diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 228b68e14..49a328ff5 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -1527,9 +1527,9 @@ class DbrxModel(Model):
             # But llama.cpp moe graph works differently
             # AND the dimensions in ggml are typically in the reverse order of the pytorch dimensions
             # so (n_expert, n_ff, n_embd) in pytorch is {n_embd, n_ff, n_expert} in ggml_tensor
-            exp_tensor_names = {"ffn.experts.mlp.v1": None,       # LLM_TENSOR_FFN_GATE_EXPS ggml_tensor->ne{n_embd, n_ff,   n_expert}
+            exp_tensor_names = {"ffn.experts.mlp.w1": None,       # LLM_TENSOR_FFN_GATE_EXPS ggml_tensor->ne{n_embd, n_ff,   n_expert}
                                 "ffn.experts.mlp.w2": (0, 2, 1),  # LLM_TENSOR_FFN_DOWN_EXPS ggml_tensor->ne{n_ff,   n_embd, n_expert}
-                                "ffn.experts.mlp.w1": None}       # LLM_TENSOR_FFN_UP_EXPS   ggml_tensor->ne{n_embd, n_ff,   n_expert}
+                                "ffn.experts.mlp.v1": None}       # LLM_TENSOR_FFN_UP_EXPS   ggml_tensor->ne{n_embd, n_ff,   n_expert}
             experts = False
             for exp_tensor_name in exp_tensor_names.keys():
                 if name.find(exp_tensor_name) != -1 and name.find(".weight") == -1:
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 510a273c8..5d120a10f 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -238,7 +238,7 @@ class TensorNameMap:
         MODEL_TENSOR.FFN_UP_EXP: (
             "layers.{bid}.feed_forward.experts.w3",                 # mixtral (merged)
             "transformer.decoder_layer.{bid}.moe.linear_v",         # Grok (merged)
-            "transformer.blocks.{bid}.ffn.experts.mlp.w1",          # dbrx
+            "transformer.blocks.{bid}.ffn.experts.mlp.v1",          # dbrx
         ),
 
         # AWQ-activation gate
@@ -259,7 +259,7 @@ class TensorNameMap:
         MODEL_TENSOR.FFN_GATE_EXP: (
             "layers.{bid}.feed_forward.experts.w1",         # mixtral (merged)
             "transformer.decoder_layer.{bid}.moe.linear",   # Grok (merged)
-            "transformer.blocks.{bid}.ffn.experts.mlp.v1",  # dbrx
+            "transformer.blocks.{bid}.ffn.experts.mlp.w1",  # dbrx
         ),
 
         # Feed-forward down