0x00001F76}, {0x00001FDB, 0x00001F77}, {0x00001FE8, 0x00001FE0},
-{0x00001FE9, 0x00001FE1}, {0x00001FEA, 0x00001F7A}, {0x00001FEB, 0x00001F7B}, {0x00001FEC, 0x00001FE5},
-{0x00001FF8, 0x00001F78}, {0x00001FF9, 0x00001F79}, {0x00001FFA, 0x00001F7C}, {0x00001FFB, 0x00001F7D},
-{0x00001FFC, 0x00001FF3}, {0x00002126, 0x000003C9}, {0x0000212A, 0x0000006B}, {0x0000212B, 0x000000E5},
-{0x00002132, 0x0000214E}, {0x00002160, 0x00002170}, {0x00002161, 0x00002171}, {0x00002162, 0x00002172},
-{0x00002163, 0x00002173}, {0x00002164, 0x00002174}, {0x00002165, 0x00002175}, {0x00002166, 0x00002176},
-{0x00002167, 0x00002177}, {0x00002168, 0x00002178}, {0x00002169, 0x00002179}, {0x0000216A, 0x0000217A},
-{0x0000216B, 0x0000217B}, {0x0000216C, 0x0000217C}, {0x0000216D, 0x0000217D}, {0x0000216E, 0x0000217E},
-{0x0000216F, 0x0000217F}, {0x00002183, 0x00002184}, {0x000024B6, 0x000024D0}, {0x000024B7, 0x000024D1},
-{0x000024B8, 0x000024D2}, {0x000024B9, 0x000024D3}, {0x000024BA, 0x000024D4}, {0x000024BB, 0x000024D5},
-{0x000024BC, 0x000024D6}, {0x000024BD, 0x000024D7}, {0x000024BE, 0x000024D8}, {0x000024BF, 0x000024D9},
-{0x000024C0, 0x000024DA}, {0x000024C1, 0x000024DB}, {0x000024C2, 0x000024DC}, {0x000024C3, 0x000024DD},
-{0x000024C4, 0x000024DE}, {0x000024C5, 0x000024DF}, {0x000024C6, 0x000024E0}, {0x000024C7, 0x000024E1},
-{0x000024C8, 0x000024E2}, {0x000024C9, 0x000024E3}, {0x000024CA, 0x000024E4}, {0x000024CB, 0x000024E5},
-{0x000024CC, 0x000024E6}, {0x000024CD, 0x000024E7}, {0x000024CE, 0x000024E8}, {0x000024CF, 0x000024E9},
-{0x00002C00, 0x00002C30}, {0x00002C01, 0x00002C31}, {0x00002C02, 0x00002C32}, {0x00002C03, 0x00002C33},
-{0x00002C04, 0x00002C34}, {0x00002C05, 0x00002C35}, {0x00002C06, 0x00002C36}, {0x00002C07, 0x00002C37},
-{0x00002C08, 0x00002C38}, {0x00002C09, 0x00002C39}, {0x00002C0A, 0x00002C3A}, {0x00002C0B, 0x00002C3B},
-{0x00002C0C, 0x00002C3C}, {0x00002C0D, 0x00002C3D}, {0x00002C0E, 0x00002C3E}, {0x00002C0F, 0x00002C3F},
-{0x00002C10, 0x00002C40}, {0x00002C11, 0x00002C41}, {0x00002C12, 0x00002C42}, {0x00002C13, 0x00002C43},
-{0x00002C14, 0x00002C44}, {0x00002C15, 0x00002C45}, {0x00002C16, 0x00002C46}, {0x00002C17, 0x00002C47},
-{0x00002C18, 0x00002C48}, {0x00002C19, 0x00002C49}, {0x00002C1A, 0x00002C4A}, {0x00002C1B, 0x00002C4B},
-{0x00002C1C, 0x00002C4C}, {0x00002C1D, 0x00002C4D}, {0x00002C1E, 0x00002C4E}, {0x00002C1F, 0x00002C4F},
-{0x00002C20, 0x00002C50}, {0x00002C21, 0x00002C51}, {0x00002C22, 0x00002C52}, {0x00002C23, 0x00002C53},
-{0x00002C24, 0x00002C54}, {0x00002C25, 0x00002C55}, {0x00002C26, 0x00002C56}, {0x00002C27, 0x00002C57},
-{0x00002C28, 0x00002C58}, {0x00002C29, 0x00002C59}, {0x00002C2A, 0x00002C5A}, {0x00002C2B, 0x00002C5B},
-{0x00002C2C, 0x00002C5C}, {0x00002C2D, 0x00002C5D}, {0x00002C2E, 0x00002C5E}, {0x00002C60, 0x00002C61},
-{0x00002C62, 0x0000026B}, {0x00002C63, 0x00001D7D}, {0x00002C64, 0x0000027D}, {0x00002C67, 0x00002C68},
-{0x00002C69, 0x00002C6A}, {0x00002C6B, 0x00002C6C}, {0x00002C6D, 0x00000251}, {0x00002C6E, 0x00000271},
-{0x00002C6F, 0x00000250}, {0x00002C70, 0x00000252}, {0x00002C72, 0x00002C73}, {0x00002C75, 0x00002C76},
-{0x00002C7E, 0x0000023F}, {0x00002C7F, 0x00000240}, {0x00002C80, 0x00002C81}, {0x00002C82, 0x00002C83},
-{0x00002C84, 0x00002C85}, {0x00002C86, 0x00002C87}, {0x00002C88, 0x00002C89}, {0x00002C8A, 0x00002C8B},
-{0x00002C8C, 0x00002C8D}, {0x00002C8E, 0x00002C8F}, {0x00002C90, 0x00002C91}, {0x00002C92, 0x00002C93},
-{0x00002C94, 0x00002C95}, {0x00002C96, 0x00002C97}, {0x00002C98, 0x00002C99}, {0x00002C9A, 0x00002C9B},
-{0x00002C9C, 0x00002C9D}, {0x00002C9E, 0x00002C9F}, {0x00002CA0, 0x00002CA1}, {0x00002CA2, 0x00002CA3},
-{0x00002CA4, 0x00002CA5}, {0x00002CA6, 0x00002CA7}, {0x00002CA8, 0x00002CA9}, {0x00002CAA, 0x00002CAB},
-{0x00002CAC, 0x00002CAD}, {0x00002CAE, 0x00002CAF}, {0x00002CB0, 0x00002CB1}, {0x00002CB2, 0x00002CB3},
-{0x00002CB4, 0x00002CB5}, {0x00002CB6, 0x00002CB7}, {0x00002CB8, 0x00002CB9}, {0x00002CBA, 0x00002CBB},
-{0x00002CBC, 0x00002CBD}, {0x00002CBE, 0x00002CBF}, {0x00002CC0, 0x00002CC1}, {0x00002CC2, 0x00002CC3},
-{0x00002CC4, 0x00002CC5}, {0x00002CC6, 0x00002CC7}, {0x00002CC8, 0x00002CC9}, {0x00002CCA, 0x00002CCB},
-{0x00002CCC, 0x00002CCD}, {0x00002CCE, 0x00002CCF}, {0x00002CD0, 0x00002CD1}, {0x00002CD2, 0x00002CD3},
-{0x00002CD4, 0x00002CD5}, {0x00002CD6, 0x00002CD7}, {0x00002CD8, 0x00002CD9}, {0x00002CDA, 0x00002CDB},
-{0x00002CDC, 0x00002CDD}, {0x00002CDE, 0x00002CDF}, {0x00002CE0, 0x00002CE1}, {0x00002CE2, 0x00002CE3},
-{0x00002CEB, 0x00002CEC}, {0x00002CED, 0x00002CEE}, {0x00002CF2, 0x00002CF3}, {0x0000A640, 0x0000A641},
-{0x0000A642, 0x0000A643}, {0x0000A644, 0x0000A645}, {0x0000A646, 0x0000A647}, {0x0000A648, 0x0000A649},
-{0x0000A64A, 0x0000A64B}, {0x0000A64C, 0x0000A64D}, {0x0000A64E, 0x0000A64F}, {0x0000A650, 0x0000A651},
-{0x0000A652, 0x0000A653}, {0x0000A654, 0x0000A655}, {0x0000A656, 0x0000A657}, {0x0000A658, 0x0000A659},
-{0x0000A65A, 0x0000A65B}, {0x0000A65C, 0x0000A65D}, {0x0000A65E, 0x0000A65F}, {0x0000A660, 0x0000A661},
-{0x0000A662, 0x0000A663}, {0x0000A664, 0x0000A665}, {0x0000A666, 0x0000A667}, {0x0000A668, 0x0000A669},
-{0x0000A66A, 0x0000A66B}, {0x0000A66C, 0x0000A66D}, {0x0000A680, 0x0000A681}, {0x0000A682, 0x0000A683},
-{0x0000A684, 0x0000A685}, {0x0000A686, 0x0000A687}, {0x0000A688, 0x0000A689}, {0x0000A68A, 0x0000A68B},
-{0x0000A68C, 0x0000A68D}, {0x0000A68E, 0x0000A68F}, {0x0000A690, 0x0000A691}, {0x0000A692, 0x0000A693},
-{0x0000A694, 0x0000A695}, {0x0000A696, 0x0000A697}, {0x0000A698, 0x0000A699}, {0x0000A69A, 0x0000A69B},
-{0x0000A722, 0x0000A723}, {0x0000A724, 0x0000A725}, {0x0000A726, 0x0000A727}, {0x0000A728, 0x0000A729},
-{0x0000A72A, 0x0000A72B}, {0x0000A72C, 0x0000A72D}, {0x0000A72E, 0x0000A72F}, {0x0000A732, 0x0000A733},
-{0x0000A734, 0x0000A735}, {0x0000A736, 0x0000A737}, {0x0000A738, 0x0000A739}, {0x0000A73A, 0x0000A73B},
-{0x0000A73C, 0x0000A73D}, {0x0000A73E, 0x0000A73F}, {0x0000A740, 0x0000A741}, {0x0000A742, 0x0000A743},
-{0x0000A744, 0x0000A745}, {0x0000A746, 0x0000A747}, {0x0000A748, 0x0000A749}, {0x0000A74A, 0x0000A74B},
-{0x0000A74C, 0x0000A74D}, {0x0000A74E, 0x0000A74F}, {0x0000A750, 0x0000A751}, {0x0000A752, 0x0000A753},
-{0x0000A754, 0x0000A755}, {0x0000A756, 0x0000A757}, {0x0000A758, 0x0000A759}, {0x0000A75A, 0x0000A75B},
-{0x0000A75C, 0x0000A75D}, {0x0000A75E, 0x0000A75F}, {0x0000A760, 0x0000A761}, {0x0000A762, 0x0000A763},
-{0x0000A764, 0x0000A765}, {0x0000A766, 0x0000A767}, {0x0000A768, 0x0000A769}, {0x0000A76A, 0x0000A76B},
-{0x0000A76C, 0x0000A76D}, {0x0000A76E, 0x0000A76F}, {0x0000A779, 0x0000A77A}, {0x0000A77B, 0x0000A77C},
-{0x0000A77D, 0x00001D79}, {0x0000A77E, 0x0000A77F}, {0x0000A780, 0x0000A781}, {0x0000A782, 0x0000A783},
-{0x0000A784, 0x0000A785}, {0x0000A786, 0x0000A787}, {0x0000A78B, 0x0000A78C}, {0x0000A78D, 0x00000265},
-{0x0000A790, 0x0000A791}, {0x0000A792, 0x0000A793}, {0x0000A796, 0x0000A797}, {0x0000A798, 0x0000A799},
-{0x0000A79A, 0x0000A79B}, {0x0000A79C, 0x0000A79D}, {0x0000A79E, 0x0000A79F}, {0x0000A7A0, 0x0000A7A1},
-{0x0000A7A2, 0x0000A7A3}, {0x0000A7A4, 0x0000A7A5}, {0x0000A7A6, 0x0000A7A7}, {0x0000A7A8, 0x0000A7A9},
-{0x0000A7AA, 0x00000266}, {0x0000A7AB, 0x0000025C}, {0x0000A7AC, 0x00000261}, {0x0000A7AD, 0x0000026C},
-{0x0000A7AE, 0x0000026A}, {0x0000A7B0, 0x0000029E}, {0x0000A7B1, 0x00000287}, {0x0000A7B2, 0x0000029D},
-{0x0000A7B3, 0x0000AB53}, {0x0000A7B4, 0x0000A7B5}, {0x0000A7B6, 0x0000A7B7}, {0x0000A7B8, 0x0000A7B9},
-{0x0000A7BA, 0x0000A7BB}, {0x0000A7BC, 0x0000A7BD}, {0x0000A7BE, 0x0000A7BF}, {0x0000A7C2, 0x0000A7C3},
-{0x0000A7C4, 0x0000A794}, {0x0000A7C5, 0x00000282}, {0x0000A7C6, 0x00001D8E}, {0x0000A7C7, 0x0000A7C8},
-{0x0000A7C9, 0x0000A7CA}, {0x0000A7F5, 0x0000A7F6}, {0x0000FF21, 0x0000FF41}, {0x0000FF22, 0x0000FF42},
-{0x0000FF23, 0x0000FF43}, {0x0000FF24, 0x0000FF44}, {0x0000FF25, 0x0000FF45}, {0x0000FF26, 0x0000FF46},
-{0x0000FF27, 0x0000FF47}, {0x0000FF28, 0x0000FF48}, {0x0000FF29, 0x0000FF49}, {0x0000FF2A, 0x0000FF4A},
-{0x0000FF2B, 0x0000FF4B}, {0x0000FF2C, 0x0000FF4C}, {0x0000FF2D, 0x0000FF4D}, {0x0000FF2E, 0x0000FF4E},
-{0x0000FF2F, 0x0000FF4F}, {0x0000FF30, 0x0000FF50}, {0x0000FF31, 0x0000FF51}, {0x0000FF32, 0x0000FF52},
-{0x0000FF33, 0x0000FF53}, {0x0000FF34, 0x0000FF54}, {0x0000FF35, 0x0000FF55}, {0x0000FF36, 0x0000FF56},
-{0x0000FF37, 0x0000FF57}, {0x0000FF38, 0x0000FF58}, {0x0000FF39, 0x0000FF59}, {0x0000FF3A, 0x0000FF5A},
-{0x00010400, 0x00010428}, {0x00010401, 0x00010429}, {0x00010402, 0x0001042A}, {0x00010403, 0x0001042B},
-{0x00010404, 0x0001042C}, {0x00010405, 0x0001042D}, {0x00010406, 0x0001042E}, {0x00010407, 0x0001042F},
-{0x00010408, 0x00010430}, {0x00010409, 0x00010431}, {0x0001040A, 0x00010432}, {0x0001040B, 0x00010433},
-{0x0001040C, 0x00010434}, {0x0001040D, 0x00010435}, {0x0001040E, 0x00010436}, {0x0001040F, 0x00010437},
-{0x00010410, 0x00010438}, {0x00010411, 0x00010439}, {0x00010412, 0x0001043A}, {0x00010413, 0x0001043B},
-{0x00010414, 0x0001043C}, {0x00010415, 0x0001043D}, {0x00010416, 0x0001043E}, {0x00010417, 0x0001043F},
-{0x00010418, 0x00010440}, {0x00010419, 0x00010441}, {0x0001041A, 0x00010442}, {0x0001041B, 0x00010443},
-{0x0001041C, 0x00010444}, {0x0001041D, 0x00010445}, {0x0001041E, 0x00010446}, {0x0001041F, 0x00010447},
-{0x00010420, 0x00010448}, {0x00010421, 0x00010449}, {0x00010422, 0x0001044A}, {0x00010423, 0x0001044B},
-{0x00010424, 0x0001044C}, {0x00010425, 0x0001044D}, {0x00010426, 0x0001044E}, {0x00010427, 0x0001044F},
-{0x000104B0, 0x000104D8}, {0x000104B1, 0x000104D9}, {0x000104B2, 0x000104DA}, {0x000104B3, 0x000104DB},
-{0x000104B4, 0x000104DC}, {0x000104B5, 0x000104DD}, {0x000104B6, 0x000104DE}, {0x000104B7, 0x000104DF},
-{0x000104B8, 0x000104E0}, {0x000104B9, 0x000104E1}, {0x000104BA, 0x000104E2}, {0x000104BB, 0x000104E3},
-{0x000104BC, 0x000104E4}, {0x000104BD, 0x000104E5}, {0x000104BE, 0x000104E6}, {0x000104BF, 0x000104E7},
-{0x000104C0, 0x000104E8}, {0x000104C1, 0x000104E9}, {0x000104C2, 0x000104EA}, {0x000104C3, 0x000104EB},
-{0x000104C4, 0x000104EC}, {0x000104C5, 0x000104ED}, {0x000104C6, 0x000104EE}, {0x000104C7, 0x000104EF},
-{0x000104C8, 0x000104F0}, {0x000104C9, 0x000104F1}, {0x000104CA, 0x000104F2}, {0x000104CB, 0x000104F3},
-{0x000104CC, 0x000104F4}, {0x000104CD, 0x000104F5}, {0x000104CE, 0x000104F6}, {0x000104CF, 0x000104F7},
-{0x000104D0, 0x000104F8}, {0x000104D1, 0x000104F9}, {0x000104D2, 0x000104FA}, {0x000104D3, 0x000104FB},
-{0x00010C80, 0x00010CC0}, {0x00010C81, 0x00010CC1}, {0x00010C82, 0x00010CC2}, {0x00010C83, 0x00010CC3},
-{0x00010C84, 0x00010CC4}, {0x00010C85, 0x00010CC5}, {0x00010C86, 0x00010CC6}, {0x00010C87, 0x00010CC7},
-{0x00010C88, 0x00010CC8}, {0x00010C89, 0x00010CC9}, {0x00010C8A, 0x00010CCA}, {0x00010C8B, 0x00010CCB},
-{0x00010C8C, 0x00010CCC}, {0x00010C8D, 0x00010CCD}, {0x00010C8E, 0x00010CCE}, {0x00010C8F, 0x00010CCF},
-{0x00010C90, 0x00010CD0}, {0x00010C91, 0x00010CD1}, {0x00010C92, 0x00010CD2}, {0x00010C93, 0x00010CD3},
-{0x00010C94, 0x00010CD4}, {0x00010C95, 0x00010CD5}, {0x00010C96, 0x00010CD6}, {0x00010C97, 0x00010CD7},
-{0x00010C98, 0x00010CD8}, {0x00010C99, 0x00010CD9}, {0x00010C9A, 0x00010CDA}, {0x00010C9B, 0x00010CDB},
-{0x00010C9C, 0x00010CDC}, {0x00010C9D, 0x00010CDD}, {0x00010C9E, 0x00010CDE}, {0x00010C9F, 0x00010CDF},
-{0x00010CA0, 0x00010CE0}, {0x00010CA1, 0x00010CE1}, {0x00010CA2, 0x00010CE2}, {0x00010CA3, 0x00010CE3},
-{0x00010CA4, 0x00010CE4}, {0x00010CA5, 0x00010CE5}, {0x00010CA6, 0x00010CE6}, {0x00010CA7, 0x00010CE7},
-{0x00010CA8, 0x00010CE8}, {0x00010CA9, 0x00010CE9}, {0x00010CAA, 0x00010CEA}, {0x00010CAB, 0x00010CEB},
-{0x00010CAC, 0x00010CEC}, {0x00010CAD, 0x00010CED}, {0x00010CAE, 0x00010CEE}, {0x00010CAF, 0x00010CEF},
-{0x00010CB0, 0x00010CF0}, {0x00010CB1, 0x00010CF1}, {0x00010CB2, 0x00010CF2}, {0x000118A0, 0x000118C0},
-{0x000118A1, 0x000118C1}, {0x000118A2, 0x000118C2}, {0x000118A3, 0x000118C3}, {0x000118A4, 0x000118C4},
-{0x000118A5, 0x000118C5}, {0x000118A6, 0x000118C6}, {0x000118A7, 0x000118C7}, {0x000118A8, 0x000118C8},
-{0x000118A9, 0x000118C9}, {0x000118AA, 0x000118CA}, {0x000118AB, 0x000118CB}, {0x000118AC, 0x000118CC},
-{0x000118AD, 0x000118CD}, {0x000118AE, 0x000118CE}, {0x000118AF, 0x000118CF}, {0x000118B0, 0x000118D0},
-{0x000118B1, 0x000118D1}, {0x000118B2, 0x000118D2}, {0x000118B3, 0x000118D3}, {0x000118B4, 0x000118D4},
-{0x000118B5, 0x000118D5}, {0x000118B6, 0x000118D6}, {0x000118B7, 0x000118D7}, {0x000118B8, 0x000118D8},
-{0x000118B9, 0x000118D9}, {0x000118BA, 0x000118DA}, {0x000118BB, 0x000118DB}, {0x000118BC, 0x000118DC},
-{0x000118BD, 0x000118DD}, {0x000118BE, 0x000118DE}, {0x000118BF, 0x000118DF}, {0x00016E40, 0x00016E60},
-{0x00016E41, 0x00016E61}, {0x00016E42, 0x00016E62}, {0x00016E43, 0x00016E63}, {0x00016E44, 0x00016E64},
-{0x00016E45, 0x00016E65}, {0x00016E46, 0x00016E66}, {0x00016E47, 0x00016E67}, {0x00016E48, 0x00016E68},
-{0x00016E49, 0x00016E69}, {0x00016E4A, 0x00016E6A}, {0x00016E4B, 0x00016E6B}, {0x00016E4C, 0x00016E6C},
-{0x00016E4D, 0x00016E6D}, {0x00016E4E, 0x00016E6E}, {0x00016E4F, 0x00016E6F}, {0x00016E50, 0x00016E70},
-{0x00016E51, 0x00016E71}, {0x00016E52, 0x00016E72}, {0x00016E53, 0x00016E73}, {0x00016E54, 0x00016E74},
-{0x00016E55, 0x00016E75}, {0x00016E56, 0x00016E76}, {0x00016E57, 0x00016E77}, {0x00016E58, 0x00016E78},
-{0x00016E59, 0x00016E79}, {0x00016E5A, 0x00016E7A}, {0x00016E5B, 0x00016E7B}, {0x00016E5C, 0x00016E7C},
-{0x00016E5D, 0x00016E7D}, {0x00016E5E, 0x00016E7E}, {0x00016E5F, 0x00016E7F}, {0x0001E900, 0x0001E922},
-{0x0001E901, 0x0001E923}, {0x0001E902, 0x0001E924}, {0x0001E903, 0x0001E925}, {0x0001E904, 0x0001E926},
-{0x0001E905, 0x0001E927}, {0x0001E906, 0x0001E928}, {0x0001E907, 0x0001E929}, {0x0001E908, 0x0001E92A},
-{0x0001E909, 0x0001E92B}, {0x0001E90A, 0x0001E92C}, {0x0001E90B, 0x0001E92D}, {0x0001E90C, 0x0001E92E},
-{0x0001E90D, 0x0001E92F}, {0x0001E90E, 0x0001E930}, {0x0001E90F, 0x0001E931}, {0x0001E910, 0x0001E932},
-{0x0001E911, 0x0001E933}, {0x0001E912, 0x0001E934}, {0x0001E913, 0x0001E935}, {0x0001E914, 0x0001E936},
-{0x0001E915, 0x0001E937}, {0x0001E916, 0x0001E938}, {0x0001E917, 0x0001E939}, {0x0001E918, 0x0001E93A},
-{0x0001E919, 0x0001E93B}, {0x0001E91A, 0x0001E93C}, {0x0001E91B, 0x0001E93D}, {0x0001E91C, 0x0001E93E},
-{0x0001E91D, 0x0001E93F}, {0x0001E91E, 0x0001E940}, {0x0001E91F, 0x0001E941}, {0x0001E920, 0x0001E942},
-{0x0001E921, 0x0001E943},
-};
-
-const std::map<char32_t, char32_t> unicode_map_uppercase = {
-{0x00000061, 0x00000041}, {0x00000062, 0x00000042}, {0x00000063, 0x00000043}, {0x00000064, 0x00000044},
-{0x00000065, 0x00000045}, {0x00000066, 0x00000046}, {0x00000067, 0x00000047}, {0x00000068, 0x00000048},
-{0x00000069, 0x00000049}, {0x0000006A, 0x0000004A}, {0x0000006B, 0x0000004B}, {0x0000006C, 0x0000004C},
-{0x0000006D, 0x0000004D}, {0x0000006E, 0x0000004E}, {0x0000006F, 0x0000004F}, {0x00000070, 0x00000050},
-{0x00000071, 0x00000051}, {0x00000072, 0x00000052}, {0x00000073, 0x00000053}, {0x00000074, 0x00000054},
-{0x00000075, 0x00000055}, {0x00000076, 0x00000056}, {0x00000077, 0x00000057}, {0x00000078, 0x00000058},
-{0x00000079, 0x00000059}, {0x0000007A, 0x0000005A}, {0x000000B5, 0x0000039C}, {0x000000DF, 0x00000053},
-{0x000000E0, 0x000000C0}, {0x000000E1, 0x000000C1}, {0x000000E2, 0x000000C2}, {0x000000E3, 0x000000C3},
-{0x000000E4, 0x000000C4}, {0x000000E5, 0x000000C5}, {0x000000E6, 0x000000C6}, {0x000000E7, 0x000000C7},
-{0x000000E8, 0x000000C8}, {0x000000E9, 0x000000C9}, {0x000000EA, 0x000000CA}, {0x000000EB, 0x000000CB},
-{0x000000EC, 0x000000CC}, {0x000000ED, 0x000000CD}, {0x000000EE, 0x000000CE}, {0x000000EF, 0x000000CF},
-{0x000000F0, 0x000000D0}, {0x000000F1, 0x000000D1}, {0x000000F2, 0x000000D2}, {0x000000F3, 0x000000D3},
-{0x000000F4, 0x000000D4}, {0x000000F5, 0x000000D5}, {0x000000F6, 0x000000D6}, {0x000000F8, 0x000000D8},
-{0x000000F9, 0x000000D9}, {0x000000FA, 0x000000DA}, {0x000000FB, 0x000000DB}, {0x000000FC, 0x000000DC},
-{0x000000FD, 0x000000DD}, {0x000000FE, 0x000000DE}, {0x000000FF, 0x00000178}, {0x00000101, 0x00000100},
-{0x00000103, 0x00000102}, {0x00000105, 0x00000104}, {0x00000107, 0x00000106}, {0x00000109, 0x00000108},
-{0x0000010B, 0x0000010A}, {0x0000010D, 0x0000010C}, {0x0000010F, 0x0000010E}, {0x00000111, 0x00000110},
-{0x00000113, 0x00000112}, {0x00000115, 0x00000114}, {0x00000117, 0x00000116}, {0x00000119, 0x00000118},
-{0x0000011B, 0x0000011A}, {0x0000011D, 0x0000011C}, {0x0000011F, 0x0000011E}, {0x00000121, 0x00000120},
-{0x00000123, 0x00000122}, {0x00000125, 0x00000124}, {0x00000127, 0x00000126}, {0x00000129, 0x00000128},
-{0x0000012B, 0x0000012A}, {0x0000012D, 0x0000012C}, {0x0000012F, 0x0000012E}, {0x00000131, 0x00000049},
-{0x00000133, 0x00000132}, {0x00000135, 0x00000134}, {0x00000137, 0x00000136}, {0x0000013A, 0x00000139},
-{0x0000013C, 0x0000013B}, {0x0000013E, 0x0000013D}, {0x00000140, 0x0000013F}, {0x00000142, 0x00000141},
-{0x00000144, 0x00000143}, {0x00000146, 0x00000145}, {0x00000148, 0x00000147}, {0x00000149, 0x000002BC},
-{0x0000014B, 0x0000014A}, {0x0000014D, 0x0000014C}, {0x0000014F, 0x0000014E}, {0x00000151, 0x00000150},
-{0x00000153, 0x00000152}, {0x00000155, 0x00000154}, {0x00000157, 0x00000156}, {0x00000159, 0x00000158},
-{0x0000015B, 0x0000015A}, {0x0000015D, 0x0000015C}, {0x0000015F, 0x0000015E}, {0x00000161, 0x00000160},
-{0x00000163, 0x00000162}, {0x00000165, 0x00000164}, {0x00000167, 0x00000166}, {0x00000169, 0x00000168},
-{0x0000016B, 0x0000016A}, {0x0000016D, 0x0000016C}, {0x0000016F, 0x0000016E}, {0x00000171, 0x00000170},
-{0x00000173, 0x00000172}, {0x00000175, 0x00000174}, {0x00000177, 0x00000176}, {0x0000017A, 0x00000179},
-{0x0000017C, 0x0000017B}, {0x0000017E, 0x0000017D}, {0x0000017F, 0x00000053}, {0x00000180, 0x00000243},
-{0x00000183, 0x00000182}, {0x00000185, 0x00000184}, {0x00000188, 0x00000187}, {0x0000018C, 0x0000018B},
-{0x00000192, 0x00000191}, {0x00000195, 0x000001F6}, {0x00000199, 0x00000198}, {0x0000019A, 0x0000023D},
-{0x0000019E, 0x00000220}, {0x000001A1, 0x000001A0}, {0x000001A3, 0x000001A2}, {0x000001A5, 0x000001A4},
-{0x000001A8, 0x000001A7}, {0x000001AD, 0x000001AC}, {0x000001B0, 0x000001AF}, {0x000001B4, 0x000001B3},
-{0x000001B6, 0x000001B5}, {0x000001B9, 0x000001B8}, {0x000001BD, 0x000001BC}, {0x000001BF, 0x000001F7},
-{0x000001C5, 0x000001C4}, {0x000001C6, 0x000001C4}, {0x000001C8, 0x000001C7}, {0x000001C9, 0x000001C7},
-{0x000001CB, 0x000001CA}, {0x000001CC, 0x000001CA}, {0x000001CE, 0x000001CD}, {0x000001D0, 0x000001CF},
-{0x000001D2, 0x000001D1}, {0x000001D4, 0x000001D3}, {0x000001D6, 0x000001D5}, {0x000001D8, 0x000001D7},
-{0x000001DA, 0x000001D9}, {0x000001DC, 0x000001DB}, {0x000001DD, 0x0000018E}, {0x000001DF, 0x000001DE},
-{0x000001E1, 0x000001E0}, {0x000001E3, 0x000001E2}, {0x000001E5, 0x000001E4}, {0x000001E7, 0x000001E6},
-{0x000001E9, 0x000001E8}, {0x000001EB, 0x000001EA}, {0x000001ED, 0x000001EC}, {0x000001EF, 0x000001EE},
-{0x000001F0, 0x0000004A}, {0x000001F2, 0x000001F1}, {0x000001F3, 0x000001F1}, {0x000001F5, 0x000001F4},
-{0x000001F9, 0x000001F8}, {0x000001FB, 0x000001FA}, {0x000001FD, 0x000001FC}, {0x000001FF, 0x000001FE},
-{0x00000201, 0x00000200}, {0x00000203, 0x00000202}, {0x00000205, 0x00000204}, {0x00000207, 0x00000206},
-{0x00000209, 0x00000208}, {0x0000020B, 0x0000020A}, {0x0000020D, 0x0000020C}, {0x0000020F, 0x0000020E},
-{0x00000211, 0x00000210}, {0x00000213, 0x00000212}, {0x00000215, 0x00000214}, {0x00000217, 0x00000216},
-{0x00000219, 0x00000218}, {0x0000021B, 0x0000021A}, {0x0000021D, 0x0000021C}, {0x0000021F, 0x0000021E},
-{0x00000223, 0x00000222}, {0x00000225, 0x00000224}, {0x00000227, 0x00000226}, {0x00000229, 0x00000228},
-{0x0000022B, 0x0000022A}, {0x0000022D, 0x0000022C}, {0x0000022F, 0x0000022E}, {0x00000231, 0x00000230},
-{0x00000233, 0x00000232}, {0x0000023C, 0x0000023B}, {0x0000023F, 0x00002C7E}, {0x00000240, 0x00002C7F},
-{0x00000242, 0x00000241}, {0x00000247, 0x00000246}, {0x00000249, 0x00000248}, {0x0000024B, 0x0000024A},
-{0x0000024D, 0x0000024C}, {0x0000024F, 0x0000024E}, {0x00000250, 0x00002C6F}, {0x00000251, 0x00002C6D},
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-{0x00000257, 0x0000018A}, {0x00000259, 0x0000018F}, {0x0000025B, 0x00000190}, {0x0000025C, 0x0000A7AB},
-{0x00000260, 0x00000193}, {0x00000261, 0x0000A7AC}, {0x00000263, 0x00000194}, {0x00000265, 0x0000A78D},
-{0x00000266, 0x0000A7AA}, {0x00000268, 0x00000197}, {0x00000269, 0x00000196}, {0x0000026A, 0x0000A7AE},
-{0x0000026B, 0x00002C62}, {0x0000026C, 0x0000A7AD}, {0x0000026F, 0x0000019C}, {0x00000271, 0x00002C6E},
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-{0x00000282, 0x0000A7C5}, {0x00000283, 0x000001A9}, {0x00000287, 0x0000A7B1}, {0x00000288, 0x000001AE},
-{0x00000289, 0x00000244}, {0x0000028A, 0x000001B1}, {0x0000028B, 0x000001B2}, {0x0000028C, 0x00000245},
-{0x00000292, 0x000001B7}, {0x0000029D, 0x0000A7B2}, {0x0000029E, 0x0000A7B0}, {0x00000345, 0x00000399},
-{0x00000371, 0x00000370}, {0x00000373, 0x00000372}, {0x00000377, 0x00000376}, {0x0000037B, 0x000003FD},
-{0x0000037C, 0x000003FE}, {0x0000037D, 0x000003FF}, {0x00000390, 0x00000399}, {0x000003AC, 0x00000386},
-{0x000003AD, 0x00000388}, {0x000003AE, 0x00000389}, {0x000003AF, 0x0000038A}, {0x000003B0, 0x000003A5},
-{0x000003B1, 0x00000391}, {0x000003B2, 0x00000392}, {0x000003B3, 0x00000393}, {0x000003B4, 0x00000394},
-{0x000003B5, 0x00000395}, {0x000003B6, 0x00000396}, {0x000003B7, 0x00000397}, {0x000003B8, 0x00000398},
-{0x000003B9, 0x00000399}, {0x000003BA, 0x0000039A}, {0x000003BB, 0x0000039B}, {0x000003BC, 0x0000039C},
-{0x000003BD, 0x0000039D}, {0x000003BE, 0x0000039E}, {0x000003BF, 0x0000039F}, {0x000003C0, 0x000003A0},
-{0x000003C1, 0x000003A1}, {0x000003C2, 0x000003A3}, {0x000003C3, 0x000003A3}, {0x000003C4, 0x000003A4},
-{0x000003C5, 0x000003A5}, {0x000003C6, 0x000003A6}, {0x000003C7, 0x000003A7}, {0x000003C8, 0x000003A8},
-{0x000003C9, 0x000003A9}, {0x000003CA, 0x000003AA}, {0x000003CB, 0x000003AB}, {0x000003CC, 0x0000038C},
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-{0x000003DB, 0x000003DA}, {0x000003DD, 0x000003DC}, {0x000003DF, 0x000003DE}, {0x000003E1, 0x000003E0},
-{0x000003E3, 0x000003E2}, {0x000003E5, 0x000003E4}, {0x000003E7, 0x000003E6}, {0x000003E9, 0x000003E8},
-{0x000003EB, 0x000003EA}, {0x000003ED, 0x000003EC}, {0x000003EF, 0x000003EE}, {0x000003F0, 0x0000039A},
-{0x000003F1, 0x000003A1}, {0x000003F2, 0x000003F9}, {0x000003F3, 0x0000037F}, {0x000003F5, 0x00000395},
-{0x000003F8, 0x000003F7}, {0x000003FB, 0x000003FA}, {0x00000430, 0x00000410}, {0x00000431, 0x00000411},
-{0x00000432, 0x00000412}, {0x00000433, 0x00000413}, {0x00000434, 0x00000414}, {0x00000435, 0x00000415},
-{0x00000436, 0x00000416}, {0x00000437, 0x00000417}, {0x00000438, 0x00000418}, {0x00000439, 0x00000419},
-{0x0000043A, 0x0000041A}, {0x0000043B, 0x0000041B}, {0x0000043C, 0x0000041C}, {0x0000043D, 0x0000041D},
-{0x0000043E, 0x0000041E}, {0x0000043F, 0x0000041F}, {0x00000440, 0x00000420}, {0x00000441, 0x00000421},
-{0x00000442, 0x00000422}, {0x00000443, 0x00000423}, {0x00000444, 0x00000424}, {0x00000445, 0x00000425},
-{0x00000446, 0x00000426}, {0x00000447, 0x00000427}, {0x00000448, 0x00000428}, {0x00000449, 0x00000429},
-{0x0000044A, 0x0000042A}, {0x0000044B, 0x0000042B}, {0x0000044C, 0x0000042C}, {0x0000044D, 0x0000042D},
-{0x0000044E, 0x0000042E}, {0x0000044F, 0x0000042F}, {0x00000450, 0x00000400}, {0x00000451, 0x00000401},
-{0x00000452, 0x00000402}, {0x00000453, 0x00000403}, {0x00000454, 0x00000404}, {0x00000455, 0x00000405},
-{0x00000456, 0x00000406}, {0x00000457, 0x00000407}, {0x00000458, 0x00000408}, {0x00000459, 0x00000409},
-{0x0000045A, 0x0000040A}, {0x0000045B, 0x0000040B}, {0x0000045C, 0x0000040C}, {0x0000045D, 0x0000040D},
-{0x0000045E, 0x0000040E}, {0x0000045F, 0x0000040F}, {0x00000461, 0x00000460}, {0x00000463, 0x00000462},
-{0x00000465, 0x00000464}, {0x00000467, 0x00000466}, {0x00000469, 0x00000468}, {0x0000046B, 0x0000046A},
-{0x0000046D, 0x0000046C}, {0x0000046F, 0x0000046E}, {0x00000471, 0x00000470}, {0x00000473, 0x00000472},
-{0x00000475, 0x00000474}, {0x00000477, 0x00000476}, {0x00000479, 0x00000478}, {0x0000047B, 0x0000047A},
-{0x0000047D, 0x0000047C}, {0x0000047F, 0x0000047E}, {0x00000481, 0x00000480}, {0x0000048B, 0x0000048A},
-{0x0000048D, 0x0000048C}, {0x0000048F, 0x0000048E}, {0x00000491, 0x00000490}, {0x00000493, 0x00000492},
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-{0x0000049D, 0x0000049C}, {0x0000049F, 0x0000049E}, {0x000004A1, 0x000004A0}, {0x000004A3, 0x000004A2},
-{0x000004A5, 0x000004A4}, {0x000004A7, 0x000004A6}, {0x000004A9, 0x000004A8}, {0x000004AB, 0x000004AA},
-{0x000004AD, 0x000004AC}, {0x000004AF, 0x000004AE}, {0x000004B1, 0x000004B0}, {0x000004B3, 0x000004B2},
-{0x000004B5, 0x000004B4}, {0x000004B7, 0x000004B6}, {0x000004B9, 0x000004B8}, {0x000004BB, 0x000004BA},
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-{0x0000050D, 0x0000050C}, {0x0000050F, 0x0000050E}, {0x00000511, 0x00000510}, {0x00000513, 0x00000512},
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-{0x00000567, 0x00000537}, {0x00000568, 0x00000538}, {0x00000569, 0x00000539}, {0x0000056A, 0x0000053A},
-{0x0000056B, 0x0000053B}, {0x0000056C, 0x0000053C}, {0x0000056D, 0x0000053D}, {0x0000056E, 0x0000053E},
-{0x0000056F, 0x0000053F}, {0x00000570, 0x00000540}, {0x00000571, 0x00000541}, {0x00000572, 0x00000542},
-{0x00000573, 0x00000543}, {0x00000574, 0x00000544}, {0x00000575, 0x00000545}, {0x00000576, 0x00000546},
-{0x00000577, 0x00000547}, {0x00000578, 0x00000548}, {0x00000579, 0x00000549}, {0x0000057A, 0x0000054A},
-{0x0000057B, 0x0000054B}, {0x0000057C, 0x0000054C}, {0x0000057D, 0x0000054D}, {0x0000057E, 0x0000054E},
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-{0x00000587, 0x00000535}, {0x000010D0, 0x00001C90}, {0x000010D1, 0x00001C91}, {0x000010D2, 0x00001C92},
-{0x000010D3, 0x00001C93}, {0x000010D4, 0x00001C94}, {0x000010D5, 0x00001C95}, {0x000010D6, 0x00001C96},
-{0x000010D7, 0x00001C97}, {0x000010D8, 0x00001C98}, {0x000010D9, 0x00001C99}, {0x000010DA, 0x00001C9A},
-{0x000010DB, 0x00001C9B}, {0x000010DC, 0x00001C9C}, {0x000010DD, 0x00001C9D}, {0x000010DE, 0x00001C9E},
-{0x000010DF, 0x00001C9F}, {0x000010E0, 0x00001CA0}, {0x000010E1, 0x00001CA1}, {0x000010E2, 0x00001CA2},
-{0x000010E3, 0x00001CA3}, {0x000010E4, 0x00001CA4}, {0x000010E5, 0x00001CA5}, {0x000010E6, 0x00001CA6},
-{0x000010E7, 0x00001CA7}, {0x000010E8, 0x00001CA8}, {0x000010E9, 0x00001CA9}, {0x000010EA, 0x00001CAA},
-{0x000010EB, 0x00001CAB}, {0x000010EC, 0x00001CAC}, {0x000010ED, 0x00001CAD}, {0x000010EE, 0x00001CAE},
-{0x000010EF, 0x00001CAF}, {0x000010F0, 0x00001CB0}, {0x000010F1, 0x00001CB1}, {0x000010F2, 0x00001CB2},
-{0x000010F3, 0x00001CB3}, {0x000010F4, 0x00001CB4}, {0x000010F5, 0x00001CB5}, {0x000010F6, 0x00001CB6},
-{0x000010F7, 0x00001CB7}, {0x000010F8, 0x00001CB8}, {0x000010F9, 0x00001CB9}, {0x000010FA, 0x00001CBA},
-{0x000010FD, 0x00001CBD}, {0x000010FE, 0x00001CBE}, {0x000010FF, 0x00001CBF}, {0x000013F8, 0x000013F0},
-{0x000013F9, 0x000013F1}, {0x000013FA, 0x000013F2}, {0x000013FB, 0x000013F3}, {0x000013FC, 0x000013F4},
-{0x000013FD, 0x000013F5}, {0x00001C80, 0x00000412}, {0x00001C81, 0x00000414}, {0x00001C82, 0x0000041E},
-{0x00001C83, 0x00000421}, {0x00001C84, 0x00000422}, {0x00001C85, 0x00000422}, {0x00001C86, 0x0000042A},
-{0x00001C87, 0x00000462}, {0x00001C88, 0x0000A64A}, {0x00001D79, 0x0000A77D}, {0x00001D7D, 0x00002C63},
-{0x00001D8E, 0x0000A7C6}, {0x00001E01, 0x00001E00}, {0x00001E03, 0x00001E02}, {0x00001E05, 0x00001E04},
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-{0x00001E0F, 0x00001E0E}, {0x00001E11, 0x00001E10}, {0x00001E13, 0x00001E12}, {0x00001E15, 0x00001E14},
-{0x00001E17, 0x00001E16}, {0x00001E19, 0x00001E18}, {0x00001E1B, 0x00001E1A}, {0x00001E1D, 0x00001E1C},
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-{0x00001E2F, 0x00001E2E}, {0x00001E31, 0x00001E30}, {0x00001E33, 0x00001E32}, {0x00001E35, 0x00001E34},
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-{0x00001E47, 0x00001E46}, {0x00001E49, 0x00001E48}, {0x00001E4B, 0x00001E4A}, {0x00001E4D, 0x00001E4C},
-{0x00001E4F, 0x00001E4E}, {0x00001E51, 0x00001E50}, {0x00001E53, 0x00001E52}, {0x00001E55, 0x00001E54},
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-{0x00001E5F, 0x00001E5E}, {0x00001E61, 0x00001E60}, {0x00001E63, 0x00001E62}, {0x00001E65, 0x00001E64},
-{0x00001E67, 0x00001E66}, {0x00001E69, 0x00001E68}, {0x00001E6B, 0x00001E6A}, {0x00001E6D, 0x00001E6C},
-{0x00001E6F, 0x00001E6E}, {0x00001E71, 0x00001E70}, {0x00001E73, 0x00001E72}, {0x00001E75, 0x00001E74},
-{0x00001E77, 0x00001E76}, {0x00001E79, 0x00001E78}, {0x00001E7B, 0x00001E7A}, {0x00001E7D, 0x00001E7C},
-{0x00001E7F, 0x00001E7E}, {0x00001E81, 0x00001E80}, {0x00001E83, 0x00001E82}, {0x00001E85, 0x00001E84},
-{0x00001E87, 0x00001E86}, {0x00001E89, 0x00001E88}, {0x00001E8B, 0x00001E8A}, {0x00001E8D, 0x00001E8C},
-{0x00001E8F, 0x00001E8E}, {0x00001E91, 0x00001E90}, {0x00001E93, 0x00001E92}, {0x00001E95, 0x00001E94},
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-{0x00001EB5, 0x00001EB4}, {0x00001EB7, 0x00001EB6}, {0x00001EB9, 0x00001EB8}, {0x00001EBB, 0x00001EBA},
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-{0x00001EDD, 0x00001EDC}, {0x00001EDF, 0x00001EDE}, {0x00001EE1, 0x00001EE0}, {0x00001EE3, 0x00001EE2},
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-{0x00001EED, 0x00001EEC}, {0x00001EEF, 0x00001EEE}, {0x00001EF1, 0x00001EF0}, {0x00001EF3, 0x00001EF2},
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-{0x00001F02, 0x00001F0A}, {0x00001F03, 0x00001F0B}, {0x00001F04, 0x00001F0C}, {0x00001F05, 0x00001F0D},
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-{0x00001F12, 0x00001F1A}, {0x00001F13, 0x00001F1B}, {0x00001F14, 0x00001F1C}, {0x00001F15, 0x00001F1D},
-{0x00001F20, 0x00001F28}, {0x00001F21, 0x00001F29}, {0x00001F22, 0x00001F2A}, {0x00001F23, 0x00001F2B},
-{0x00001F24, 0x00001F2C}, {0x00001F25, 0x00001F2D}, {0x00001F26, 0x00001F2E}, {0x00001F27, 0x00001F2F},
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-{0x00001F34, 0x00001F3C}, {0x00001F35, 0x00001F3D}, {0x00001F36, 0x00001F3E}, {0x00001F37, 0x00001F3F},
-{0x00001F40, 0x00001F48}, {0x00001F41, 0x00001F49}, {0x00001F42, 0x00001F4A}, {0x00001F43, 0x00001F4B},
-{0x00001F44, 0x00001F4C}, {0x00001F45, 0x00001F4D}, {0x00001F50, 0x000003A5}, {0x00001F51, 0x00001F59},
-{0x00001F52, 0x000003A5}, {0x00001F53, 0x00001F5B}, {0x00001F54, 0x000003A5}, {0x00001F55, 0x00001F5D},
-{0x00001F56, 0x000003A5}, {0x00001F57, 0x00001F5F}, {0x00001F60, 0x00001F68}, {0x00001F61, 0x00001F69},
-{0x00001F62, 0x00001F6A}, {0x00001F63, 0x00001F6B}, {0x00001F64, 0x00001F6C}, {0x00001F65, 0x00001F6D},
-{0x00001F66, 0x00001F6E}, {0x00001F67, 0x00001F6F}, {0x00001F70, 0x00001FBA}, {0x00001F71, 0x00001FBB},
-{0x00001F72, 0x00001FC8}, {0x00001F73, 0x00001FC9}, {0x00001F74, 0x00001FCA}, {0x00001F75, 0x00001FCB},
-{0x00001F76, 0x00001FDA}, {0x00001F77, 0x00001FDB}, {0x00001F78, 0x00001FF8}, {0x00001F79, 0x00001FF9},
-{0x00001F7A, 0x00001FEA}, {0x00001F7B, 0x00001FEB}, {0x00001F7C, 0x00001FFA}, {0x00001F7D, 0x00001FFB},
-{0x00001F80, 0x00001F08}, {0x00001F81, 0x00001F09}, {0x00001F82, 0x00001F0A}, {0x00001F83, 0x00001F0B},
-{0x00001F84, 0x00001F0C}, {0x00001F85, 0x00001F0D}, {0x00001F86, 0x00001F0E}, {0x00001F87, 0x00001F0F},
-{0x00001F88, 0x00001F08}, {0x00001F89, 0x00001F09}, {0x00001F8A, 0x00001F0A}, {0x00001F8B, 0x00001F0B},
-{0x00001F8C, 0x00001F0C}, {0x00001F8D, 0x00001F0D}, {0x00001F8E, 0x00001F0E}, {0x00001F8F, 0x00001F0F},
-{0x00001F90, 0x00001F28}, {0x00001F91, 0x00001F29}, {0x00001F92, 0x00001F2A}, {0x00001F93, 0x00001F2B},
-{0x00001F94, 0x00001F2C}, {0x00001F95, 0x00001F2D}, {0x00001F96, 0x00001F2E}, {0x00001F97, 0x00001F2F},
-{0x00001F98, 0x00001F28}, {0x00001F99, 0x00001F29}, {0x00001F9A, 0x00001F2A}, {0x00001F9B, 0x00001F2B},
-{0x00001F9C, 0x00001F2C}, {0x00001F9D, 0x00001F2D}, {0x00001F9E, 0x00001F2E}, {0x00001F9F, 0x00001F2F},
-{0x00001FA0, 0x00001F68}, {0x00001FA1, 0x00001F69}, {0x00001FA2, 0x00001F6A}, {0x00001FA3, 0x00001F6B},
-{0x00001FA4, 0x00001F6C}, {0x00001FA5, 0x00001F6D}, {0x00001FA6, 0x00001F6E}, {0x00001FA7, 0x00001F6F},
-{0x00001FA8, 0x00001F68}, {0x00001FA9, 0x00001F69}, {0x00001FAA, 0x00001F6A}, {0x00001FAB, 0x00001F6B},
-{0x00001FAC, 0x00001F6C}, {0x00001FAD, 0x00001F6D}, {0x00001FAE, 0x00001F6E}, {0x00001FAF, 0x00001F6F},
-{0x00001FB0, 0x00001FB8}, {0x00001FB1, 0x00001FB9}, {0x00001FB2, 0x00001FBA}, {0x00001FB3, 0x00000391},
-{0x00001FB4, 0x00000386}, {0x00001FB6, 0x00000391}, {0x00001FB7, 0x00000391}, {0x00001FBC, 0x00000391},
-{0x00001FBE, 0x00000399}, {0x00001FC2, 0x00001FCA}, {0x00001FC3, 0x00000397}, {0x00001FC4, 0x00000389},
-{0x00001FC6, 0x00000397}, {0x00001FC7, 0x00000397}, {0x00001FCC, 0x00000397}, {0x00001FD0, 0x00001FD8},
-{0x00001FD1, 0x00001FD9}, {0x00001FD2, 0x00000399}, {0x00001FD3, 0x00000399}, {0x00001FD6, 0x00000399},
-{0x00001FD7, 0x00000399}, {0x00001FE0, 0x00001FE8}, {0x00001FE1, 0x00001FE9}, {0x00001FE2, 0x000003A5},
-{0x00001FE3, 0x000003A5}, {0x00001FE4, 0x000003A1}, {0x00001FE5, 0x00001FEC}, {0x00001FE6, 0x000003A5},
-{0x00001FE7, 0x000003A5}, {0x00001FF2, 0x00001FFA}, {0x00001FF3, 0x000003A9}, {0x00001FF4, 0x0000038F},
-{0x00001FF6, 0x000003A9}, {0x00001FF7, 0x000003A9}, {0x00001FFC, 0x000003A9}, {0x0000214E, 0x00002132},
-{0x00002170, 0x00002160}, {0x00002171, 0x00002161}, {0x00002172, 0x00002162}, {0x00002173, 0x00002163},
-{0x00002174, 0x00002164}, {0x00002175, 0x00002165}, {0x00002176, 0x00002166}, {0x00002177, 0x00002167},
-{0x00002178, 0x00002168}, {0x00002179, 0x00002169}, {0x0000217A, 0x0000216A}, {0x0000217B, 0x0000216B},
-{0x0000217C, 0x0000216C}, {0x0000217D, 0x0000216D}, {0x0000217E, 0x0000216E}, {0x0000217F, 0x0000216F},
-{0x00002184, 0x00002183}, {0x000024D0, 0x000024B6}, {0x000024D1, 0x000024B7}, {0x000024D2, 0x000024B8},
-{0x000024D3, 0x000024B9}, {0x000024D4, 0x000024BA}, {0x000024D5, 0x000024BB}, {0x000024D6, 0x000024BC},
-{0x000024D7, 0x000024BD}, {0x000024D8, 0x000024BE}, {0x000024D9, 0x000024BF}, {0x000024DA, 0x000024C0},
-{0x000024DB, 0x000024C1}, {0x000024DC, 0x000024C2}, {0x000024DD, 0x000024C3}, {0x000024DE, 0x000024C4},
-{0x000024DF, 0x000024C5}, {0x000024E0, 0x000024C6}, {0x000024E1, 0x000024C7}, {0x000024E2, 0x000024C8},
-{0x000024E3, 0x000024C9}, {0x000024E4, 0x000024CA}, {0x000024E5, 0x000024CB}, {0x000024E6, 0x000024CC},
-{0x000024E7, 0x000024CD}, {0x000024E8, 0x000024CE}, {0x000024E9, 0x000024CF}, {0x00002C30, 0x00002C00},
-{0x00002C31, 0x00002C01}, {0x00002C32, 0x00002C02}, {0x00002C33, 0x00002C03}, {0x00002C34, 0x00002C04},
-{0x00002C35, 0x00002C05}, {0x00002C36, 0x00002C06}, {0x00002C37, 0x00002C07}, {0x00002C38, 0x00002C08},
-{0x00002C39, 0x00002C09}, {0x00002C3A, 0x00002C0A}, {0x00002C3B, 0x00002C0B}, {0x00002C3C, 0x00002C0C},
-{0x00002C3D, 0x00002C0D}, {0x00002C3E, 0x00002C0E}, {0x00002C3F, 0x00002C0F}, {0x00002C40, 0x00002C10},
-{0x00002C41, 0x00002C11}, {0x00002C42, 0x00002C12}, {0x00002C43, 0x00002C13}, {0x00002C44, 0x00002C14},
-{0x00002C45, 0x00002C15}, {0x00002C46, 0x00002C16}, {0x00002C47, 0x00002C17}, {0x00002C48, 0x00002C18},
-{0x00002C49, 0x00002C19}, {0x00002C4A, 0x00002C1A}, {0x00002C4B, 0x00002C1B}, {0x00002C4C, 0x00002C1C},
-{0x00002C4D, 0x00002C1D}, {0x00002C4E, 0x00002C1E}, {0x00002C4F, 0x00002C1F}, {0x00002C50, 0x00002C20},
-{0x00002C51, 0x00002C21}, {0x00002C52, 0x00002C22}, {0x00002C53, 0x00002C23}, {0x00002C54, 0x00002C24},
-{0x00002C55, 0x00002C25}, {0x00002C56, 0x00002C26}, {0x00002C57, 0x00002C27}, {0x00002C58, 0x00002C28},
-{0x00002C59, 0x00002C29}, {0x00002C5A, 0x00002C2A}, {0x00002C5B, 0x00002C2B}, {0x00002C5C, 0x00002C2C},
-{0x00002C5D, 0x00002C2D}, {0x00002C5E, 0x00002C2E}, {0x00002C61, 0x00002C60}, {0x00002C65, 0x0000023A},
-{0x00002C66, 0x0000023E}, {0x00002C68, 0x00002C67}, {0x00002C6A, 0x00002C69}, {0x00002C6C, 0x00002C6B},
-{0x00002C73, 0x00002C72}, {0x00002C76, 0x00002C75}, {0x00002C81, 0x00002C80}, {0x00002C83, 0x00002C82},
-{0x00002C85, 0x00002C84}, {0x00002C87, 0x00002C86}, {0x00002C89, 0x00002C88}, {0x00002C8B, 0x00002C8A},
-{0x00002C8D, 0x00002C8C}, {0x00002C8F, 0x00002C8E}, {0x00002C91, 0x00002C90}, {0x00002C93, 0x00002C92},
-{0x00002C95, 0x00002C94}, {0x00002C97, 0x00002C96}, {0x00002C99, 0x00002C98}, {0x00002C9B, 0x00002C9A},
-{0x00002C9D, 0x00002C9C}, {0x00002C9F, 0x00002C9E}, {0x00002CA1, 0x00002CA0}, {0x00002CA3, 0x00002CA2},
-{0x00002CA5, 0x00002CA4}, {0x00002CA7, 0x00002CA6}, {0x00002CA9, 0x00002CA8}, {0x00002CAB, 0x00002CAA},
-{0x00002CAD, 0x00002CAC}, {0x00002CAF, 0x00002CAE}, {0x00002CB1, 0x00002CB0}, {0x00002CB3, 0x00002CB2},
-{0x00002CB5, 0x00002CB4}, {0x00002CB7, 0x00002CB6}, {0x00002CB9, 0x00002CB8}, {0x00002CBB, 0x00002CBA},
-{0x00002CBD, 0x00002CBC}, {0x00002CBF, 0x00002CBE}, {0x00002CC1, 0x00002CC0}, {0x00002CC3, 0x00002CC2},
-{0x00002CC5, 0x00002CC4}, {0x00002CC7, 0x00002CC6}, {0x00002CC9, 0x00002CC8}, {0x00002CCB, 0x00002CCA},
-{0x00002CCD, 0x00002CCC}, {0x00002CCF, 0x00002CCE}, {0x00002CD1, 0x00002CD0}, {0x00002CD3, 0x00002CD2},
-{0x00002CD5, 0x00002CD4}, {0x00002CD7, 0x00002CD6}, {0x00002CD9, 0x00002CD8}, {0x00002CDB, 0x00002CDA},
-{0x00002CDD, 0x00002CDC}, {0x00002CDF, 0x00002CDE}, {0x00002CE1, 0x00002CE0}, {0x00002CE3, 0x00002CE2},
-{0x00002CEC, 0x00002CEB}, {0x00002CEE, 0x00002CED}, {0x00002CF3, 0x00002CF2}, {0x00002D00, 0x000010A0},
-{0x00002D01, 0x000010A1}, {0x00002D02, 0x000010A2}, {0x00002D03, 0x000010A3}, {0x00002D04, 0x000010A4},
-{0x00002D05, 0x000010A5}, {0x00002D06, 0x000010A6}, {0x00002D07, 0x000010A7}, {0x00002D08, 0x000010A8},
-{0x00002D09, 0x000010A9}, {0x00002D0A, 0x000010AA}, {0x00002D0B, 0x000010AB}, {0x00002D0C, 0x000010AC},
-{0x00002D0D, 0x000010AD}, {0x00002D0E, 0x000010AE}, {0x00002D0F, 0x000010AF}, {0x00002D10, 0x000010B0},
-{0x00002D11, 0x000010B1}, {0x00002D12, 0x000010B2}, {0x00002D13, 0x000010B3}, {0x00002D14, 0x000010B4},
-{0x00002D15, 0x000010B5}, {0x00002D16, 0x000010B6}, {0x00002D17, 0x000010B7}, {0x00002D18, 0x000010B8},
-{0x00002D19, 0x000010B9}, {0x00002D1A, 0x000010BA}, {0x00002D1B, 0x000010BB}, {0x00002D1C, 0x000010BC},
-{0x00002D1D, 0x000010BD}, {0x00002D1E, 0x000010BE}, {0x00002D1F, 0x000010BF}, {0x00002D20, 0x000010C0},
-{0x00002D21, 0x000010C1}, {0x00002D22, 0x000010C2}, {0x00002D23, 0x000010C3}, {0x00002D24, 0x000010C4},
-{0x00002D25, 0x000010C5}, {0x00002D27, 0x000010C7}, {0x00002D2D, 0x000010CD}, {0x0000A641, 0x0000A640},
-{0x0000A643, 0x0000A642}, {0x0000A645, 0x0000A644}, {0x0000A647, 0x0000A646}, {0x0000A649, 0x0000A648},
-{0x0000A64B, 0x0000A64A}, {0x0000A64D, 0x0000A64C}, {0x0000A64F, 0x0000A64E}, {0x0000A651, 0x0000A650},
-{0x0000A653, 0x0000A652}, {0x0000A655, 0x0000A654}, {0x0000A657, 0x0000A656}, {0x0000A659, 0x0000A658},
-{0x0000A65B, 0x0000A65A}, {0x0000A65D, 0x0000A65C}, {0x0000A65F, 0x0000A65E}, {0x0000A661, 0x0000A660},
-{0x0000A663, 0x0000A662}, {0x0000A665, 0x0000A664}, {0x0000A667, 0x0000A666}, {0x0000A669, 0x0000A668},
-{0x0000A66B, 0x0000A66A}, {0x0000A66D, 0x0000A66C}, {0x0000A681, 0x0000A680}, {0x0000A683, 0x0000A682},
-{0x0000A685, 0x0000A684}, {0x0000A687, 0x0000A686}, {0x0000A689, 0x0000A688}, {0x0000A68B, 0x0000A68A},
-{0x0000A68D, 0x0000A68C}, {0x0000A68F, 0x0000A68E}, {0x0000A691, 0x0000A690}, {0x0000A693, 0x0000A692},
-{0x0000A695, 0x0000A694}, {0x0000A697, 0x0000A696}, {0x0000A699, 0x0000A698}, {0x0000A69B, 0x0000A69A},
-{0x0000A723, 0x0000A722}, {0x0000A725, 0x0000A724}, {0x0000A727, 0x0000A726}, {0x0000A729, 0x0000A728},
-{0x0000A72B, 0x0000A72A}, {0x0000A72D, 0x0000A72C}, {0x0000A72F, 0x0000A72E}, {0x0000A733, 0x0000A732},
-{0x0000A735, 0x0000A734}, {0x0000A737, 0x0000A736}, {0x0000A739, 0x0000A738}, {0x0000A73B, 0x0000A73A},
-{0x0000A73D, 0x0000A73C}, {0x0000A73F, 0x0000A73E}, {0x0000A741, 0x0000A740}, {0x0000A743, 0x0000A742},
-{0x0000A745, 0x0000A744}, {0x0000A747, 0x0000A746}, {0x0000A749, 0x0000A748}, {0x0000A74B, 0x0000A74A},
-{0x0000A74D, 0x0000A74C}, {0x0000A74F, 0x0000A74E}, {0x0000A751, 0x0000A750}, {0x0000A753, 0x0000A752},
-{0x0000A755, 0x0000A754}, {0x0000A757, 0x0000A756}, {0x0000A759, 0x0000A758}, {0x0000A75B, 0x0000A75A},
-{0x0000A75D, 0x0000A75C}, {0x0000A75F, 0x0000A75E}, {0x0000A761, 0x0000A760}, {0x0000A763, 0x0000A762},
-{0x0000A765, 0x0000A764}, {0x0000A767, 0x0000A766}, {0x0000A769, 0x0000A768}, {0x0000A76B, 0x0000A76A},
-{0x0000A76D, 0x0000A76C}, {0x0000A76F, 0x0000A76E}, {0x0000A77A, 0x0000A779}, {0x0000A77C, 0x0000A77B},
-{0x0000A77F, 0x0000A77E}, {0x0000A781, 0x0000A780}, {0x0000A783, 0x0000A782}, {0x0000A785, 0x0000A784},
-{0x0000A787, 0x0000A786}, {0x0000A78C, 0x0000A78B}, {0x0000A791, 0x0000A790}, {0x0000A793, 0x0000A792},
-{0x0000A794, 0x0000A7C4}, {0x0000A797, 0x0000A796}, {0x0000A799, 0x0000A798}, {0x0000A79B, 0x0000A79A},
-{0x0000A79D, 0x0000A79C}, {0x0000A79F, 0x0000A79E}, {0x0000A7A1, 0x0000A7A0}, {0x0000A7A3, 0x0000A7A2},
-{0x0000A7A5, 0x0000A7A4}, {0x0000A7A7, 0x0000A7A6}, {0x0000A7A9, 0x0000A7A8}, {0x0000A7B5, 0x0000A7B4},
-{0x0000A7B7, 0x0000A7B6}, {0x0000A7B9, 0x0000A7B8}, {0x0000A7BB, 0x0000A7BA}, {0x0000A7BD, 0x0000A7BC},
-{0x0000A7BF, 0x0000A7BE}, {0x0000A7C3, 0x0000A7C2}, {0x0000A7C8, 0x0000A7C7}, {0x0000A7CA, 0x0000A7C9},
-{0x0000A7F6, 0x0000A7F5}, {0x0000AB53, 0x0000A7B3}, {0x0000AB70, 0x000013A0}, {0x0000AB71, 0x000013A1},
-{0x0000AB72, 0x000013A2}, {0x0000AB73, 0x000013A3}, {0x0000AB74, 0x000013A4}, {0x0000AB75, 0x000013A5},
-{0x0000AB76, 0x000013A6}, {0x0000AB77, 0x000013A7}, {0x0000AB78, 0x000013A8}, {0x0000AB79, 0x000013A9},
-{0x0000AB7A, 0x000013AA}, {0x0000AB7B, 0x000013AB}, {0x0000AB7C, 0x000013AC}, {0x0000AB7D, 0x000013AD},
-{0x0000AB7E, 0x000013AE}, {0x0000AB7F, 0x000013AF}, {0x0000AB80, 0x000013B0}, {0x0000AB81, 0x000013B1},
-{0x0000AB82, 0x000013B2}, {0x0000AB83, 0x000013B3}, {0x0000AB84, 0x000013B4}, {0x0000AB85, 0x000013B5},
-{0x0000AB86, 0x000013B6}, {0x0000AB87, 0x000013B7}, {0x0000AB88, 0x000013B8}, {0x0000AB89, 0x000013B9},
-{0x0000AB8A, 0x000013BA}, {0x0000AB8B, 0x000013BB}, {0x0000AB8C, 0x000013BC}, {0x0000AB8D, 0x000013BD},
-{0x0000AB8E, 0x000013BE}, {0x0000AB8F, 0x000013BF}, {0x0000AB90, 0x000013C0}, {0x0000AB91, 0x000013C1},
-{0x0000AB92, 0x000013C2}, {0x0000AB93, 0x000013C3}, {0x0000AB94, 0x000013C4}, {0x0000AB95, 0x000013C5},
-{0x0000AB96, 0x000013C6}, {0x0000AB97, 0x000013C7}, {0x0000AB98, 0x000013C8}, {0x0000AB99, 0x000013C9},
-{0x0000AB9A, 0x000013CA}, {0x0000AB9B, 0x000013CB}, {0x0000AB9C, 0x000013CC}, {0x0000AB9D, 0x000013CD},
-{0x0000AB9E, 0x000013CE}, {0x0000AB9F, 0x000013CF}, {0x0000ABA0, 0x000013D0}, {0x0000ABA1, 0x000013D1},
-{0x0000ABA2, 0x000013D2}, {0x0000ABA3, 0x000013D3}, {0x0000ABA4, 0x000013D4}, {0x0000ABA5, 0x000013D5},
-{0x0000ABA6, 0x000013D6}, {0x0000ABA7, 0x000013D7}, {0x0000ABA8, 0x000013D8}, {0x0000ABA9, 0x000013D9},
-{0x0000ABAA, 0x000013DA}, {0x0000ABAB, 0x000013DB}, {0x0000ABAC, 0x000013DC}, {0x0000ABAD, 0x000013DD},
-{0x0000ABAE, 0x000013DE}, {0x0000ABAF, 0x000013DF}, {0x0000ABB0, 0x000013E0}, {0x0000ABB1, 0x000013E1},
-{0x0000ABB2, 0x000013E2}, {0x0000ABB3, 0x000013E3}, {0x0000ABB4, 0x000013E4}, {0x0000ABB5, 0x000013E5},
-{0x0000ABB6, 0x000013E6}, {0x0000ABB7, 0x000013E7}, {0x0000ABB8, 0x000013E8}, {0x0000ABB9, 0x000013E9},
-{0x0000ABBA, 0x000013EA}, {0x0000ABBB, 0x000013EB}, {0x0000ABBC, 0x000013EC}, {0x0000ABBD, 0x000013ED},
-{0x0000ABBE, 0x000013EE}, {0x0000ABBF, 0x000013EF}, {0x0000FB00, 0x00000046}, {0x0000FB01, 0x00000046},
-{0x0000FB02, 0x00000046}, {0x0000FB03, 0x00000046}, {0x0000FB04, 0x00000046}, {0x0000FB05, 0x00000053},
-{0x0000FB06, 0x00000053}, {0x0000FB13, 0x00000544}, {0x0000FB14, 0x00000544}, {0x0000FB15, 0x00000544},
-{0x0000FB16, 0x0000054E}, {0x0000FB17, 0x00000544}, {0x0000FF41, 0x0000FF21}, {0x0000FF42, 0x0000FF22},
-{0x0000FF43, 0x0000FF23}, {0x0000FF44, 0x0000FF24}, {0x0000FF45, 0x0000FF25}, {0x0000FF46, 0x0000FF26},
-{0x0000FF47, 0x0000FF27}, {0x0000FF48, 0x0000FF28}, {0x0000FF49, 0x0000FF29}, {0x0000FF4A, 0x0000FF2A},
-{0x0000FF4B, 0x0000FF2B}, {0x0000FF4C, 0x0000FF2C}, {0x0000FF4D, 0x0000FF2D}, {0x0000FF4E, 0x0000FF2E},
-{0x0000FF4F, 0x0000FF2F}, {0x0000FF50, 0x0000FF30}, {0x0000FF51, 0x0000FF31}, {0x0000FF52, 0x0000FF32},
-{0x0000FF53, 0x0000FF33}, {0x0000FF54, 0x0000FF34}, {0x0000FF55, 0x0000FF35}, {0x0000FF56, 0x0000FF36},
-{0x0000FF57, 0x0000FF37}, {0x0000FF58, 0x0000FF38}, {0x0000FF59, 0x0000FF39}, {0x0000FF5A, 0x0000FF3A},
-{0x00010428, 0x00010400}, {0x00010429, 0x00010401}, {0x0001042A, 0x00010402}, {0x0001042B, 0x00010403},
-{0x0001042C, 0x00010404}, {0x0001042D, 0x00010405}, {0x0001042E, 0x00010406}, {0x0001042F, 0x00010407},
-{0x00010430, 0x00010408}, {0x00010431, 0x00010409}, {0x00010432, 0x0001040A}, {0x00010433, 0x0001040B},
-{0x00010434, 0x0001040C}, {0x00010435, 0x0001040D}, {0x00010436, 0x0001040E}, {0x00010437, 0x0001040F},
-{0x00010438, 0x00010410}, {0x00010439, 0x00010411}, {0x0001043A, 0x00010412}, {0x0001043B, 0x00010413},
-{0x0001043C, 0x00010414}, {0x0001043D, 0x00010415}, {0x0001043E, 0x00010416}, {0x0001043F, 0x00010417},
-{0x00010440, 0x00010418}, {0x00010441, 0x00010419}, {0x00010442, 0x0001041A}, {0x00010443, 0x0001041B},
-{0x00010444, 0x0001041C}, {0x00010445, 0x0001041D}, {0x00010446, 0x0001041E}, {0x00010447, 0x0001041F},
-{0x00010448, 0x00010420}, {0x00010449, 0x00010421}, {0x0001044A, 0x00010422}, {0x0001044B, 0x00010423},
-{0x0001044C, 0x00010424}, {0x0001044D, 0x00010425}, {0x0001044E, 0x00010426}, {0x0001044F, 0x00010427},
-{0x000104D8, 0x000104B0}, {0x000104D9, 0x000104B1}, {0x000104DA, 0x000104B2}, {0x000104DB, 0x000104B3},
-{0x000104DC, 0x000104B4}, {0x000104DD, 0x000104B5}, {0x000104DE, 0x000104B6}, {0x000104DF, 0x000104B7},
-{0x000104E0, 0x000104B8}, {0x000104E1, 0x000104B9}, {0x000104E2, 0x000104BA}, {0x000104E3, 0x000104BB},
-{0x000104E4, 0x000104BC}, {0x000104E5, 0x000104BD}, {0x000104E6, 0x000104BE}, {0x000104E7, 0x000104BF},
-{0x000104E8, 0x000104C0}, {0x000104E9, 0x000104C1}, {0x000104EA, 0x000104C2}, {0x000104EB, 0x000104C3},
-{0x000104EC, 0x000104C4}, {0x000104ED, 0x000104C5}, {0x000104EE, 0x000104C6}, {0x000104EF, 0x000104C7},
-{0x000104F0, 0x000104C8}, {0x000104F1, 0x000104C9}, {0x000104F2, 0x000104CA}, {0x000104F3, 0x000104CB},
-{0x000104F4, 0x000104CC}, {0x000104F5, 0x000104CD}, {0x000104F6, 0x000104CE}, {0x000104F7, 0x000104CF},
-{0x000104F8, 0x000104D0}, {0x000104F9, 0x000104D1}, {0x000104FA, 0x000104D2}, {0x000104FB, 0x000104D3},
-{0x00010CC0, 0x00010C80}, {0x00010CC1, 0x00010C81}, {0x00010CC2, 0x00010C82}, {0x00010CC3, 0x00010C83},
-{0x00010CC4, 0x00010C84}, {0x00010CC5, 0x00010C85}, {0x00010CC6, 0x00010C86}, {0x00010CC7, 0x00010C87},
-{0x00010CC8, 0x00010C88}, {0x00010CC9, 0x00010C89}, {0x00010CCA, 0x00010C8A}, {0x00010CCB, 0x00010C8B},
-{0x00010CCC, 0x00010C8C}, {0x00010CCD, 0x00010C8D}, {0x00010CCE, 0x00010C8E}, {0x00010CCF, 0x00010C8F},
-{0x00010CD0, 0x00010C90}, {0x00010CD1, 0x00010C91}, {0x00010CD2, 0x00010C92}, {0x00010CD3, 0x00010C93},
-{0x00010CD4, 0x00010C94}, {0x00010CD5, 0x00010C95}, {0x00010CD6, 0x00010C96}, {0x00010CD7, 0x00010C97},
-{0x00010CD8, 0x00010C98}, {0x00010CD9, 0x00010C99}, {0x00010CDA, 0x00010C9A}, {0x00010CDB, 0x00010C9B},
-{0x00010CDC, 0x00010C9C}, {0x00010CDD, 0x00010C9D}, {0x00010CDE, 0x00010C9E}, {0x00010CDF, 0x00010C9F},
-{0x00010CE0, 0x00010CA0}, {0x00010CE1, 0x00010CA1}, {0x00010CE2, 0x00010CA2}, {0x00010CE3, 0x00010CA3},
-{0x00010CE4, 0x00010CA4}, {0x00010CE5, 0x00010CA5}, {0x00010CE6, 0x00010CA6}, {0x00010CE7, 0x00010CA7},
-{0x00010CE8, 0x00010CA8}, {0x00010CE9, 0x00010CA9}, {0x00010CEA, 0x00010CAA}, {0x00010CEB, 0x00010CAB},
-{0x00010CEC, 0x00010CAC}, {0x00010CED, 0x00010CAD}, {0x00010CEE, 0x00010CAE}, {0x00010CEF, 0x00010CAF},
-{0x00010CF0, 0x00010CB0}, {0x00010CF1, 0x00010CB1}, {0x00010CF2, 0x00010CB2}, {0x000118C0, 0x000118A0},
-{0x000118C1, 0x000118A1}, {0x000118C2, 0x000118A2}, {0x000118C3, 0x000118A3}, {0x000118C4, 0x000118A4},
-{0x000118C5, 0x000118A5}, {0x000118C6, 0x000118A6}, {0x000118C7, 0x000118A7}, {0x000118C8, 0x000118A8},
-{0x000118C9, 0x000118A9}, {0x000118CA, 0x000118AA}, {0x000118CB, 0x000118AB}, {0x000118CC, 0x000118AC},
-{0x000118CD, 0x000118AD}, {0x000118CE, 0x000118AE}, {0x000118CF, 0x000118AF}, {0x000118D0, 0x000118B0},
-{0x000118D1, 0x000118B1}, {0x000118D2, 0x000118B2}, {0x000118D3, 0x000118B3}, {0x000118D4, 0x000118B4},
-{0x000118D5, 0x000118B5}, {0x000118D6, 0x000118B6}, {0x000118D7, 0x000118B7}, {0x000118D8, 0x000118B8},
-{0x000118D9, 0x000118B9}, {0x000118DA, 0x000118BA}, {0x000118DB, 0x000118BB}, {0x000118DC, 0x000118BC},
-{0x000118DD, 0x000118BD}, {0x000118DE, 0x000118BE}, {0x000118DF, 0x000118BF}, {0x00016E60, 0x00016E40},
-{0x00016E61, 0x00016E41}, {0x00016E62, 0x00016E42}, {0x00016E63, 0x00016E43}, {0x00016E64, 0x00016E44},
-{0x00016E65, 0x00016E45}, {0x00016E66, 0x00016E46}, {0x00016E67, 0x00016E47}, {0x00016E68, 0x00016E48},
-{0x00016E69, 0x00016E49}, {0x00016E6A, 0x00016E4A}, {0x00016E6B, 0x00016E4B}, {0x00016E6C, 0x00016E4C},
-{0x00016E6D, 0x00016E4D}, {0x00016E6E, 0x00016E4E}, {0x00016E6F, 0x00016E4F}, {0x00016E70, 0x00016E50},
-{0x00016E71, 0x00016E51}, {0x00016E72, 0x00016E52}, {0x00016E73, 0x00016E53}, {0x00016E74, 0x00016E54},
-{0x00016E75, 0x00016E55}, {0x00016E76, 0x00016E56}, {0x00016E77, 0x00016E57}, {0x00016E78, 0x00016E58},
-{0x00016E79, 0x00016E59}, {0x00016E7A, 0x00016E5A}, {0x00016E7B, 0x00016E5B}, {0x00016E7C, 0x00016E5C},
-{0x00016E7D, 0x00016E5D}, {0x00016E7E, 0x00016E5E}, {0x00016E7F, 0x00016E5F}, {0x0001E922, 0x0001E900},
-{0x0001E923, 0x0001E901}, {0x0001E924, 0x0001E902}, {0x0001E925, 0x0001E903}, {0x0001E926, 0x0001E904},
-{0x0001E927, 0x0001E905}, {0x0001E928, 0x0001E906}, {0x0001E929, 0x0001E907}, {0x0001E92A, 0x0001E908},
-{0x0001E92B, 0x0001E909}, {0x0001E92C, 0x0001E90A}, {0x0001E92D, 0x0001E90B}, {0x0001E92E, 0x0001E90C},
-{0x0001E92F, 0x0001E90D}, {0x0001E930, 0x0001E90E}, {0x0001E931, 0x0001E90F}, {0x0001E932, 0x0001E910},
-{0x0001E933, 0x0001E911}, {0x0001E934, 0x0001E912}, {0x0001E935, 0x0001E913}, {0x0001E936, 0x0001E914},
-{0x0001E937, 0x0001E915}, {0x0001E938, 0x0001E916}, {0x0001E939, 0x0001E917}, {0x0001E93A, 0x0001E918},
-{0x0001E93B, 0x0001E919}, {0x0001E93C, 0x0001E91A}, {0x0001E93D, 0x0001E91B}, {0x0001E93E, 0x0001E91C},
-{0x0001E93F, 0x0001E91D}, {0x0001E940, 0x0001E91E}, {0x0001E941, 0x0001E91F}, {0x0001E942, 0x0001E920},
-{0x0001E943, 0x0001E921},
-};
-
-const std::multimap<uint32_t, uint32_t> unicode_map_nfd = {
-{0x000000C0, 0x00000041}, {0x000000C0, 0x00000300}, {0x000000C1, 0x00000041}, {0x000000C1, 0x00000301},
-{0x000000C2, 0x00000041}, {0x000000C2, 0x00000302}, {0x000000C3, 0x00000041}, {0x000000C3, 0x00000303},
-{0x000000C4, 0x00000041}, {0x000000C4, 0x00000308}, {0x000000C5, 0x00000041}, {0x000000C5, 0x0000030A},
-{0x000000C7, 0x00000043}, {0x000000C7, 0x00000327}, {0x000000C8, 0x00000045}, {0x000000C8, 0x00000300},
-{0x000000C9, 0x00000045}, {0x000000C9, 0x00000301}, {0x000000CA, 0x00000045}, {0x000000CA, 0x00000302},
-{0x000000CB, 0x00000045}, {0x000000CB, 0x00000308}, {0x000000CC, 0x00000049}, {0x000000CC, 0x00000300},
-{0x000000CD, 0x00000049}, {0x000000CD, 0x00000301}, {0x000000CE, 0x00000049}, {0x000000CE, 0x00000302},
-{0x000000CF, 0x00000049}, {0x000000CF, 0x00000308}, {0x000000D1, 0x0000004E}, {0x000000D1, 0x00000303},
-{0x000000D2, 0x0000004F}, {0x000000D2, 0x00000300}, {0x000000D3, 0x0000004F}, {0x000000D3, 0x00000301},
-{0x000000D4, 0x0000004F}, {0x000000D4, 0x00000302}, {0x000000D5, 0x0000004F}, {0x000000D5, 0x00000303},
-{0x000000D6, 0x0000004F}, {0x000000D6, 0x00000308}, {0x000000D9, 0x00000055}, {0x000000D9, 0x00000300},
-{0x000000DA, 0x00000055}, {0x000000DA, 0x00000301}, {0x000000DB, 0x00000055}, {0x000000DB, 0x00000302},
-{0x000000DC, 0x00000055}, {0x000000DC, 0x00000308}, {0x000000DD, 0x00000059}, {0x000000DD, 0x00000301},
-{0x000000E0, 0x00000061}, {0x000000E0, 0x00000300}, {0x000000E1, 0x00000061}, {0x000000E1, 0x00000301},
-{0x000000E2, 0x00000061}, {0x000000E2, 0x00000302}, {0x000000E3, 0x00000061}, {0x000000E3, 0x00000303},
-{0x000000E4, 0x00000061}, {0x000000E4, 0x00000308}, {0x000000E5, 0x00000061}, {0x000000E5, 0x0000030A},
-{0x000000E7, 0x00000063}, {0x000000E7, 0x00000327}, {0x000000E8, 0x00000065}, {0x000000E8, 0x00000300},
-{0x000000E9, 0x00000065}, {0x000000E9, 0x00000301}, {0x000000EA, 0x00000065}, {0x000000EA, 0x00000302},
-{0x000000EB, 0x00000065}, {0x000000EB, 0x00000308}, {0x000000EC, 0x00000069}, {0x000000EC, 0x00000300},
-{0x000000ED, 0x00000069}, {0x000000ED, 0x00000301}, {0x000000EE, 0x00000069}, {0x000000EE, 0x00000302},
-{0x000000EF, 0x00000069}, {0x000000EF, 0x00000308}, {0x000000F1, 0x0000006E}, {0x000000F1, 0x00000303},
-{0x000000F2, 0x0000006F}, {0x000000F2, 0x00000300}, {0x000000F3, 0x0000006F}, {0x000000F3, 0x00000301},
-{0x000000F4, 0x0000006F}, {0x000000F4, 0x00000302}, {0x000000F5, 0x0000006F}, {0x000000F5, 0x00000303},
-{0x000000F6, 0x0000006F}, {0x000000F6, 0x00000308}, {0x000000F9, 0x00000075}, {0x000000F9, 0x00000300},
-{0x000000FA, 0x00000075}, {0x000000FA, 0x00000301}, {0x000000FB, 0x00000075}, {0x000000FB, 0x00000302},
-{0x000000FC, 0x00000075}, {0x000000FC, 0x00000308}, {0x000000FD, 0x00000079}, {0x000000FD, 0x00000301},
-{0x000000FF, 0x00000079}, {0x000000FF, 0x00000308}, {0x00000100, 0x00000041}, {0x00000100, 0x00000304},
-{0x00000101, 0x00000061}, {0x00000101, 0x00000304}, {0x00000102, 0x00000041}, {0x00000102, 0x00000306},
-{0x00000103, 0x00000061}, {0x00000103, 0x00000306}, {0x00000104, 0x00000041}, {0x00000104, 0x00000328},
-{0x00000105, 0x00000061}, {0x00000105, 0x00000328}, {0x00000106, 0x00000043}, {0x00000106, 0x00000301},
-{0x00000107, 0x00000063}, {0x00000107, 0x00000301}, {0x00000108, 0x00000043}, {0x00000108, 0x00000302},
-{0x00000109, 0x00000063}, {0x00000109, 0x00000302}, {0x0000010A, 0x00000043}, {0x0000010A, 0x00000307},
-{0x0000010B, 0x00000063}, {0x0000010B, 0x00000307}, {0x0000010C, 0x00000043}, {0x0000010C, 0x0000030C},
-{0x0000010D, 0x00000063}, {0x0000010D, 0x0000030C}, {0x0000010E, 0x00000044}, {0x0000010E, 0x0000030C},
-{0x0000010F, 0x00000064}, {0x0000010F, 0x0000030C}, {0x00000112, 0x00000045}, {0x00000112, 0x00000304},
-{0x00000113, 0x00000065}, {0x00000113, 0x00000304}, {0x00000114, 0x00000045}, {0x00000114, 0x00000306},
-{0x00000115, 0x00000065}, {0x00000115, 0x00000306}, {0x00000116, 0x00000045}, {0x00000116, 0x00000307},
-{0x00000117, 0x00000065}, {0x00000117, 0x00000307}, {0x00000118, 0x00000045}, {0x00000118, 0x00000328},
-{0x00000119, 0x00000065}, {0x00000119, 0x00000328}, {0x0000011A, 0x00000045}, {0x0000011A, 0x0000030C},
-{0x0000011B, 0x00000065}, {0x0000011B, 0x0000030C}, {0x0000011C, 0x00000047}, {0x0000011C, 0x00000302},
-{0x0000011D, 0x00000067}, {0x0000011D, 0x00000302}, {0x0000011E, 0x00000047}, {0x0000011E, 0x00000306},
-{0x0000011F, 0x00000067}, {0x0000011F, 0x00000306}, {0x00000120, 0x00000047}, {0x00000120, 0x00000307},
-{0x00000121, 0x00000067}, {0x00000121, 0x00000307}, {0x00000122, 0x00000047}, {0x00000122, 0x00000327},
-{0x00000123, 0x00000067}, {0x00000123, 0x00000327}, {0x00000124, 0x00000048}, {0x00000124, 0x00000302},
-{0x00000125, 0x00000068}, {0x00000125, 0x00000302}, {0x00000128, 0x00000049}, {0x00000128, 0x00000303},
-{0x00000129, 0x00000069}, {0x00000129, 0x00000303}, {0x0000012A, 0x00000049}, {0x0000012A, 0x00000304},
-{0x0000012B, 0x00000069}, {0x0000012B, 0x00000304}, {0x0000012C, 0x00000049}, {0x0000012C, 0x00000306},
-{0x0000012D, 0x00000069}, {0x0000012D, 0x00000306}, {0x0000012E, 0x00000049}, {0x0000012E, 0x00000328},
-{0x0000012F, 0x00000069}, {0x0000012F, 0x00000328}, {0x00000130, 0x00000049}, {0x00000130, 0x00000307},
-{0x00000134, 0x0000004A}, {0x00000134, 0x00000302}, {0x00000135, 0x0000006A}, {0x00000135, 0x00000302},
-{0x00000136, 0x0000004B}, {0x00000136, 0x00000327}, {0x00000137, 0x0000006B}, {0x00000137, 0x00000327},
-{0x00000139, 0x0000004C}, {0x00000139, 0x00000301}, {0x0000013A, 0x0000006C}, {0x0000013A, 0x00000301},
-{0x0000013B, 0x0000004C}, {0x0000013B, 0x00000327}, {0x0000013C, 0x0000006C}, {0x0000013C, 0x00000327},
-{0x0000013D, 0x0000004C}, {0x0000013D, 0x0000030C}, {0x0000013E, 0x0000006C}, {0x0000013E, 0x0000030C},
-{0x00000143, 0x0000004E}, {0x00000143, 0x00000301}, {0x00000144, 0x0000006E}, {0x00000144, 0x00000301},
-{0x00000145, 0x0000004E}, {0x00000145, 0x00000327}, {0x00000146, 0x0000006E}, {0x00000146, 0x00000327},
-{0x00000147, 0x0000004E}, {0x00000147, 0x0000030C}, {0x00000148, 0x0000006E}, {0x00000148, 0x0000030C},
-{0x0000014C, 0x0000004F}, {0x0000014C, 0x00000304}, {0x0000014D, 0x0000006F}, {0x0000014D, 0x00000304},
-{0x0000014E, 0x0000004F}, {0x0000014E, 0x00000306}, {0x0000014F, 0x0000006F}, {0x0000014F, 0x00000306},
-{0x00000150, 0x0000004F}, {0x00000150, 0x0000030B}, {0x00000151, 0x0000006F}, {0x00000151, 0x0000030B},
-{0x00000154, 0x00000052}, {0x00000154, 0x00000301}, {0x00000155, 0x00000072}, {0x00000155, 0x00000301},
-{0x00000156, 0x00000052}, {0x00000156, 0x00000327}, {0x00000157, 0x00000072}, {0x00000157, 0x00000327},
-{0x00000158, 0x00000052}, {0x00000158, 0x0000030C}, {0x00000159, 0x00000072}, {0x00000159, 0x0000030C},
-{0x0000015A, 0x00000053}, {0x0000015A, 0x00000301}, {0x0000015B, 0x00000073}, {0x0000015B, 0x00000301},
-{0x0000015C, 0x00000053}, {0x0000015C, 0x00000302}, {0x0000015D, 0x00000073}, {0x0000015D, 0x00000302},
-{0x0000015E, 0x00000053}, {0x0000015E, 0x00000327}, {0x0000015F, 0x00000073}, {0x0000015F, 0x00000327},
-{0x00000160, 0x00000053}, {0x00000160, 0x0000030C}, {0x00000161, 0x00000073}, {0x00000161, 0x0000030C},
-{0x00000162, 0x00000054}, {0x00000162, 0x00000327}, {0x00000163, 0x00000074}, {0x00000163, 0x00000327},
-{0x00000164, 0x00000054}, {0x00000164, 0x0000030C}, {0x00000165, 0x00000074}, {0x00000165, 0x0000030C},
-{0x00000168, 0x00000055}, {0x00000168, 0x00000303}, {0x00000169, 0x00000075}, {0x00000169, 0x00000303},
-{0x0000016A, 0x00000055}, {0x0000016A, 0x00000304}, {0x0000016B, 0x00000075}, {0x0000016B, 0x00000304},
-{0x0000016C, 0x00000055}, {0x0000016C, 0x00000306}, {0x0000016D, 0x00000075}, {0x0000016D, 0x00000306},
-{0x0000016E, 0x00000055}, {0x0000016E, 0x0000030A}, {0x0000016F, 0x00000075}, {0x0000016F, 0x0000030A},
-{0x00000170, 0x00000055}, {0x00000170, 0x0000030B}, {0x00000171, 0x00000075}, {0x00000171, 0x0000030B},
-{0x00000172, 0x00000055}, {0x00000172, 0x00000328}, {0x00000173, 0x00000075}, {0x00000173, 0x00000328},
-{0x00000174, 0x00000057}, {0x00000174, 0x00000302}, {0x00000175, 0x00000077}, {0x00000175, 0x00000302},
-{0x00000176, 0x00000059}, {0x00000176, 0x00000302}, {0x00000177, 0x00000079}, {0x00000177, 0x00000302},
-{0x00000178, 0x00000059}, {0x00000178, 0x00000308}, {0x00000179, 0x0000005A}, {0x00000179, 0x00000301},
-{0x0000017A, 0x0000007A}, {0x0000017A, 0x00000301}, {0x0000017B, 0x0000005A}, {0x0000017B, 0x00000307},
-{0x0000017C, 0x0000007A}, {0x0000017C, 0x00000307}, {0x0000017D, 0x0000005A}, {0x0000017D, 0x0000030C},
-{0x0000017E, 0x0000007A}, {0x0000017E, 0x0000030C}, {0x000001A0, 0x0000004F}, {0x000001A0, 0x0000031B},
-{0x000001A1, 0x0000006F}, {0x000001A1, 0x0000031B}, {0x000001AF, 0x00000055}, {0x000001AF, 0x0000031B},
-{0x000001B0, 0x00000075}, {0x000001B0, 0x0000031B}, {0x000001CD, 0x00000041}, {0x000001CD, 0x0000030C},
-{0x000001CE, 0x00000061}, {0x000001CE, 0x0000030C}, {0x000001CF, 0x00000049}, {0x000001CF, 0x0000030C},
-{0x000001D0, 0x00000069}, {0x000001D0, 0x0000030C}, {0x000001D1, 0x0000004F}, {0x000001D1, 0x0000030C},
-{0x000001D2, 0x0000006F}, {0x000001D2, 0x0000030C}, {0x000001D3, 0x00000055}, {0x000001D3, 0x0000030C},
-{0x000001D4, 0x00000075}, {0x000001D4, 0x0000030C}, {0x000001D5, 0x00000055}, {0x000001D5, 0x00000308},
-{0x000001D5, 0x00000304}, {0x000001D6, 0x00000075}, {0x000001D6, 0x00000308}, {0x000001D6, 0x00000304},
-{0x000001D7, 0x00000055}, {0x000001D7, 0x00000308}, {0x000001D7, 0x00000301}, {0x000001D8, 0x00000075},
-{0x000001D8, 0x00000308}, {0x000001D8, 0x00000301}, {0x000001D9, 0x00000055}, {0x000001D9, 0x00000308},
-{0x000001D9, 0x0000030C}, {0x000001DA, 0x00000075}, {0x000001DA, 0x00000308}, {0x000001DA, 0x0000030C},
-{0x000001DB, 0x00000055}, {0x000001DB, 0x00000308}, {0x000001DB, 0x00000300}, {0x000001DC, 0x00000075},
-{0x000001DC, 0x00000308}, {0x000001DC, 0x00000300}, {0x000001DE, 0x00000041}, {0x000001DE, 0x00000308},
-{0x000001DE, 0x00000304}, {0x000001DF, 0x00000061}, {0x000001DF, 0x00000308}, {0x000001DF, 0x00000304},
-{0x000001E0, 0x00000041}, {0x000001E0, 0x00000307}, {0x000001E0, 0x00000304}, {0x000001E1, 0x00000061},
-{0x000001E1, 0x00000307}, {0x000001E1, 0x00000304}, {0x000001E2, 0x000000C6}, {0x000001E2, 0x00000304},
-{0x000001E3, 0x000000E6}, {0x000001E3, 0x00000304}, {0x000001E6, 0x00000047}, {0x000001E6, 0x0000030C},
-{0x000001E7, 0x00000067}, {0x000001E7, 0x0000030C}, {0x000001E8, 0x0000004B}, {0x000001E8, 0x0000030C},
-{0x000001E9, 0x0000006B}, {0x000001E9, 0x0000030C}, {0x000001EA, 0x0000004F}, {0x000001EA, 0x00000328},
-{0x000001EB, 0x0000006F}, {0x000001EB, 0x00000328}, {0x000001EC, 0x0000004F}, {0x000001EC, 0x00000328},
-{0x000001EC, 0x00000304}, {0x000001ED, 0x0000006F}, {0x000001ED, 0x00000328}, {0x000001ED, 0x00000304},
-{0x000001EE, 0x000001B7}, {0x000001EE, 0x0000030C}, {0x000001EF, 0x00000292}, {0x000001EF, 0x0000030C},
-{0x000001F0, 0x0000006A}, {0x000001F0, 0x0000030C}, {0x000001F4, 0x00000047}, {0x000001F4, 0x00000301},
-{0x000001F5, 0x00000067}, {0x000001F5, 0x00000301}, {0x000001F8, 0x0000004E}, {0x000001F8, 0x00000300},
-{0x000001F9, 0x0000006E}, {0x000001F9, 0x00000300}, {0x000001FA, 0x00000041}, {0x000001FA, 0x0000030A},
-{0x000001FA, 0x00000301}, {0x000001FB, 0x00000061}, {0x000001FB, 0x0000030A}, {0x000001FB, 0x00000301},
-{0x000001FC, 0x000000C6}, {0x000001FC, 0x00000301}, {0x000001FD, 0x000000E6}, {0x000001FD, 0x00000301},
-{0x000001FE, 0x000000D8}, {0x000001FE, 0x00000301}, {0x000001FF, 0x000000F8}, {0x000001FF, 0x00000301},
-{0x00000200, 0x00000041}, {0x00000200, 0x0000030F}, {0x00000201, 0x00000061}, {0x00000201, 0x0000030F},
-{0x00000202, 0x00000041}, {0x00000202, 0x00000311}, {0x00000203, 0x00000061}, {0x00000203, 0x00000311},
-{0x00000204, 0x00000045}, {0x00000204, 0x0000030F}, {0x00000205, 0x00000065}, {0x00000205, 0x0000030F},
-{0x00000206, 0x00000045}, {0x00000206, 0x00000311}, {0x00000207, 0x00000065}, {0x00000207, 0x00000311},
-{0x00000208, 0x00000049}, {0x00000208, 0x0000030F}, {0x00000209, 0x00000069}, {0x00000209, 0x0000030F},
-{0x0000020A, 0x00000049}, {0x0000020A, 0x00000311}, {0x0000020B, 0x00000069}, {0x0000020B, 0x00000311},
-{0x0000020C, 0x0000004F}, {0x0000020C, 0x0000030F}, {0x0000020D, 0x0000006F}, {0x0000020D, 0x0000030F},
-{0x0000020E, 0x0000004F}, {0x0000020E, 0x00000311}, {0x0000020F, 0x0000006F}, {0x0000020F, 0x00000311},
-{0x00000210, 0x00000052}, {0x00000210, 0x0000030F}, {0x00000211, 0x00000072}, {0x00000211, 0x0000030F},
-{0x00000212, 0x00000052}, {0x00000212, 0x00000311}, {0x00000213, 0x00000072}, {0x00000213, 0x00000311},
-{0x00000214, 0x00000055}, {0x00000214, 0x0000030F}, {0x00000215, 0x00000075}, {0x00000215, 0x0000030F},
-{0x00000216, 0x00000055}, {0x00000216, 0x00000311}, {0x00000217, 0x00000075}, {0x00000217, 0x00000311},
-{0x00000218, 0x00000053}, {0x00000218, 0x00000326}, {0x00000219, 0x00000073}, {0x00000219, 0x00000326},
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-{0x00001F77, 0x00000301}, {0x00001F78, 0x000003BF}, {0x00001F78, 0x00000300}, {0x00001F79, 0x000003BF},
-{0x00001F79, 0x00000301}, {0x00001F7A, 0x000003C5}, {0x00001F7A, 0x00000300}, {0x00001F7B, 0x000003C5},
-{0x00001F7B, 0x00000301}, {0x00001F7C, 0x000003C9}, {0x00001F7C, 0x00000300}, {0x00001F7D, 0x000003C9},
-{0x00001F7D, 0x00000301}, {0x00001F80, 0x000003B1}, {0x00001F80, 0x00000313}, {0x00001F80, 0x00000345},
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-{0x00001F84, 0x00000313}, {0x00001F84, 0x00000301}, {0x00001F84, 0x00000345}, {0x00001F85, 0x000003B1},
-{0x00001F85, 0x00000314}, {0x00001F85, 0x00000301}, {0x00001F85, 0x00000345}, {0x00001F86, 0x000003B1},
-{0x00001F86, 0x00000313}, {0x00001F86, 0x00000342}, {0x00001F86, 0x00000345}, {0x00001F87, 0x000003B1},
-{0x00001F87, 0x00000314}, {0x00001F87, 0x00000342}, {0x00001F87, 0x00000345}, {0x00001F88, 0x00000391},
-{0x00001F88, 0x00000313}, {0x00001F88, 0x00000345}, {0x00001F89, 0x00000391}, {0x00001F89, 0x00000314},
-{0x00001F89, 0x00000345}, {0x00001F8A, 0x00000391}, {0x00001F8A, 0x00000313}, {0x00001F8A, 0x00000300},
-{0x00001F8A, 0x00000345}, {0x00001F8B, 0x00000391}, {0x00001F8B, 0x00000314}, {0x00001F8B, 0x00000300},
-{0x00001F8B, 0x00000345}, {0x00001F8C, 0x00000391}, {0x00001F8C, 0x00000313}, {0x00001F8C, 0x00000301},
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-{0x00001F94, 0x00000313}, {0x00001F94, 0x00000301}, {0x00001F94, 0x00000345}, {0x00001F95, 0x000003B7},
-{0x00001F95, 0x00000314}, {0x00001F95, 0x00000301}, {0x00001F95, 0x00000345}, {0x00001F96, 0x000003B7},
-{0x00001F96, 0x00000313}, {0x00001F96, 0x00000342}, {0x00001F96, 0x00000345}, {0x00001F97, 0x000003B7},
-{0x00001F97, 0x00000314}, {0x00001F97, 0x00000342}, {0x00001F97, 0x00000345}, {0x00001F98, 0x00000397},
-{0x00001F98, 0x00000313}, {0x00001F98, 0x00000345}, {0x00001F99, 0x00000397}, {0x00001F99, 0x00000314},
-{0x00001F99, 0x00000345}, {0x00001F9A, 0x00000397}, {0x00001F9A, 0x00000313}, {0x00001F9A, 0x00000300},
-{0x00001F9A, 0x00000345}, {0x00001F9B, 0x00000397}, {0x00001F9B, 0x00000314}, {0x00001F9B, 0x00000300},
-{0x00001F9B, 0x00000345}, {0x00001F9C, 0x00000397}, {0x00001F9C, 0x00000313}, {0x00001F9C, 0x00000301},
-{0x00001F9C, 0x00000345}, {0x00001F9D, 0x00000397}, {0x00001F9D, 0x00000314}, {0x00001F9D, 0x00000301},
-{0x00001F9D, 0x00000345}, {0x00001F9E, 0x00000397}, {0x00001F9E, 0x00000313}, {0x00001F9E, 0x00000342},
-{0x00001F9E, 0x00000345}, {0x00001F9F, 0x00000397}, {0x00001F9F, 0x00000314}, {0x00001F9F, 0x00000342},
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-{0x00001FA4, 0x00000313}, {0x00001FA4, 0x00000301}, {0x00001FA4, 0x00000345}, {0x00001FA5, 0x000003C9},
-{0x00001FA5, 0x00000314}, {0x00001FA5, 0x00000301}, {0x00001FA5, 0x00000345}, {0x00001FA6, 0x000003C9},
-{0x00001FA6, 0x00000313}, {0x00001FA6, 0x00000342}, {0x00001FA6, 0x00000345}, {0x00001FA7, 0x000003C9},
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-{0x0000F903, 0x00008CC8}, {0x0000F904, 0x00006ED1}, {0x0000F905, 0x00004E32}, {0x0000F906, 0x000053E5},
-{0x0000F907, 0x00009F9C}, {0x0000F908, 0x00009F9C}, {0x0000F909, 0x00005951}, {0x0000F90A, 0x000091D1},
-{0x0000F90B, 0x00005587}, {0x0000F90C, 0x00005948}, {0x0000F90D, 0x000061F6}, {0x0000F90E, 0x00007669},
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-{0x0000F923, 0x000085CD}, {0x0000F924, 0x00008964}, {0x0000F925, 0x000062C9}, {0x0000F926, 0x000081D8},
-{0x0000F927, 0x0000881F}, {0x0000F928, 0x00005ECA}, {0x0000F929, 0x00006717}, {0x0000F92A, 0x00006D6A},
-{0x0000F92B, 0x000072FC}, {0x0000F92C, 0x000090CE}, {0x0000F92D, 0x00004F86}, {0x0000F92E, 0x000051B7},
-{0x0000F92F, 0x000052DE}, {0x0000F930, 0x000064C4}, {0x0000F931, 0x00006AD3}, {0x0000F932, 0x00007210},
-{0x0000F933, 0x000076E7}, {0x0000F934, 0x00008001}, {0x0000F935, 0x00008606}, {0x0000F936, 0x0000865C},
-{0x0000F937, 0x00008DEF}, {0x0000F938, 0x00009732}, {0x0000F939, 0x00009B6F}, {0x0000F93A, 0x00009DFA},
-{0x0000F93B, 0x0000788C}, {0x0000F93C, 0x0000797F}, {0x0000F93D, 0x00007DA0}, {0x0000F93E, 0x000083C9},
-{0x0000F93F, 0x00009304}, {0x0000F940, 0x00009E7F}, {0x0000F941, 0x00008AD6}, {0x0000F942, 0x000058DF},
-{0x0000F943, 0x00005F04}, {0x0000F944, 0x00007C60}, {0x0000F945, 0x0000807E}, {0x0000F946, 0x00007262},
-{0x0000F947, 0x000078CA}, {0x0000F948, 0x00008CC2}, {0x0000F949, 0x000096F7}, {0x0000F94A, 0x000058D8},
-{0x0000F94B, 0x00005C62}, {0x0000F94C, 0x00006A13}, {0x0000F94D, 0x00006DDA}, {0x0000F94E, 0x00006F0F},
-{0x0000F94F, 0x00007D2F}, {0x0000F950, 0x00007E37}, {0x0000F951, 0x0000964B}, {0x0000F952, 0x000052D2},
-{0x0000F953, 0x0000808B}, {0x0000F954, 0x000051DC}, {0x0000F955, 0x000051CC}, {0x0000F956, 0x00007A1C},
-{0x0000F957, 0x00007DBE}, {0x0000F958, 0x000083F1}, {0x0000F959, 0x00009675}, {0x0000F95A, 0x00008B80},
-{0x0000F95B, 0x000062CF}, {0x0000F95C, 0x00006A02}, {0x0000F95D, 0x00008AFE}, {0x0000F95E, 0x00004E39},
-{0x0000F95F, 0x00005BE7}, {0x0000F960, 0x00006012}, {0x0000F961, 0x00007387}, {0x0000F962, 0x00007570},
-{0x0000F963, 0x00005317}, {0x0000F964, 0x000078FB}, {0x0000F965, 0x00004FBF}, {0x0000F966, 0x00005FA9},
-{0x0000F967, 0x00004E0D}, {0x0000F968, 0x00006CCC}, {0x0000F969, 0x00006578}, {0x0000F96A, 0x00007D22},
-{0x0000F96B, 0x000053C3}, {0x0000F96C, 0x0000585E}, {0x0000F96D, 0x00007701}, {0x0000F96E, 0x00008449},
-{0x0000F96F, 0x00008AAA}, {0x0000F970, 0x00006BBA}, {0x0000F971, 0x00008FB0}, {0x0000F972, 0x00006C88},
-{0x0000F973, 0x000062FE}, {0x0000F974, 0x000082E5}, {0x0000F975, 0x000063A0}, {0x0000F976, 0x00007565},
-{0x0000F977, 0x00004EAE}, {0x0000F978, 0x00005169}, {0x0000F979, 0x000051C9}, {0x0000F97A, 0x00006881},
-{0x0000F97B, 0x00007CE7}, {0x0000F97C, 0x0000826F}, {0x0000F97D, 0x00008AD2}, {0x0000F97E, 0x000091CF},
-{0x0000F97F, 0x000052F5}, {0x0000F980, 0x00005442}, {0x0000F981, 0x00005973}, {0x0000F982, 0x00005EEC},
-{0x0000F983, 0x000065C5}, {0x0000F984, 0x00006FFE}, {0x0000F985, 0x0000792A}, {0x0000F986, 0x000095AD},
-{0x0000F987, 0x00009A6A}, {0x0000F988, 0x00009E97}, {0x0000F989, 0x00009ECE}, {0x0000F98A, 0x0000529B},
-{0x0000F98B, 0x000066C6}, {0x0000F98C, 0x00006B77}, {0x0000F98D, 0x00008F62}, {0x0000F98E, 0x00005E74},
-{0x0000F98F, 0x00006190}, {0x0000F990, 0x00006200}, {0x0000F991, 0x0000649A}, {0x0000F992, 0x00006F23},
-{0x0000F993, 0x00007149}, {0x0000F994, 0x00007489}, {0x0000F995, 0x000079CA}, {0x0000F996, 0x00007DF4},
-{0x0000F997, 0x0000806F}, {0x0000F998, 0x00008F26}, {0x0000F999, 0x000084EE}, {0x0000F99A, 0x00009023},
-{0x0000F99B, 0x0000934A}, {0x0000F99C, 0x00005217}, {0x0000F99D, 0x000052A3}, {0x0000F99E, 0x000054BD},
-{0x0000F99F, 0x000070C8}, {0x0000F9A0, 0x000088C2}, {0x0000F9A1, 0x00008AAA}, {0x0000F9A2, 0x00005EC9},
-{0x0000F9A3, 0x00005FF5}, {0x0000F9A4, 0x0000637B}, {0x0000F9A5, 0x00006BAE}, {0x0000F9A6, 0x00007C3E},
-{0x0000F9A7, 0x00007375}, {0x0000F9A8, 0x00004EE4}, {0x0000F9A9, 0x000056F9}, {0x0000F9AA, 0x00005BE7},
-{0x0000F9AB, 0x00005DBA}, {0x0000F9AC, 0x0000601C}, {0x0000F9AD, 0x000073B2}, {0x0000F9AE, 0x00007469},
-{0x0000F9AF, 0x00007F9A}, {0x0000F9B0, 0x00008046}, {0x0000F9B1, 0x00009234}, {0x0000F9B2, 0x000096F6},
-{0x0000F9B3, 0x00009748}, {0x0000F9B4, 0x00009818}, {0x0000F9B5, 0x00004F8B}, {0x0000F9B6, 0x000079AE},
-{0x0000F9B7, 0x000091B4}, {0x0000F9B8, 0x000096B8}, {0x0000F9B9, 0x000060E1}, {0x0000F9BA, 0x00004E86},
-{0x0000F9BB, 0x000050DA}, {0x0000F9BC, 0x00005BEE}, {0x0000F9BD, 0x00005C3F}, {0x0000F9BE, 0x00006599},
-{0x0000F9BF, 0x00006A02}, {0x0000F9C0, 0x000071CE}, {0x0000F9C1, 0x00007642}, {0x0000F9C2, 0x000084FC},
-{0x0000F9C3, 0x0000907C}, {0x0000F9C4, 0x00009F8D}, {0x0000F9C5, 0x00006688}, {0x0000F9C6, 0x0000962E},
-{0x0000F9C7, 0x00005289}, {0x0000F9C8, 0x0000677B}, {0x0000F9C9, 0x000067F3}, {0x0000F9CA, 0x00006D41},
-{0x0000F9CB, 0x00006E9C}, {0x0000F9CC, 0x00007409}, {0x0000F9CD, 0x00007559}, {0x0000F9CE, 0x0000786B},
-{0x0000F9CF, 0x00007D10}, {0x0000F9D0, 0x0000985E}, {0x0000F9D1, 0x0000516D}, {0x0000F9D2, 0x0000622E},
-{0x0000F9D3, 0x00009678}, {0x0000F9D4, 0x0000502B}, {0x0000F9D5, 0x00005D19}, {0x0000F9D6, 0x00006DEA},
-{0x0000F9D7, 0x00008F2A}, {0x0000F9D8, 0x00005F8B}, {0x0000F9D9, 0x00006144}, {0x0000F9DA, 0x00006817},
-{0x0000F9DB, 0x00007387}, {0x0000F9DC, 0x00009686}, {0x0000F9DD, 0x00005229}, {0x0000F9DE, 0x0000540F},
-{0x0000F9DF, 0x00005C65}, {0x0000F9E0, 0x00006613}, {0x0000F9E1, 0x0000674E}, {0x0000F9E2, 0x000068A8},
-{0x0000F9E3, 0x00006CE5}, {0x0000F9E4, 0x00007406}, {0x0000F9E5, 0x000075E2}, {0x0000F9E6, 0x00007F79},
-{0x0000F9E7, 0x000088CF}, {0x0000F9E8, 0x000088E1}, {0x0000F9E9, 0x000091CC}, {0x0000F9EA, 0x000096E2},
-{0x0000F9EB, 0x0000533F}, {0x0000F9EC, 0x00006EBA}, {0x0000F9ED, 0x0000541D}, {0x0000F9EE, 0x000071D0},
-{0x0000F9EF, 0x00007498}, {0x0000F9F0, 0x000085FA}, {0x0000F9F1, 0x000096A3}, {0x0000F9F2, 0x00009C57},
-{0x0000F9F3, 0x00009E9F}, {0x0000F9F4, 0x00006797}, {0x0000F9F5, 0x00006DCB}, {0x0000F9F6, 0x000081E8},
-{0x0000F9F7, 0x00007ACB}, {0x0000F9F8, 0x00007B20}, {0x0000F9F9, 0x00007C92}, {0x0000F9FA, 0x000072C0},
-{0x0000F9FB, 0x00007099}, {0x0000F9FC, 0x00008B58}, {0x0000F9FD, 0x00004EC0}, {0x0000F9FE, 0x00008336},
-{0x0000F9FF, 0x0000523A}, {0x0000FA00, 0x00005207}, {0x0000FA01, 0x00005EA6}, {0x0000FA02, 0x000062D3},
-{0x0000FA03, 0x00007CD6}, {0x0000FA04, 0x00005B85}, {0x0000FA05, 0x00006D1E}, {0x0000FA06, 0x000066B4},
-{0x0000FA07, 0x00008F3B}, {0x0000FA08, 0x0000884C}, {0x0000FA09, 0x0000964D}, {0x0000FA0A, 0x0000898B},
-{0x0000FA0B, 0x00005ED3}, {0x0000FA0C, 0x00005140}, {0x0000FA0D, 0x000055C0}, {0x0000FA10, 0x0000585A},
-{0x0000FA12, 0x00006674}, {0x0000FA15, 0x000051DE}, {0x0000FA16, 0x0000732A}, {0x0000FA17, 0x000076CA},
-{0x0000FA18, 0x0000793C}, {0x0000FA19, 0x0000795E}, {0x0000FA1A, 0x00007965}, {0x0000FA1B, 0x0000798F},
-{0x0000FA1C, 0x00009756}, {0x0000FA1D, 0x00007CBE}, {0x0000FA1E, 0x00007FBD}, {0x0000FA20, 0x00008612},
-{0x0000FA22, 0x00008AF8}, {0x0000FA25, 0x00009038}, {0x0000FA26, 0x000090FD}, {0x0000FA2A, 0x000098EF},
-{0x0000FA2B, 0x000098FC}, {0x0000FA2C, 0x00009928}, {0x0000FA2D, 0x00009DB4}, {0x0000FA2E, 0x000090DE},
-{0x0000FA2F, 0x000096B7}, {0x0000FA30, 0x00004FAE}, {0x0000FA31, 0x000050E7}, {0x0000FA32, 0x0000514D},
-{0x0000FA33, 0x000052C9}, {0x0000FA34, 0x000052E4}, {0x0000FA35, 0x00005351}, {0x0000FA36, 0x0000559D},
-{0x0000FA37, 0x00005606}, {0x0000FA38, 0x00005668}, {0x0000FA39, 0x00005840}, {0x0000FA3A, 0x000058A8},
-{0x0000FA3B, 0x00005C64}, {0x0000FA3C, 0x00005C6E}, {0x0000FA3D, 0x00006094}, {0x0000FA3E, 0x00006168},
-{0x0000FA3F, 0x0000618E}, {0x0000FA40, 0x000061F2}, {0x0000FA41, 0x0000654F}, {0x0000FA42, 0x000065E2},
-{0x0000FA43, 0x00006691}, {0x0000FA44, 0x00006885}, {0x0000FA45, 0x00006D77}, {0x0000FA46, 0x00006E1A},
-{0x0000FA47, 0x00006F22}, {0x0000FA48, 0x0000716E}, {0x0000FA49, 0x0000722B}, {0x0000FA4A, 0x00007422},
-{0x0000FA4B, 0x00007891}, {0x0000FA4C, 0x0000793E}, {0x0000FA4D, 0x00007949}, {0x0000FA4E, 0x00007948},
-{0x0000FA4F, 0x00007950}, {0x0000FA50, 0x00007956}, {0x0000FA51, 0x0000795D}, {0x0000FA52, 0x0000798D},
-{0x0000FA53, 0x0000798E}, {0x0000FA54, 0x00007A40}, {0x0000FA55, 0x00007A81}, {0x0000FA56, 0x00007BC0},
-{0x0000FA57, 0x00007DF4}, {0x0000FA58, 0x00007E09}, {0x0000FA59, 0x00007E41}, {0x0000FA5A, 0x00007F72},
-{0x0000FA5B, 0x00008005}, {0x0000FA5C, 0x000081ED}, {0x0000FA5D, 0x00008279}, {0x0000FA5E, 0x00008279},
-{0x0000FA5F, 0x00008457}, {0x0000FA60, 0x00008910}, {0x0000FA61, 0x00008996}, {0x0000FA62, 0x00008B01},
-{0x0000FA63, 0x00008B39}, {0x0000FA64, 0x00008CD3}, {0x0000FA65, 0x00008D08}, {0x0000FA66, 0x00008FB6},
-{0x0000FA67, 0x00009038}, {0x0000FA68, 0x000096E3}, {0x0000FA69, 0x000097FF}, {0x0000FA6A, 0x0000983B},
-{0x0000FA6B, 0x00006075}, {0x0000FA6C, 0x000242EE}, {0x0000FA6D, 0x00008218}, {0x0000FA70, 0x00004E26},
-{0x0000FA71, 0x000051B5}, {0x0000FA72, 0x00005168}, {0x0000FA73, 0x00004F80}, {0x0000FA74, 0x00005145},
-{0x0000FA75, 0x00005180}, {0x0000FA76, 0x000052C7}, {0x0000FA77, 0x000052FA}, {0x0000FA78, 0x0000559D},
-{0x0000FA79, 0x00005555}, {0x0000FA7A, 0x00005599}, {0x0000FA7B, 0x000055E2}, {0x0000FA7C, 0x0000585A},
-{0x0000FA7D, 0x000058B3}, {0x0000FA7E, 0x00005944}, {0x0000FA7F, 0x00005954}, {0x0000FA80, 0x00005A62},
-{0x0000FA81, 0x00005B28}, {0x0000FA82, 0x00005ED2}, {0x0000FA83, 0x00005ED9}, {0x0000FA84, 0x00005F69},
-{0x0000FA85, 0x00005FAD}, {0x0000FA86, 0x000060D8}, {0x0000FA87, 0x0000614E}, {0x0000FA88, 0x00006108},
-{0x0000FA89, 0x0000618E}, {0x0000FA8A, 0x00006160}, {0x0000FA8B, 0x000061F2}, {0x0000FA8C, 0x00006234},
-{0x0000FA8D, 0x000063C4}, {0x0000FA8E, 0x0000641C}, {0x0000FA8F, 0x00006452}, {0x0000FA90, 0x00006556},
-{0x0000FA91, 0x00006674}, {0x0000FA92, 0x00006717}, {0x0000FA93, 0x0000671B}, {0x0000FA94, 0x00006756},
-{0x0000FA95, 0x00006B79}, {0x0000FA96, 0x00006BBA}, {0x0000FA97, 0x00006D41}, {0x0000FA98, 0x00006EDB},
-{0x0000FA99, 0x00006ECB}, {0x0000FA9A, 0x00006F22}, {0x0000FA9B, 0x0000701E}, {0x0000FA9C, 0x0000716E},
-{0x0000FA9D, 0x000077A7}, {0x0000FA9E, 0x00007235}, {0x0000FA9F, 0x000072AF}, {0x0000FAA0, 0x0000732A},
-{0x0000FAA1, 0x00007471}, {0x0000FAA2, 0x00007506}, {0x0000FAA3, 0x0000753B}, {0x0000FAA4, 0x0000761D},
-{0x0000FAA5, 0x0000761F}, {0x0000FAA6, 0x000076CA}, {0x0000FAA7, 0x000076DB}, {0x0000FAA8, 0x000076F4},
-{0x0000FAA9, 0x0000774A}, {0x0000FAAA, 0x00007740}, {0x0000FAAB, 0x000078CC}, {0x0000FAAC, 0x00007AB1},
-{0x0000FAAD, 0x00007BC0}, {0x0000FAAE, 0x00007C7B}, {0x0000FAAF, 0x00007D5B}, {0x0000FAB0, 0x00007DF4},
-{0x0000FAB1, 0x00007F3E}, {0x0000FAB2, 0x00008005}, {0x0000FAB3, 0x00008352}, {0x0000FAB4, 0x000083EF},
-{0x0000FAB5, 0x00008779}, {0x0000FAB6, 0x00008941}, {0x0000FAB7, 0x00008986}, {0x0000FAB8, 0x00008996},
-{0x0000FAB9, 0x00008ABF}, {0x0000FABA, 0x00008AF8}, {0x0000FABB, 0x00008ACB}, {0x0000FABC, 0x00008B01},
-{0x0000FABD, 0x00008AFE}, {0x0000FABE, 0x00008AED}, {0x0000FABF, 0x00008B39}, {0x0000FAC0, 0x00008B8A},
-{0x0000FAC1, 0x00008D08}, {0x0000FAC2, 0x00008F38}, {0x0000FAC3, 0x00009072}, {0x0000FAC4, 0x00009199},
-{0x0000FAC5, 0x00009276}, {0x0000FAC6, 0x0000967C}, {0x0000FAC7, 0x000096E3}, {0x0000FAC8, 0x00009756},
-{0x0000FAC9, 0x000097DB}, {0x0000FACA, 0x000097FF}, {0x0000FACB, 0x0000980B}, {0x0000FACC, 0x0000983B},
-{0x0000FACD, 0x00009B12}, {0x0000FACE, 0x00009F9C}, {0x0000FACF, 0x0002284A}, {0x0000FAD0, 0x00022844},
-{0x0000FAD1, 0x000233D5}, {0x0000FAD2, 0x00003B9D}, {0x0000FAD3, 0x00004018}, {0x0000FAD4, 0x00004039},
-{0x0000FAD5, 0x00025249}, {0x0000FAD6, 0x00025CD0}, {0x0000FAD7, 0x00027ED3}, {0x0000FAD8, 0x00009F43},
-{0x0000FAD9, 0x00009F8E}, {0x0000FB1D, 0x000005D9}, {0x0000FB1D, 0x000005B4}, {0x0000FB1F, 0x000005F2},
-{0x0000FB1F, 0x000005B7}, {0x0000FB2A, 0x000005E9}, {0x0000FB2A, 0x000005C1}, {0x0000FB2B, 0x000005E9},
-{0x0000FB2B, 0x000005C2}, {0x0000FB2C, 0x000005E9}, {0x0000FB2C, 0x000005BC}, {0x0000FB2C, 0x000005C1},
-{0x0000FB2D, 0x000005E9}, {0x0000FB2D, 0x000005BC}, {0x0000FB2D, 0x000005C2}, {0x0000FB2E, 0x000005D0},
-{0x0000FB2E, 0x000005B7}, {0x0000FB2F, 0x000005D0}, {0x0000FB2F, 0x000005B8}, {0x0000FB30, 0x000005D0},
-{0x0000FB30, 0x000005BC}, {0x0000FB31, 0x000005D1}, {0x0000FB31, 0x000005BC}, {0x0000FB32, 0x000005D2},
-{0x0000FB32, 0x000005BC}, {0x0000FB33, 0x000005D3}, {0x0000FB33, 0x000005BC}, {0x0000FB34, 0x000005D4},
-{0x0000FB34, 0x000005BC}, {0x0000FB35, 0x000005D5}, {0x0000FB35, 0x000005BC}, {0x0000FB36, 0x000005D6},
-{0x0000FB36, 0x000005BC}, {0x0000FB38, 0x000005D8}, {0x0000FB38, 0x000005BC}, {0x0000FB39, 0x000005D9},
-{0x0000FB39, 0x000005BC}, {0x0000FB3A, 0x000005DA}, {0x0000FB3A, 0x000005BC}, {0x0000FB3B, 0x000005DB},
-{0x0000FB3B, 0x000005BC}, {0x0000FB3C, 0x000005DC}, {0x0000FB3C, 0x000005BC}, {0x0000FB3E, 0x000005DE},
-{0x0000FB3E, 0x000005BC}, {0x0000FB40, 0x000005E0}, {0x0000FB40, 0x000005BC}, {0x0000FB41, 0x000005E1},
-{0x0000FB41, 0x000005BC}, {0x0000FB43, 0x000005E3}, {0x0000FB43, 0x000005BC}, {0x0000FB44, 0x000005E4},
-{0x0000FB44, 0x000005BC}, {0x0000FB46, 0x000005E6}, {0x0000FB46, 0x000005BC}, {0x0000FB47, 0x000005E7},
-{0x0000FB47, 0x000005BC}, {0x0000FB48, 0x000005E8}, {0x0000FB48, 0x000005BC}, {0x0000FB49, 0x000005E9},
-{0x0000FB49, 0x000005BC}, {0x0000FB4A, 0x000005EA}, {0x0000FB4A, 0x000005BC}, {0x0000FB4B, 0x000005D5},
-{0x0000FB4B, 0x000005B9}, {0x0000FB4C, 0x000005D1}, {0x0000FB4C, 0x000005BF}, {0x0000FB4D, 0x000005DB},
-{0x0000FB4D, 0x000005BF}, {0x0000FB4E, 0x000005E4}, {0x0000FB4E, 0x000005BF}, {0x0001109A, 0x00011099},
-{0x0001109A, 0x000110BA}, {0x0001109C, 0x0001109B}, {0x0001109C, 0x000110BA}, {0x000110AB, 0x000110A5},
-{0x000110AB, 0x000110BA}, {0x0001112E, 0x00011131}, {0x0001112E, 0x00011127}, {0x0001112F, 0x00011132},
-{0x0001112F, 0x00011127}, {0x0001134B, 0x00011347}, {0x0001134B, 0x0001133E}, {0x0001134C, 0x00011347},
-{0x0001134C, 0x00011357}, {0x000114BB, 0x000114B9}, {0x000114BB, 0x000114BA}, {0x000114BC, 0x000114B9},
-{0x000114BC, 0x000114B0}, {0x000114BE, 0x000114B9}, {0x000114BE, 0x000114BD}, {0x000115BA, 0x000115B8},
-{0x000115BA, 0x000115AF}, {0x000115BB, 0x000115B9}, {0x000115BB, 0x000115AF}, {0x0001D15E, 0x0001D157},
-{0x0001D15E, 0x0001D165}, {0x0001D15F, 0x0001D158}, {0x0001D15F, 0x0001D165}, {0x0001D160, 0x0001D158},
-{0x0001D160, 0x0001D165}, {0x0001D160, 0x0001D16E}, {0x0001D161, 0x0001D158}, {0x0001D161, 0x0001D165},
-{0x0001D161, 0x0001D16F}, {0x0001D162, 0x0001D158}, {0x0001D162, 0x0001D165}, {0x0001D162, 0x0001D170},
-{0x0001D163, 0x0001D158}, {0x0001D163, 0x0001D165}, {0x0001D163, 0x0001D171}, {0x0001D164, 0x0001D158},
-{0x0001D164, 0x0001D165}, {0x0001D164, 0x0001D172}, {0x0001D1BB, 0x0001D1B9}, {0x0001D1BB, 0x0001D165},
-{0x0001D1BC, 0x0001D1BA}, {0x0001D1BC, 0x0001D165}, {0x0001D1BD, 0x0001D1B9}, {0x0001D1BD, 0x0001D165},
-{0x0001D1BD, 0x0001D16E}, {0x0001D1BE, 0x0001D1BA}, {0x0001D1BE, 0x0001D165}, {0x0001D1BE, 0x0001D16E},
-{0x0001D1BF, 0x0001D1B9}, {0x0001D1BF, 0x0001D165}, {0x0001D1BF, 0x0001D16F}, {0x0001D1C0, 0x0001D1BA},
-{0x0001D1C0, 0x0001D165}, {0x0001D1C0, 0x0001D16F}, {0x0002F800, 0x00004E3D}, {0x0002F801, 0x00004E38},
-{0x0002F802, 0x00004E41}, {0x0002F803, 0x00020122}, {0x0002F804, 0x00004F60}, {0x0002F805, 0x00004FAE},
-{0x0002F806, 0x00004FBB}, {0x0002F807, 0x00005002}, {0x0002F808, 0x0000507A}, {0x0002F809, 0x00005099},
-{0x0002F80A, 0x000050E7}, {0x0002F80B, 0x000050CF}, {0x0002F80C, 0x0000349E}, {0x0002F80D, 0x0002063A},
-{0x0002F80E, 0x0000514D}, {0x0002F80F, 0x00005154}, {0x0002F810, 0x00005164}, {0x0002F811, 0x00005177},
-{0x0002F812, 0x0002051C}, {0x0002F813, 0x000034B9}, {0x0002F814, 0x00005167}, {0x0002F815, 0x0000518D},
-{0x0002F816, 0x0002054B}, {0x0002F817, 0x00005197}, {0x0002F818, 0x000051A4}, {0x0002F819, 0x00004ECC},
-{0x0002F81A, 0x000051AC}, {0x0002F81B, 0x000051B5}, {0x0002F81C, 0x000291DF}, {0x0002F81D, 0x000051F5},
-{0x0002F81E, 0x00005203}, {0x0002F81F, 0x000034DF}, {0x0002F820, 0x0000523B}, {0x0002F821, 0x00005246},
-{0x0002F822, 0x00005272}, {0x0002F823, 0x00005277}, {0x0002F824, 0x00003515}, {0x0002F825, 0x000052C7},
-{0x0002F826, 0x000052C9}, {0x0002F827, 0x000052E4}, {0x0002F828, 0x000052FA}, {0x0002F829, 0x00005305},
-{0x0002F82A, 0x00005306}, {0x0002F82B, 0x00005317}, {0x0002F82C, 0x00005349}, {0x0002F82D, 0x00005351},
-{0x0002F82E, 0x0000535A}, {0x0002F82F, 0x00005373}, {0x0002F830, 0x0000537D}, {0x0002F831, 0x0000537F},
-{0x0002F832, 0x0000537F}, {0x0002F833, 0x0000537F}, {0x0002F834, 0x00020A2C}, {0x0002F835, 0x00007070},
-{0x0002F836, 0x000053CA}, {0x0002F837, 0x000053DF}, {0x0002F838, 0x00020B63}, {0x0002F839, 0x000053EB},
-{0x0002F83A, 0x000053F1}, {0x0002F83B, 0x00005406}, {0x0002F83C, 0x0000549E}, {0x0002F83D, 0x00005438},
-{0x0002F83E, 0x00005448}, {0x0002F83F, 0x00005468}, {0x0002F840, 0x000054A2}, {0x0002F841, 0x000054F6},
-{0x0002F842, 0x00005510}, {0x0002F843, 0x00005553}, {0x0002F844, 0x00005563}, {0x0002F845, 0x00005584},
-{0x0002F846, 0x00005584}, {0x0002F847, 0x00005599}, {0x0002F848, 0x000055AB}, {0x0002F849, 0x000055B3},
-{0x0002F84A, 0x000055C2}, {0x0002F84B, 0x00005716}, {0x0002F84C, 0x00005606}, {0x0002F84D, 0x00005717},
-{0x0002F84E, 0x00005651}, {0x0002F84F, 0x00005674}, {0x0002F850, 0x00005207}, {0x0002F851, 0x000058EE},
-{0x0002F852, 0x000057CE}, {0x0002F853, 0x000057F4}, {0x0002F854, 0x0000580D}, {0x0002F855, 0x0000578B},
-{0x0002F856, 0x00005832}, {0x0002F857, 0x00005831}, {0x0002F858, 0x000058AC}, {0x0002F859, 0x000214E4},
-{0x0002F85A, 0x000058F2}, {0x0002F85B, 0x000058F7}, {0x0002F85C, 0x00005906}, {0x0002F85D, 0x0000591A},
-{0x0002F85E, 0x00005922}, {0x0002F85F, 0x00005962}, {0x0002F860, 0x000216A8}, {0x0002F861, 0x000216EA},
-{0x0002F862, 0x000059EC}, {0x0002F863, 0x00005A1B}, {0x0002F864, 0x00005A27}, {0x0002F865, 0x000059D8},
-{0x0002F866, 0x00005A66}, {0x0002F867, 0x000036EE}, {0x0002F868, 0x000036FC}, {0x0002F869, 0x00005B08},
-{0x0002F86A, 0x00005B3E}, {0x0002F86B, 0x00005B3E}, {0x0002F86C, 0x000219C8}, {0x0002F86D, 0x00005BC3},
-{0x0002F86E, 0x00005BD8}, {0x0002F86F, 0x00005BE7}, {0x0002F870, 0x00005BF3}, {0x0002F871, 0x00021B18},
-{0x0002F872, 0x00005BFF}, {0x0002F873, 0x00005C06}, {0x0002F874, 0x00005F53}, {0x0002F875, 0x00005C22},
-{0x0002F876, 0x00003781}, {0x0002F877, 0x00005C60}, {0x0002F878, 0x00005C6E}, {0x0002F879, 0x00005CC0},
-{0x0002F87A, 0x00005C8D}, {0x0002F87B, 0x00021DE4}, {0x0002F87C, 0x00005D43}, {0x0002F87D, 0x00021DE6},
-{0x0002F87E, 0x00005D6E}, {0x0002F87F, 0x00005D6B}, {0x0002F880, 0x00005D7C}, {0x0002F881, 0x00005DE1},
-{0x0002F882, 0x00005DE2}, {0x0002F883, 0x0000382F}, {0x0002F884, 0x00005DFD}, {0x0002F885, 0x00005E28},
-{0x0002F886, 0x00005E3D}, {0x0002F887, 0x00005E69}, {0x0002F888, 0x00003862}, {0x0002F889, 0x00022183},
-{0x0002F88A, 0x0000387C}, {0x0002F88B, 0x00005EB0}, {0x0002F88C, 0x00005EB3}, {0x0002F88D, 0x00005EB6},
-{0x0002F88E, 0x00005ECA}, {0x0002F88F, 0x0002A392}, {0x0002F890, 0x00005EFE}, {0x0002F891, 0x00022331},
-{0x0002F892, 0x00022331}, {0x0002F893, 0x00008201}, {0x0002F894, 0x00005F22}, {0x0002F895, 0x00005F22},
-{0x0002F896, 0x000038C7}, {0x0002F897, 0x000232B8}, {0x0002F898, 0x000261DA}, {0x0002F899, 0x00005F62},
-{0x0002F89A, 0x00005F6B}, {0x0002F89B, 0x000038E3}, {0x0002F89C, 0x00005F9A}, {0x0002F89D, 0x00005FCD},
-{0x0002F89E, 0x00005FD7}, {0x0002F89F, 0x00005FF9}, {0x0002F8A0, 0x00006081}, {0x0002F8A1, 0x0000393A},
-{0x0002F8A2, 0x0000391C}, {0x0002F8A3, 0x00006094}, {0x0002F8A4, 0x000226D4}, {0x0002F8A5, 0x000060C7},
-{0x0002F8A6, 0x00006148}, {0x0002F8A7, 0x0000614C}, {0x0002F8A8, 0x0000614E}, {0x0002F8A9, 0x0000614C},
-{0x0002F8AA, 0x0000617A}, {0x0002F8AB, 0x0000618E}, {0x0002F8AC, 0x000061B2}, {0x0002F8AD, 0x000061A4},
-{0x0002F8AE, 0x000061AF}, {0x0002F8AF, 0x000061DE}, {0x0002F8B0, 0x000061F2}, {0x0002F8B1, 0x000061F6},
-{0x0002F8B2, 0x00006210}, {0x0002F8B3, 0x0000621B}, {0x0002F8B4, 0x0000625D}, {0x0002F8B5, 0x000062B1},
-{0x0002F8B6, 0x000062D4}, {0x0002F8B7, 0x00006350}, {0x0002F8B8, 0x00022B0C}, {0x0002F8B9, 0x0000633D},
-{0x0002F8BA, 0x000062FC}, {0x0002F8BB, 0x00006368}, {0x0002F8BC, 0x00006383}, {0x0002F8BD, 0x000063E4},
-{0x0002F8BE, 0x00022BF1}, {0x0002F8BF, 0x00006422}, {0x0002F8C0, 0x000063C5}, {0x0002F8C1, 0x000063A9},
-{0x0002F8C2, 0x00003A2E}, {0x0002F8C3, 0x00006469}, {0x0002F8C4, 0x0000647E}, {0x0002F8C5, 0x0000649D},
-{0x0002F8C6, 0x00006477}, {0x0002F8C7, 0x00003A6C}, {0x0002F8C8, 0x0000654F}, {0x0002F8C9, 0x0000656C},
-{0x0002F8CA, 0x0002300A}, {0x0002F8CB, 0x000065E3}, {0x0002F8CC, 0x000066F8}, {0x0002F8CD, 0x00006649},
-{0x0002F8CE, 0x00003B19}, {0x0002F8CF, 0x00006691}, {0x0002F8D0, 0x00003B08}, {0x0002F8D1, 0x00003AE4},
-{0x0002F8D2, 0x00005192}, {0x0002F8D3, 0x00005195}, {0x0002F8D4, 0x00006700}, {0x0002F8D5, 0x0000669C},
-{0x0002F8D6, 0x000080AD}, {0x0002F8D7, 0x000043D9}, {0x0002F8D8, 0x00006717}, {0x0002F8D9, 0x0000671B},
-{0x0002F8DA, 0x00006721}, {0x0002F8DB, 0x0000675E}, {0x0002F8DC, 0x00006753}, {0x0002F8DD, 0x000233C3},
-{0x0002F8DE, 0x00003B49}, {0x0002F8DF, 0x000067FA}, {0x0002F8E0, 0x00006785}, {0x0002F8E1, 0x00006852},
-{0x0002F8E2, 0x00006885}, {0x0002F8E3, 0x0002346D}, {0x0002F8E4, 0x0000688E}, {0x0002F8E5, 0x0000681F},
-{0x0002F8E6, 0x00006914}, {0x0002F8E7, 0x00003B9D}, {0x0002F8E8, 0x00006942}, {0x0002F8E9, 0x000069A3},
-{0x0002F8EA, 0x000069EA}, {0x0002F8EB, 0x00006AA8}, {0x0002F8EC, 0x000236A3}, {0x0002F8ED, 0x00006ADB},
-{0x0002F8EE, 0x00003C18}, {0x0002F8EF, 0x00006B21}, {0x0002F8F0, 0x000238A7}, {0x0002F8F1, 0x00006B54},
-{0x0002F8F2, 0x00003C4E}, {0x0002F8F3, 0x00006B72}, {0x0002F8F4, 0x00006B9F}, {0x0002F8F5, 0x00006BBA},
-{0x0002F8F6, 0x00006BBB}, {0x0002F8F7, 0x00023A8D}, {0x0002F8F8, 0x00021D0B}, {0x0002F8F9, 0x00023AFA},
-{0x0002F8FA, 0x00006C4E}, {0x0002F8FB, 0x00023CBC}, {0x0002F8FC, 0x00006CBF}, {0x0002F8FD, 0x00006CCD},
-{0x0002F8FE, 0x00006C67}, {0x0002F8FF, 0x00006D16}, {0x0002F900, 0x00006D3E}, {0x0002F901, 0x00006D77},
-{0x0002F902, 0x00006D41}, {0x0002F903, 0x00006D69}, {0x0002F904, 0x00006D78}, {0x0002F905, 0x00006D85},
-{0x0002F906, 0x00023D1E}, {0x0002F907, 0x00006D34}, {0x0002F908, 0x00006E2F}, {0x0002F909, 0x00006E6E},
-{0x0002F90A, 0x00003D33}, {0x0002F90B, 0x00006ECB}, {0x0002F90C, 0x00006EC7}, {0x0002F90D, 0x00023ED1},
-{0x0002F90E, 0x00006DF9}, {0x0002F90F, 0x00006F6E}, {0x0002F910, 0x00023F5E}, {0x0002F911, 0x00023F8E},
-{0x0002F912, 0x00006FC6}, {0x0002F913, 0x00007039}, {0x0002F914, 0x0000701E}, {0x0002F915, 0x0000701B},
-{0x0002F916, 0x00003D96}, {0x0002F917, 0x0000704A}, {0x0002F918, 0x0000707D}, {0x0002F919, 0x00007077},
-{0x0002F91A, 0x000070AD}, {0x0002F91B, 0x00020525}, {0x0002F91C, 0x00007145}, {0x0002F91D, 0x00024263},
-{0x0002F91E, 0x0000719C}, {0x0002F91F, 0x000243AB}, {0x0002F920, 0x00007228}, {0x0002F921, 0x00007235},
-{0x0002F922, 0x00007250}, {0x0002F923, 0x00024608}, {0x0002F924, 0x00007280}, {0x0002F925, 0x00007295},
-{0x0002F926, 0x00024735}, {0x0002F927, 0x00024814}, {0x0002F928, 0x0000737A}, {0x0002F929, 0x0000738B},
-{0x0002F92A, 0x00003EAC}, {0x0002F92B, 0x000073A5}, {0x0002F92C, 0x00003EB8}, {0x0002F92D, 0x00003EB8},
-{0x0002F92E, 0x00007447}, {0x0002F92F, 0x0000745C}, {0x0002F930, 0x00007471}, {0x0002F931, 0x00007485},
-{0x0002F932, 0x000074CA}, {0x0002F933, 0x00003F1B}, {0x0002F934, 0x00007524}, {0x0002F935, 0x00024C36},
-{0x0002F936, 0x0000753E}, {0x0002F937, 0x00024C92}, {0x0002F938, 0x00007570}, {0x0002F939, 0x0002219F},
-{0x0002F93A, 0x00007610}, {0x0002F93B, 0x00024FA1}, {0x0002F93C, 0x00024FB8}, {0x0002F93D, 0x00025044},
-{0x0002F93E, 0x00003FFC}, {0x0002F93F, 0x00004008}, {0x0002F940, 0x000076F4}, {0x0002F941, 0x000250F3},
-{0x0002F942, 0x000250F2}, {0x0002F943, 0x00025119}, {0x0002F944, 0x00025133}, {0x0002F945, 0x0000771E},
-{0x0002F946, 0x0000771F}, {0x0002F947, 0x0000771F}, {0x0002F948, 0x0000774A}, {0x0002F949, 0x00004039},
-{0x0002F94A, 0x0000778B}, {0x0002F94B, 0x00004046}, {0x0002F94C, 0x00004096}, {0x0002F94D, 0x0002541D},
-{0x0002F94E, 0x0000784E}, {0x0002F94F, 0x0000788C}, {0x0002F950, 0x000078CC}, {0x0002F951, 0x000040E3},
-{0x0002F952, 0x00025626}, {0x0002F953, 0x00007956}, {0x0002F954, 0x0002569A}, {0x0002F955, 0x000256C5},
-{0x0002F956, 0x0000798F}, {0x0002F957, 0x000079EB}, {0x0002F958, 0x0000412F}, {0x0002F959, 0x00007A40},
-{0x0002F95A, 0x00007A4A}, {0x0002F95B, 0x00007A4F}, {0x0002F95C, 0x0002597C}, {0x0002F95D, 0x00025AA7},
-{0x0002F95E, 0x00025AA7}, {0x0002F95F, 0x00007AEE}, {0x0002F960, 0x00004202}, {0x0002F961, 0x00025BAB},
-{0x0002F962, 0x00007BC6}, {0x0002F963, 0x00007BC9}, {0x0002F964, 0x00004227}, {0x0002F965, 0x00025C80},
-{0x0002F966, 0x00007CD2}, {0x0002F967, 0x000042A0}, {0x0002F968, 0x00007CE8}, {0x0002F969, 0x00007CE3},
-{0x0002F96A, 0x00007D00}, {0x0002F96B, 0x00025F86}, {0x0002F96C, 0x00007D63}, {0x0002F96D, 0x00004301},
-{0x0002F96E, 0x00007DC7}, {0x0002F96F, 0x00007E02}, {0x0002F970, 0x00007E45}, {0x0002F971, 0x00004334},
-{0x0002F972, 0x00026228}, {0x0002F973, 0x00026247}, {0x0002F974, 0x00004359}, {0x0002F975, 0x000262D9},
-{0x0002F976, 0x00007F7A}, {0x0002F977, 0x0002633E}, {0x0002F978, 0x00007F95}, {0x0002F979, 0x00007FFA},
-{0x0002F97A, 0x00008005}, {0x0002F97B, 0x000264DA}, {0x0002F97C, 0x00026523}, {0x0002F97D, 0x00008060},
-{0x0002F97E, 0x000265A8}, {0x0002F97F, 0x00008070}, {0x0002F980, 0x0002335F}, {0x0002F981, 0x000043D5},
-{0x0002F982, 0x000080B2}, {0x0002F983, 0x00008103}, {0x0002F984, 0x0000440B}, {0x0002F985, 0x0000813E},
-{0x0002F986, 0x00005AB5}, {0x0002F987, 0x000267A7}, {0x0002F988, 0x000267B5}, {0x0002F989, 0x00023393},
-{0x0002F98A, 0x0002339C}, {0x0002F98B, 0x00008201}, {0x0002F98C, 0x00008204}, {0x0002F98D, 0x00008F9E},
-{0x0002F98E, 0x0000446B}, {0x0002F98F, 0x00008291}, {0x0002F990, 0x0000828B}, {0x0002F991, 0x0000829D},
-{0x0002F992, 0x000052B3}, {0x0002F993, 0x000082B1}, {0x0002F994, 0x000082B3}, {0x0002F995, 0x000082BD},
-{0x0002F996, 0x000082E6}, {0x0002F997, 0x00026B3C}, {0x0002F998, 0x000082E5}, {0x0002F999, 0x0000831D},
-{0x0002F99A, 0x00008363}, {0x0002F99B, 0x000083AD}, {0x0002F99C, 0x00008323}, {0x0002F99D, 0x000083BD},
-{0x0002F99E, 0x000083E7}, {0x0002F99F, 0x00008457}, {0x0002F9A0, 0x00008353}, {0x0002F9A1, 0x000083CA},
-{0x0002F9A2, 0x000083CC}, {0x0002F9A3, 0x000083DC}, {0x0002F9A4, 0x00026C36}, {0x0002F9A5, 0x00026D6B},
-{0x0002F9A6, 0x00026CD5}, {0x0002F9A7, 0x0000452B}, {0x0002F9A8, 0x000084F1}, {0x0002F9A9, 0x000084F3},
-{0x0002F9AA, 0x00008516}, {0x0002F9AB, 0x000273CA}, {0x0002F9AC, 0x00008564}, {0x0002F9AD, 0x00026F2C},
-{0x0002F9AE, 0x0000455D}, {0x0002F9AF, 0x00004561}, {0x0002F9B0, 0x00026FB1}, {0x0002F9B1, 0x000270D2},
-{0x0002F9B2, 0x0000456B}, {0x0002F9B3, 0x00008650}, {0x0002F9B4, 0x0000865C}, {0x0002F9B5, 0x00008667},
-{0x0002F9B6, 0x00008669}, {0x0002F9B7, 0x000086A9}, {0x0002F9B8, 0x00008688}, {0x0002F9B9, 0x0000870E},
-{0x0002F9BA, 0x000086E2}, {0x0002F9BB, 0x00008779}, {0x0002F9BC, 0x00008728}, {0x0002F9BD, 0x0000876B},
-{0x0002F9BE, 0x00008786}, {0x0002F9BF, 0x000045D7}, {0x0002F9C0, 0x000087E1}, {0x0002F9C1, 0x00008801},
-{0x0002F9C2, 0x000045F9}, {0x0002F9C3, 0x00008860}, {0x0002F9C4, 0x00008863}, {0x0002F9C5, 0x00027667},
-{0x0002F9C6, 0x000088D7}, {0x0002F9C7, 0x000088DE}, {0x0002F9C8, 0x00004635}, {0x0002F9C9, 0x000088FA},
-{0x0002F9CA, 0x000034BB}, {0x0002F9CB, 0x000278AE}, {0x0002F9CC, 0x00027966}, {0x0002F9CD, 0x000046BE},
-{0x0002F9CE, 0x000046C7}, {0x0002F9CF, 0x00008AA0}, {0x0002F9D0, 0x00008AED}, {0x0002F9D1, 0x00008B8A},
-{0x0002F9D2, 0x00008C55}, {0x0002F9D3, 0x00027CA8}, {0x0002F9D4, 0x00008CAB}, {0x0002F9D5, 0x00008CC1},
-{0x0002F9D6, 0x00008D1B}, {0x0002F9D7, 0x00008D77}, {0x0002F9D8, 0x00027F2F}, {0x0002F9D9, 0x00020804},
-{0x0002F9DA, 0x00008DCB}, {0x0002F9DB, 0x00008DBC}, {0x0002F9DC, 0x00008DF0}, {0x0002F9DD, 0x000208DE},
-{0x0002F9DE, 0x00008ED4}, {0x0002F9DF, 0x00008F38}, {0x0002F9E0, 0x000285D2}, {0x0002F9E1, 0x000285ED},
-{0x0002F9E2, 0x00009094}, {0x0002F9E3, 0x000090F1}, {0x0002F9E4, 0x00009111}, {0x0002F9E5, 0x0002872E},
-{0x0002F9E6, 0x0000911B}, {0x0002F9E7, 0x00009238}, {0x0002F9E8, 0x000092D7}, {0x0002F9E9, 0x000092D8},
-{0x0002F9EA, 0x0000927C}, {0x0002F9EB, 0x000093F9}, {0x0002F9EC, 0x00009415}, {0x0002F9ED, 0x00028BFA},
-{0x0002F9EE, 0x0000958B}, {0x0002F9EF, 0x00004995}, {0x0002F9F0, 0x000095B7}, {0x0002F9F1, 0x00028D77},
-{0x0002F9F2, 0x000049E6}, {0x0002F9F3, 0x000096C3}, {0x0002F9F4, 0x00005DB2}, {0x0002F9F5, 0x00009723},
-{0x0002F9F6, 0x00029145}, {0x0002F9F7, 0x0002921A}, {0x0002F9F8, 0x00004A6E}, {0x0002F9F9, 0x00004A76},
-{0x0002F9FA, 0x000097E0}, {0x0002F9FB, 0x0002940A}, {0x0002F9FC, 0x00004AB2}, {0x0002F9FD, 0x00029496},
-{0x0002F9FE, 0x0000980B}, {0x0002F9FF, 0x0000980B}, {0x0002FA00, 0x00009829}, {0x0002FA01, 0x000295B6},
-{0x0002FA02, 0x000098E2}, {0x0002FA03, 0x00004B33}, {0x0002FA04, 0x00009929}, {0x0002FA05, 0x000099A7},
-{0x0002FA06, 0x000099C2}, {0x0002FA07, 0x000099FE}, {0x0002FA08, 0x00004BCE}, {0x0002FA09, 0x00029B30},
-{0x0002FA0A, 0x00009B12}, {0x0002FA0B, 0x00009C40}, {0x0002FA0C, 0x00009CFD}, {0x0002FA0D, 0x00004CCE},
-{0x0002FA0E, 0x00004CED}, {0x0002FA0F, 0x00009D67}, {0x0002FA10, 0x0002A0CE}, {0x0002FA11, 0x00004CF8},
-{0x0002FA12, 0x0002A105}, {0x0002FA13, 0x0002A20E}, {0x0002FA14, 0x0002A291}, {0x0002FA15, 0x00009EBB},
-{0x0002FA16, 0x00004D56}, {0x0002FA17, 0x00009EF9}, {0x0002FA18, 0x00009EFE}, {0x0002FA19, 0x00009F05},
-{0x0002FA1A, 0x00009F0F}, {0x0002FA1B, 0x00009F16}, {0x0002FA1D, 0x0002A600},
-};
diff --git a/unicode-data.h b/unicode-data.h
index 3cccf2068..e27fe1770 100644
--- a/unicode-data.h
+++ b/unicode-data.h
@@ -1,17 +1,20 @@
 #pragma once
 
 #include <cstdint>
-#include <map>
-#include <utility>
 #include <vector>
+#include <unordered_map>
+#include <unordered_set>
 
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_number;
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_letter;
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_separator;
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_whitespace;
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_accent_mark;
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_punctuation;
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_symbol;
-extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_control;
-extern const std::multimap<uint32_t, uint32_t>          unicode_map_nfd;
-extern const std::map<char32_t, char32_t>               unicode_map_lowercase;
+struct range_nfd {
+    uint32_t first;
+    uint32_t last;
+    uint32_t nfd;
+};
+
+static const uint32_t MAX_CODEPOINTS = 0x110000;
+
+extern const std::vector<std::pair<uint32_t, uint16_t>> unicode_ranges_flags;
+extern const std::unordered_set<uint32_t> unicode_set_whitespace;
+extern const std::unordered_map<uint32_t, uint32_t> unicode_map_lowercase;
+extern const std::unordered_map<uint32_t, uint32_t> unicode_map_uppercase;
+extern const std::vector<range_nfd> unicode_ranges_nfd;
diff --git a/unicode.cpp b/unicode.cpp
index ca03c49d3..056a4c741 100644
--- a/unicode.cpp
+++ b/unicode.cpp
@@ -1,4 +1,4 @@
-#include "unicode.h"
+#include "unicode.h"
 #include "unicode-data.h"
 
 #include <cassert>
@@ -109,57 +109,49 @@ static uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset)
 //    return result;
 //}
 
-static std::unordered_map<uint32_t, int> unicode_cpt_type_map() {
-    std::unordered_map<uint32_t, int> cpt_types;
-    for (auto p : unicode_ranges_number) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            cpt_types[i] = CODEPOINT_TYPE_NUMBER;
+static std::vector<codepoint_flags> unicode_cpt_flags_array() {
+    std::vector<codepoint_flags> cpt_flags(MAX_CODEPOINTS, codepoint_flags::UNDEFINED);
+
+    assert (unicode_ranges_flags.front().first == 0);
+    assert (unicode_ranges_flags.back().first == MAX_CODEPOINTS);
+    for (size_t i = 1; i < unicode_ranges_flags.size(); ++i) {
+        const auto range_ini = unicode_ranges_flags[i-1];  // codepoint_ini, flags
+        const auto range_end = unicode_ranges_flags[i];    // codepoint_end, flags
+        for (uint32_t cpt = range_ini.first; cpt < range_end.first; ++cpt) {
+            cpt_flags[cpt] = range_ini.second;
         }
     }
-    for (auto p : unicode_ranges_letter) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            cpt_types[i] = CODEPOINT_TYPE_LETTER;
-        }
+
+    for (auto cpt : unicode_set_whitespace) {
+        cpt_flags[cpt].is_whitespace = true;
     }
-    for (auto p : unicode_ranges_separator) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            cpt_types[i] = CODEPOINT_TYPE_SEPARATOR;
-        }
+
+    for (auto p : unicode_map_lowercase) {
+        cpt_flags[p.second].is_lowercase = true;
     }
-    for (auto p : unicode_ranges_accent_mark) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            cpt_types[i] = CODEPOINT_TYPE_ACCENT_MARK;
-        }
+
+    for (auto p : unicode_map_uppercase) {
+        cpt_flags[p.second].is_uppercase = true;
     }
-    for (auto p : unicode_ranges_punctuation) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            cpt_types[i] = CODEPOINT_TYPE_PUNCTUATION;
-        }
+
+    for (auto &range : unicode_ranges_nfd) {  // start, last, nfd
+        cpt_flags[range.nfd].is_nfd = true;
     }
-    for  (auto p : unicode_ranges_symbol) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            cpt_types[i] = CODEPOINT_TYPE_SYMBOL;
-        }
-    }
-    for (auto p : unicode_ranges_control) {
-        for (auto i = p.first; i <= p.second; ++i) {
-            cpt_types[i] = CODEPOINT_TYPE_CONTROL;
-        }
-    }
-    return cpt_types;
+
+    return cpt_flags;
 }
 
 static std::unordered_map<uint8_t, std::string> unicode_byte_to_utf8_map() {
     std::unordered_map<uint8_t, std::string> map;
-    for (int ch = u'!'; ch <= u'~'; ++ch) {
+    for (int ch = 0x21; ch <= 0x7E; ++ch) {  // u'!' to u'~'
         assert(0 <= ch && ch < 256);
         map[ch] = unicode_cpt_to_utf8(ch);
     }
-    for (int ch = u'¡'; ch <= u'¬'; ++ch) {
+    for (int ch = 0xA1; ch <= 0xAC; ++ch) {  // u'¡' to u'¬'
         assert(0 <= ch && ch < 256);
         map[ch] = unicode_cpt_to_utf8(ch);
     }
-    for (int ch = u'®'; ch <= u'ÿ'; ++ch) {
+    for (int ch = 0xAE; ch <= 0xFF; ++ch) {  // u'®' to u'ÿ'
         assert(0 <= ch && ch < 256);
         map[ch] = unicode_cpt_to_utf8(ch);
     }
@@ -175,15 +167,15 @@ static std::unordered_map<uint8_t, std::string> unicode_byte_to_utf8_map() {
 
 static std::unordered_map<std::string, uint8_t> unicode_utf8_to_byte_map() {
     std::unordered_map<std::string, uint8_t> map;
-    for (int ch = u'!'; ch <= u'~'; ++ch) {
+    for (int ch = 0x21; ch <= 0x7E; ++ch) {  // u'!' to u'~'
         assert(0 <= ch && ch < 256);
         map[unicode_cpt_to_utf8(ch)] = ch;
     }
-    for (int ch = u'¡'; ch <= u'¬'; ++ch) {
+    for (int ch = 0xA1; ch <= 0xAC; ++ch) {  // u'¡' to u'¬'
         assert(0 <= ch && ch < 256);
         map[unicode_cpt_to_utf8(ch)] = ch;
     }
-    for (int ch = u'®'; ch <= u'ÿ'; ++ch) {
+    for (int ch = 0xAE; ch <= 0xFF; ++ch) {  // u'®' to u'ÿ'
         assert(0 <= ch && ch < 256);
         map[unicode_cpt_to_utf8(ch)] = ch;
     }
@@ -238,8 +230,9 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string & t
             return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : 0;
         };
 
-        auto _get_cpt_type = [&] (const size_t pos) -> int {
-            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_type(cpts[pos]) : CODEPOINT_TYPE_UNIDENTIFIED;
+        auto _get_flags = [&] (const size_t pos) -> codepoint_flags {
+            static const codepoint_flags undef(codepoint_flags::UNDEFINED);
+            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : undef;
         };
 
         size_t _prev_end = offset_ini;
@@ -261,7 +254,7 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string & t
 
         for (size_t pos = offset_ini; pos < offset_end; /*pos++*/ ) {
             const char32_t cpt = _get_cpt(pos);
-            const int cpt_type = _get_cpt_type(pos);
+            const auto flags = _get_flags(pos);
 
             // regex: 's|'t|'re|'ve|'m|'ll|'d
             if (cpt == '\'' && pos+1 < offset_end) {
@@ -281,39 +274,37 @@ static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string & t
                 }
             }
 
-            char32_t cpt2 = (cpt == ' ' ? _get_cpt(pos+1) : cpt);
-            int cpt2_type = (cpt == ' ' ? _get_cpt_type(pos+1) : cpt_type);
+            auto flags2 = (cpt == ' ' ? _get_flags(pos+1) : flags);
             // regex: <space>?\p{L}+
-            if (cpt2_type == CODEPOINT_TYPE_LETTER) {
+            if (flags2.is_letter) {
                 pos += (cpt == ' ');
-                while (cpt2_type == CODEPOINT_TYPE_LETTER) {
-                    cpt2_type = _get_cpt_type(++pos);
+                while (flags2.is_letter) {
+                    flags2 = _get_flags(++pos);
                 }
                 _add_token(pos);
                 continue;
             }
             // regex: <space>?\p{N}+
-            if (cpt2_type == CODEPOINT_TYPE_NUMBER) {
+            if (flags2.is_number) {
                 pos += (cpt == ' ');
-                while (cpt2_type == CODEPOINT_TYPE_NUMBER) {
-                    cpt2_type = _get_cpt_type(++pos);
+                while (flags2.is_number) {
+                    flags2 = _get_flags(++pos);
                 }
                 _add_token(pos);
                 continue;
             }
             // regex: <space>?[^\s\p{L}\p{N}]+
-            if (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) {
+            if (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
                 pos += (cpt == ' ');
-                while (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) {
-                    cpt2_type = _get_cpt_type(++pos);
-                    cpt2 = _get_cpt(pos);
+                while (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
+                    flags2 = _get_flags(++pos);
                 }
                 _add_token(pos);
                 continue;
             }
 
             size_t num_whitespaces = 0;
-            while (unicode_cpt_is_whitespace(_get_cpt(pos+num_whitespaces))) {
+            while (_get_flags(pos+num_whitespaces).is_whitespace) {
                 num_whitespaces++;
             }
 
@@ -357,8 +348,9 @@ static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string &
             return (offset_ini <= pos && pos < offset_end) ? cpts[pos] : 0;
         };
 
-        auto _get_cpt_type = [&] (const size_t pos) -> int {
-            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_type(cpts[pos]) : CODEPOINT_TYPE_UNIDENTIFIED;
+        auto _get_flags = [&] (const size_t pos) -> codepoint_flags {
+            static const codepoint_flags undef(codepoint_flags::UNDEFINED);
+            return (offset_ini <= pos && pos < offset_end) ? unicode_cpt_flags(cpts[pos]) : undef;
         };
 
         size_t _prev_end = offset_ini;
@@ -380,7 +372,7 @@ static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string &
 
         for (size_t pos = offset_ini; pos < offset_end; /*pos++*/ ) {
             const char32_t cpt = _get_cpt(pos);
-            const int cpt_type = _get_cpt_type(pos);
+            const auto flags = _get_flags(pos);
 
             // regex: (?i:'s|'t|'re|'ve|'m|'ll|'d) // case insensitive
             if (cpt == '\'' && pos+1 < offset_end) {
@@ -401,10 +393,10 @@ static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string &
             }
 
             // regex: [^\r\n\p{L}\p{N}]?\p{L}+  //####FIXME: the first \p{L} is correct?
-            if (cpt != '\r' && cpt != '\n' && /*cpt_type != CODEPOINT_TYPE_LETTER &&*/ cpt_type != CODEPOINT_TYPE_NUMBER) {
-                if (cpt_type == CODEPOINT_TYPE_LETTER || _get_cpt_type(pos+1) == CODEPOINT_TYPE_LETTER) {  // one or more letters
+            if (!(cpt == '\r' || cpt == '\n' || /*flags.is_letter |*/ flags.is_number)) {
+                if (flags.is_letter || _get_flags(pos+1).is_letter) {  // one or more letters
                     pos++;
-                    while (_get_cpt_type(pos) == CODEPOINT_TYPE_LETTER) {
+                    while (_get_flags(pos).is_letter) {
                         pos++;
                     }
                     _add_token(pos);
@@ -413,9 +405,9 @@ static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string &
             }
 
             // regex: \p{N}{1,3}
-            if (cpt_type == CODEPOINT_TYPE_NUMBER) {
+            if (flags.is_number) {
                 size_t ini = pos;
-                while (_get_cpt_type(pos) == CODEPOINT_TYPE_NUMBER) {
+                while (_get_flags(pos).is_number) {
                     if (++pos - ini >= 3 ) {
                         _add_token(pos);
                         ini = pos;
@@ -426,14 +418,13 @@ static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string &
             }
 
             // regex: <space>?[^\s\p{L}\p{N}]+[\r\n]*
-            char32_t cpt2 = (cpt == ' ' ? _get_cpt(pos+1) : cpt);
-            int cpt2_type = (cpt == ' ' ? _get_cpt_type(pos+1) : cpt_type);
-            if (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) {
+            auto flags2 = (cpt == ' ' ? _get_flags(pos+1) : flags);
+            if (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
                 pos += (cpt == ' ');
-                while (!unicode_cpt_is_whitespace(cpt2) && cpt2_type != CODEPOINT_TYPE_LETTER && cpt2_type != CODEPOINT_TYPE_NUMBER && cpt2_type != CODEPOINT_TYPE_UNIDENTIFIED) {
-                    cpt2_type = _get_cpt_type(++pos);
-                    cpt2 = _get_cpt(pos);
+                while (!(flags2.is_whitespace || flags2.is_letter || flags2.is_number || flags2.is_undefined)) {
+                    flags2 = _get_flags(++pos);
                 }
+                char32_t cpt2 = _get_cpt(pos);
                 while (cpt2 == '\r' || cpt2 == '\n') {
                     cpt2 = _get_cpt(++pos);
                 }
@@ -443,7 +434,7 @@ static std::vector<size_t> unicode_regex_split_custom_llama3(const std::string &
 
             size_t num_whitespaces = 0;
             size_t last_end_r_or_n = 0;
-            while (unicode_cpt_is_whitespace(_get_cpt(pos+num_whitespaces))) {
+            while (_get_flags(pos+num_whitespaces).is_whitespace) {
                 char32_t cpt2 = _get_cpt(pos+num_whitespaces);
                 if (cpt2 == '\r' || cpt2 == '\n') {
                     last_end_r_or_n = pos + num_whitespaces + 1;
@@ -589,15 +580,14 @@ std::string unicode_cpt_to_utf8(uint32_t cp) {
 }
 
 std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t> & cpts) {
-    std::vector<uint32_t> result;
-    result.reserve(cpts.size());
+    auto comp = [] (const uint32_t cpt, const range_nfd & range) {
+        return cpt < range.first;
+    };
+    std::vector<uint32_t> result(cpts.size());
     for (size_t i = 0; i < cpts.size(); ++i) {
-        auto it = unicode_map_nfd.find(cpts[i]);
-        if (it == unicode_map_nfd.end()) {
-            result.push_back(cpts[i]);
-        } else {
-            result.push_back(it->second);
-        }
+        const uint32_t cpt = cpts[i];
+        auto it = std::upper_bound(unicode_ranges_nfd.cbegin(), unicode_ranges_nfd.cend(), cpt, comp) - 1;
+        result[i] = (it->first <= cpt && cpt <= it->last) ? it->nfd : cpt;
     }
     return result;
 }
@@ -611,31 +601,19 @@ std::vector<uint32_t> unicode_cpts_from_utf8(const std::string & utf8) {
     return result;
 }
 
-int unicode_cpt_type(uint32_t cp) {
-    static std::unordered_map<uint32_t, int> cpt_types = unicode_cpt_type_map();
-    const auto it = cpt_types.find(cp);
-    return it == cpt_types.end() ? CODEPOINT_TYPE_UNIDENTIFIED : it->second;
+codepoint_flags unicode_cpt_flags(const uint32_t cp) {
+    static const codepoint_flags undef(codepoint_flags::UNDEFINED);
+    static const auto cpt_flags = unicode_cpt_flags_array();
+    return cp < cpt_flags.size() ? cpt_flags[cp] : undef;
 }
 
-int unicode_cpt_type(const std::string & utf8) {
-    if (utf8.length() == 0) {
-        return CODEPOINT_TYPE_UNIDENTIFIED;
+codepoint_flags unicode_cpt_flags(const std::string & utf8) {
+    static const codepoint_flags undef(codepoint_flags::UNDEFINED);
+    if (utf8.empty()) {
+        return undef;  // undefined
     }
     size_t offset = 0;
-    return unicode_cpt_type(unicode_cpt_from_utf8(utf8, offset));
-}
-
-bool unicode_cpt_is_whitespace(uint32_t cp) {
-    static const std::unordered_set<uint32_t> is_whitespace = [] {
-        std::unordered_set<uint32_t> is_whitespace;
-        for (auto p : unicode_ranges_whitespace) {
-            for (auto i = p.first; i <= p.second; ++i) {
-                is_whitespace.insert(i);
-            }
-        }
-        return is_whitespace;
-    }();
-    return (bool)is_whitespace.count(cp);
+    return unicode_cpt_flags(unicode_cpt_from_utf8(utf8, offset));
 }
 
 std::string unicode_byte_to_utf8(uint8_t byte) {
@@ -656,21 +634,21 @@ char32_t unicode_tolower(char32_t cp) {
 std::vector<std::string> unicode_regex_split(const std::string & text, const std::vector<std::string> & regex_exprs) {
     // unicode categories
     static const std::map<std::string, int> k_ucat_enum = {
-        { "\\p{N}", CODEPOINT_TYPE_NUMBER },
-        { "\\p{L}", CODEPOINT_TYPE_LETTER },
-        { "\\p{P}", CODEPOINT_TYPE_PUNCTUATION },
+        { "\\p{N}", codepoint_flags::NUMBER },
+        { "\\p{L}", codepoint_flags::LETTER },
+        { "\\p{P}", codepoint_flags::PUNCTUATION },
     };
 
     static const std::map<int, int> k_ucat_cpt = {
-        { CODEPOINT_TYPE_NUMBER,        0xD1 },
-        { CODEPOINT_TYPE_LETTER,        0xD2 },
-        { CODEPOINT_TYPE_PUNCTUATION,   0xD3 },
+        { codepoint_flags::NUMBER,        0xD1 },
+        { codepoint_flags::LETTER,        0xD2 },
+        { codepoint_flags::PUNCTUATION,   0xD3 },
     };
 
     static const std::map<int, std::string> k_ucat_map = {
-        { CODEPOINT_TYPE_NUMBER,        "\x30-\x39" }, // 0-9
-        { CODEPOINT_TYPE_LETTER,        "\x41-\x5A\x61-\x7A" }, // A-Za-z
-        { CODEPOINT_TYPE_PUNCTUATION,   "\x21-\x23\x25-\x2A\x2C-\x2F\x3A-\x3B\x3F-\x40\\\x5B-\\\x5D\x5F\\\x7B\\\x7D" }, // !-#%-*,-/:-;?-@\[-\]_\{\}
+        { codepoint_flags::NUMBER,        "\x30-\x39" }, // 0-9
+        { codepoint_flags::LETTER,        "\x41-\x5A\x61-\x7A" }, // A-Za-z
+        { codepoint_flags::PUNCTUATION,   "\x21-\x23\x25-\x2A\x2C-\x2F\x3A-\x3B\x3F-\x40\\\x5B-\\\x5D\x5F\\\x7B\\\x7D" }, // !-#%-*,-/:-;?-@\[-\]_\{\}
     };
 
     // compute collapsed codepoints only if needed by at least one regex
@@ -701,10 +679,10 @@ std::vector<std::string> unicode_regex_split(const std::string & text, const std
                 continue;
             }
 
-            const int cpt_type = unicode_cpt_type(cpts[i]);
+            const int cpt_flag = unicode_cpt_flags(cpts[i]).category_flag();
 
-            if (k_ucat_cpt.find(cpt_type) != k_ucat_cpt.end()) {
-                text_collapsed[i] = k_ucat_cpt.at(cpt_type);
+            if (k_ucat_cpt.find(cpt_flag) != k_ucat_cpt.end()) {
+                text_collapsed[i] = k_ucat_cpt.at(cpt_flag);
             } else {
                 text_collapsed[i] = (char) 0xD0; // fallback
             }
diff --git a/unicode.h b/unicode.h
index d6a14d470..7513be4ad 100644
--- a/unicode.h
+++ b/unicode.h
@@ -4,24 +4,56 @@
 #include <string>
 #include <vector>
 
-#define CODEPOINT_TYPE_UNIDENTIFIED 0
-#define CODEPOINT_TYPE_NUMBER       1
-#define CODEPOINT_TYPE_LETTER       2
-#define CODEPOINT_TYPE_SEPARATOR    3
-#define CODEPOINT_TYPE_ACCENT_MARK  4
-#define CODEPOINT_TYPE_PUNCTUATION  5
-#define CODEPOINT_TYPE_SYMBOL       6
-#define CODEPOINT_TYPE_CONTROL      7
+struct codepoint_flags {
+    enum {
+        UNDEFINED       = 0x0001,
+        NUMBER          = 0x0002,  // regex: \p{N}
+        LETTER          = 0x0004,  // regex: \p{L}
+        SEPARATOR       = 0x0008,  // regex: \p{Z}
+        ACCENT_MARK     = 0x0010,  // regex: \p{M}
+        PUNCTUATION     = 0x0020,  // regex: \p{P}
+        SYMBOL          = 0x0040,  // regex: \p{S}
+        CONTROL         = 0x0080,  // regex: \p{C}
+        MASK_CATEGORIES = 0x00FF,
+    };
+
+    // codepoint type
+    uint16_t is_undefined   : 1;
+    uint16_t is_number      : 1;  // regex: \p{N}
+    uint16_t is_letter      : 1;  // regex: \p{L}
+    uint16_t is_separator   : 1;  // regex: \p{Z}
+    uint16_t is_accent_mark : 1;  // regex: \p{M}
+    uint16_t is_punctuation : 1;  // regex: \p{P}
+    uint16_t is_symbol      : 1;  // regex: \p{S}
+    uint16_t is_control     : 1;  // regex: \p{C}
+    // helper flags
+    uint16_t is_whitespace  : 1;  // regex: \s
+    uint16_t is_lowercase   : 1;
+    uint16_t is_uppercase   : 1;
+    uint16_t is_nfd         : 1;
+
+    // decode from uint16
+    inline codepoint_flags(const uint16_t flags=0) {
+        *reinterpret_cast<uint16_t*>(this) = flags;
+    }
+
+    inline uint16_t as_uint() const {
+        return *reinterpret_cast<const uint16_t*>(this);
+    }
+
+    inline uint16_t category_flag() const {
+        return this->as_uint() & MASK_CATEGORIES;
+    }
+};
+
 
 std::string unicode_cpt_to_utf8(uint32_t cp);
 std::vector<uint32_t> unicode_cpts_from_utf8(const std::string & utf8);
 
 std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t> & cpts);
 
-int unicode_cpt_type(uint32_t cp);
-int unicode_cpt_type(const std::string & utf8);
-
-bool unicode_cpt_is_whitespace(uint32_t cp);
+codepoint_flags unicode_cpt_flags(const uint32_t cp);
+codepoint_flags unicode_cpt_flags(const std::string & utf8);
 
 std::string unicode_byte_to_utf8(uint8_t byte);
 uint8_t unicode_utf8_to_byte(const std::string & utf8);