diff --git a/vllm/model_executor/layers/fused_moe/fused_moe.py b/vllm/model_executor/layers/fused_moe/fused_moe.py
index f988e91c2478..5240f79be5cd 100644
--- a/vllm/model_executor/layers/fused_moe/fused_moe.py
+++ b/vllm/model_executor/layers/fused_moe/fused_moe.py
@@ -98,19 +98,19 @@ def fused_moe_kernel_gptq_awq(
     # moving by 1 element in a particular dimension. E.g. `stride_am` is
     # how much to increase `a_ptr` by to get the element one row down
     # (A has M rows).
-    stride_am: tl.int64,
-    stride_ak: tl.int64,
-    stride_be: tl.int64,
-    stride_bk: tl.int64,
-    stride_bn: tl.int64,
-    stride_cm: tl.int64,
-    stride_cn: tl.int64,
-    stride_bse: tl.int64,
-    stride_bsk: tl.int64,
-    stride_bsn: tl.int64,
-    stride_bze: tl.int64,
-    stride_bzk: tl.int64,
-    stride_bzn: tl.int64,
+    stride_am,
+    stride_ak,
+    stride_be,
+    stride_bk,
+    stride_bn,
+    stride_cm,
+    stride_cn,
+    stride_bse,
+    stride_bsk,
+    stride_bsn,
+    stride_bze,
+    stride_bzk,
+    stride_bzn,
     block_k_diviable: tl.constexpr,
     group_size: tl.constexpr,
     # Meta-parameters
@@ -332,20 +332,20 @@ def fused_moe_kernel(
     # moving by 1 element in a particular dimension. E.g. `stride_am` is
     # how much to increase `a_ptr` by to get the element one row down
     # (A has M rows).
-    stride_am: tl.int64,
-    stride_ak: tl.int64,
-    stride_be: tl.int64,
-    stride_bk: tl.int64,
-    stride_bn: tl.int64,
-    stride_cm: tl.int64,
-    stride_cn: tl.int64,
-    stride_asm: tl.int64,
-    stride_ask: tl.int64,
-    stride_bse: tl.int64,
-    stride_bsk: tl.int64,
-    stride_bsn: tl.int64,
-    stride_bbe: tl.int64,  # bias expert stride
-    stride_bbn: tl.int64,  # bias N stride
+    stride_am,
+    stride_ak,
+    stride_be,
+    stride_bk,
+    stride_bn,
+    stride_cm,
+    stride_cn,
+    stride_asm,
+    stride_ask,
+    stride_bse,
+    stride_bsk,
+    stride_bsn,
+    stride_bbe,  # bias expert stride
+    stride_bbn,  # bias N stride
     # Block size for block-wise quantization
     group_n: tl.constexpr,
     group_k: tl.constexpr,