diff --git a/tests/v1/e2e/general/test_async_scheduling_accuracy.py b/tests/v1/e2e/general/test_async_scheduling_accuracy.py
index 3ffcaefdc3..249f2c5ef7 100644
--- a/tests/v1/e2e/general/test_async_scheduling_accuracy.py
+++ b/tests/v1/e2e/general/test_async_scheduling_accuracy.py
@@ -12,6 +12,7 @@ from typing import Any
 import pytest
 import torch
 
+import vllm.envs as envs
 from tests.conftest import HfRunner, VllmRunner
 from tests.utils import (
     large_gpu_mark,
@@ -168,9 +169,16 @@ def test_with_eagle3_spec_decoding(
     reason=("XPU matmul/attention kernels are not batch-invariant"),
 )
 def test_with_ngram_gpu_spec_decoding(
-    vllm_runner: type[VllmRunner], hf_runner: type[HfRunner]
+    vllm_runner: type[VllmRunner],
+    hf_runner: type[HfRunner],
+    monkeypatch: pytest.MonkeyPatch,
 ):
     """Check ngram accuracy and acceptance across scheduling configurations."""
+    if current_platform.is_rocm():
+        # hipBLASLt picks GEMM solutions by batch shape, so sync and async runs
+        # can flip near-tie greedy tokens and shift ngram acceptance.
+        monkeypatch.setenv("VLLM_BATCH_INVARIANT", "1")
+        monkeypatch.setattr(envs, "VLLM_BATCH_INVARIANT", True)
     ngram_gpu_config = {
         "method": "ngram_gpu",
         "num_speculative_tokens": 3,