diff --git a/vllm/envs.py b/vllm/envs.py
index 9cdb7ea974b8..078e5c38f0f4 100755
--- a/vllm/envs.py
+++ b/vllm/envs.py
@@ -113,6 +113,7 @@
     VLLM_ROCM_USE_AITER_FP8BMM: bool = True
     VLLM_ROCM_USE_AITER_UNIFIED_ATTENTION: bool = False
     VLLM_ROCM_USE_AITER_FUSION_SHARED_EXPERTS: bool = True
+    VLLM_ROCM_USE_AITER_TRITON_GEMM: bool = True
     VLLM_ROCM_USE_SKINNY_GEMM: bool = True
     VLLM_ROCM_FP8_PADDING: bool = True
     VLLM_ROCM_MOE_PADDING: bool = True
@@ -944,6 +945,11 @@ def get_vllm_port() -> int | None:
         os.getenv("VLLM_ROCM_USE_AITER_FUSION_SHARED_EXPERTS", "True").lower()
         in ("true", "1")
     ),
+    # Whether to use aiter triton kernels for gemm ops.
+    # By default is enabled.
+    "VLLM_ROCM_USE_AITER_TRITON_GEMM": lambda: (
+        os.getenv("VLLM_ROCM_USE_AITER_TRITON_GEMM", "True").lower() in ("true", "1")
+    ),
     # use rocm skinny gemms
     "VLLM_ROCM_USE_SKINNY_GEMM": lambda: (
         os.getenv("VLLM_ROCM_USE_SKINNY_GEMM", "True").lower() in ("true", "1")
@@ -1586,6 +1592,7 @@ def compute_hash() -> str:
         "VLLM_ROCM_USE_TRITON_ROPE",
         "VLLM_ROCM_USE_AITER_FP8BMM",
         "VLLM_ROCM_USE_AITER_UNIFIED_ATTENTION",
+        "VLLM_ROCM_USE_AITER_TRITON_GEMM",
         "VLLM_ROCM_USE_SKINNY_GEMM",
         "VLLM_ROCM_FP8_PADDING",
         "VLLM_ROCM_MOE_PADDING",
diff --git a/vllm/model_executor/layers/utils.py b/vllm/model_executor/layers/utils.py
index 3d90c9513683..b17bdd0b7207 100644
--- a/vllm/model_executor/layers/utils.py
+++ b/vllm/model_executor/layers/utils.py
@@ -106,6 +106,7 @@ def default_unquantized_gemm(
 def use_aiter_triton_gemm(n, m, k, dtype):
     if (
         envs.VLLM_ROCM_USE_AITER == 0
+        or envs.VLLM_ROCM_USE_AITER_TRITON_GEMM == 0
         # MI300's - fp8nuz=True
         or current_platform.is_fp8_fnuz()
         or dtype not in [torch.float16, torch.bfloat16]