diff --git a/tests/compile/distributed/test_fusions_e2e.py b/tests/compile/distributed/test_fusions_e2e.py
index 996da4a29..b9913734d 100644
--- a/tests/compile/distributed/test_fusions_e2e.py
+++ b/tests/compile/distributed/test_fusions_e2e.py
@@ -290,6 +290,9 @@ def test_rms_group_quant(
     # Force spawn as it is more general.
     monkeypatch.setenv("VLLM_WORKER_MULTIPROC_METHOD", "spawn")
 
+    # TODO: remove this after fusion is fixed
+    monkeypatch.setenv("VLLM_USE_DEEP_GEMM_TMA_ALIGNED_SCALES", "0")
+
     model_kwargs["attention_config"] = {"backend": backend.name}
 
     compilation_config = CompilationConfig(
diff --git a/vllm/envs.py b/vllm/envs.py
index e28f9c431..97351902b 100755
--- a/vllm/envs.py
+++ b/vllm/envs.py
@@ -162,6 +162,7 @@ if TYPE_CHECKING:
     VLLM_USE_DEEP_GEMM: bool = True
     VLLM_MOE_USE_DEEP_GEMM: bool = True
     VLLM_USE_DEEP_GEMM_E8M0: bool = True
+    VLLM_USE_DEEP_GEMM_TMA_ALIGNED_SCALES: bool = True
     VLLM_DEEP_GEMM_WARMUP: Literal[
         "skip",
         "full",
@@ -1201,6 +1202,10 @@ environment_variables: dict[str, Callable[[], Any]] = {
     "VLLM_USE_DEEP_GEMM_E8M0": lambda: bool(
         int(os.getenv("VLLM_USE_DEEP_GEMM_E8M0", "1"))
     ),
+    # Whether to create TMA-aligned scale tensor when DeepGEMM is used.
+    "VLLM_USE_DEEP_GEMM_TMA_ALIGNED_SCALES": lambda: bool(
+        int(os.getenv("VLLM_USE_DEEP_GEMM_TMA_ALIGNED_SCALES", "1"))
+    ),
     # DeepGemm JITs the kernels on-demand. The warmup attempts to make DeepGemm
     # JIT all the required kernels before model execution so there is no
     # JIT'ing in the hot-path. However, this warmup increases the engine
diff --git a/vllm/model_executor/layers/quantization/utils/fp8_utils.py b/vllm/model_executor/layers/quantization/utils/fp8_utils.py
index 638f0f71a..3f1b14901 100644
--- a/vllm/model_executor/layers/quantization/utils/fp8_utils.py
+++ b/vllm/model_executor/layers/quantization/utils/fp8_utils.py
@@ -379,7 +379,7 @@ class W8A8BlockFp8LinearOp:
                 False,
                 self.act_quant_group_shape,
                 column_major_scales=True,
-                tma_aligned_scales=True,
+                tma_aligned_scales=envs.VLLM_USE_DEEP_GEMM_TMA_ALIGNED_SCALES,
                 use_ue8m0=self.use_deep_gemm_e8m0,
             )
             if self.is_deep_gemm_supported