diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index d351a56d1..3e1a676c0 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -375,8 +375,7 @@ class MODEL_TENSOR(IntEnum):
     ENC_FFN_UP           = auto()
     ENC_OUTPUT_NORM      = auto()
     # vision
-    V_MMPROJ_A           = auto()
-    V_MMPROJ_B           = auto()
+    V_MMPROJ             = auto()
     V_ENC_EMBD_CLS       = auto()
     V_ENC_EMBD_PATCH     = auto()
     V_ENC_EMBD_POS       = auto()
@@ -552,8 +551,7 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
     MODEL_TENSOR.ENC_FFN_UP:                "enc.blk.{bid}.ffn_up",
     MODEL_TENSOR.ENC_OUTPUT_NORM:           "enc.output_norm",
     # vision
-    MODEL_TENSOR.V_MMPROJ_A:                "v.mmproj_a",
-    MODEL_TENSOR.V_MMPROJ_B:                "v.mmproj_b",
+    MODEL_TENSOR.V_MMPROJ:                  "v.mmproj_{bid}",
     MODEL_TENSOR.V_ENC_EMBD_CLS:            "v.enc.embd.cls",
     MODEL_TENSOR.V_ENC_EMBD_PATCH:          "v.enc.embd.patch",
     MODEL_TENSOR.V_ENC_EMBD_POS:            "v.enc.embd.pos",
@@ -1343,8 +1341,7 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
         MODEL_TENSOR.FFN_UP,
     ],
     MODEL_ARCH.LLAVA_VISION: [
-        MODEL_TENSOR.V_MMPROJ_A,
-        MODEL_TENSOR.V_MMPROJ_B,
+        MODEL_TENSOR.V_MMPROJ,
         MODEL_TENSOR.V_ENC_EMBD_CLS,
         MODEL_TENSOR.V_ENC_EMBD_PATCH,
         MODEL_TENSOR.V_ENC_EMBD_POS,
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 4e73706a0..5ae4d65c7 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -680,12 +680,12 @@ class TensorNameMap:
             "encoder.final_layer_norm", # t5
         ),
 
-        MODEL_TENSOR.V_MMPROJ_A: (
-            "multi_modal_projector.linear_1",
+        MODEL_TENSOR.V_MMPROJ: (
+            "multi_modal_projector.linear_{bid}",
         ),
 
-        MODEL_TENSOR.V_MMPROJ_B: (
-            "multi_modal_projector.linear_2",
+        MODEL_TENSOR.V_MMPROJ: (
+            "multi_modal_projector.linear_{bid}",
         ),
 
         MODEL_TENSOR.V_ENC_EMBD_CLS: (
diff --git a/src/llama.cpp b/src/llama.cpp
index c4f1c1d76..0dd60cd81 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -658,8 +658,7 @@ enum llm_tensor {
 };
 
 enum vision_tensor {
-    VISION_TENSOR_MMPROJ_A,
-    VISION_TENSOR_MMPROJ_B,
+    VISION_TENSOR_MMPROJ,
     VISION_TENSOR_ENC_EMBD_CLS,
     VISION_TENSOR_ENC_EMBD_PATCH,
     VISION_TENSOR_ENC_EMBD_POS,
@@ -1601,8 +1600,7 @@ static const std::map<vision_arch, std::map<vision_tensor, std::string>> VISION_
     {
         VISION_ARCH_LLAVA,
         {
-            { VISION_TENSOR_MMPROJ_A,                "v.mmproj_a"                  },
-            { VISION_TENSOR_MMPROJ_B,                "v.mmproj_b"                  },
+            { VISION_TENSOR_MMPROJ,                  "v.mmproj"                    },
             { VISION_TENSOR_ENC_EMBD_CLS,            "v.enc.embd.cls"              },
             { VISION_TENSOR_ENC_EMBD_PATCH,          "v.enc.embd.patch"            },
             { VISION_TENSOR_ENC_EMBD_POS,            "v.enc.embd.pos"              },
@@ -8992,10 +8990,10 @@ static bool llm_load_tensors(
         switch (vparams.arch) {
             case VISION_ARCH_LLAVA:
                 {
-                    model.clip.mm_a_w = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ_A, "weight"), {n_embd, n_ff});
-                    model.clip.mm_a_b = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ_A, "bias"  ), {n_ff});
-                    model.clip.mm_b_w = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ_B, "weight"), {n_ff,   n_ff});
-                    model.clip.mm_b_b = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ_B, "bias"  ), {n_ff});
+                    model.clip.mm_a_w = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ, "weight", 1), {n_embd, n_ff});
+                    model.clip.mm_a_b = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ, "bias"  , 1), {n_ff});
+                    model.clip.mm_b_w = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ, "weight", 2), {n_ff,   n_ff});
+                    model.clip.mm_b_b = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_MMPROJ, "bias"  , 2), {n_ff});
 
                     model.clip.class_embedding     = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_ENC_EMBD_CLS            ), {n_embd});
                     model.clip.patch_embeddings    = ml.create_tensor(ctx_vision, tn(VISION_TENSOR_ENC_EMBD_PATCH, "weight"), {patch_size, patch_size, n_channel, n_embd});