diff --git a/tests/quantization/test_quark.py b/tests/quantization/test_quark.py
index 9622944670..1d531fcfbf 100644
--- a/tests/quantization/test_quark.py
+++ b/tests/quantization/test_quark.py
@@ -23,6 +23,7 @@ from vllm.model_executor.layers.quantization.quark.quark import (  # noqa: E501
     QuarkW8A8Int8,
 )
 from vllm.model_executor.layers.quantization.quark.quark_moe import (  # noqa: E501
+    QuarkW4A8Fp8MoEMethod,
     QuarkW8A8Int8MoEMethod,
 )
 from vllm.model_executor.layers.quantization.utils.quant_utils import (
@@ -31,9 +32,12 @@ from vllm.model_executor.layers.quantization.utils.quant_utils import (
 from vllm.platforms import current_platform
 
 if current_platform.is_rocm():
-    from vllm.platforms.rocm import on_gfx950
+    from vllm.platforms.rocm import on_gfx942, on_gfx950
 else:
 
+    def on_gfx942() -> bool:
+        return False
+
     def on_gfx950() -> bool:
         return False
 
@@ -170,6 +174,38 @@ def test_quark_int8_w8a8_moe(vllm_runner, tp):
         assert output
 
 
+@pytest.mark.skipif(
+    not (on_gfx950() or on_gfx942()),
+    reason="Quark W4A8 (INT4-FP8) MoE requires the AITER kernel on gfx942/gfx950",
+)
+@pytest.mark.parametrize("tp", [1])
+def test_quark_w4a8_fp8_moe(vllm_runner, monkeypatch, tp):
+    """Test W4A8 (INT4 weight + FP8 activation) MoE with a tiny Qwen3 MoE model.
+
+    W4A8 dispatches through the AITER fused MoE kernel, so AITER must be on.
+    """
+    monkeypatch.setenv("VLLM_ROCM_USE_AITER", "1")
+    monkeypatch.setenv("VLLM_ROCM_USE_AITER_MOE", "1")
+    model_path = "amd/tiny-qwen3-moe-w4a8"
+    with vllm_runner(
+        model_path,
+        enforce_eager=True,
+        tensor_parallel_size=tp,
+        gpu_memory_utilization=0.1,
+    ) as llm:
+
+        def check_model(model):
+            moe = model.model.layers[0].mlp.experts
+            assert isinstance(moe._quant_method, QuarkW4A8Fp8MoEMethod), (
+                f"Expected QuarkW4A8Fp8MoEMethod, got {type(moe._quant_method)}"
+            )
+
+        llm.apply_model(check_model)
+
+        output = llm.generate_greedy("Hello", max_tokens=4)
+        assert output
+
+
 def test_quark_fp8_parity(vllm_runner):
     quark_model_id = "amd-quark/llama-tiny-fp8-quark-quant-method"
     fp8_model_id = "amd-quark/llama-tiny-fp8-quant-method"