diff --git a/test/registered/unit/layers/quantization/test_fp4_kv_cache_quant_method.py b/test/registered/unit/layers/quantization/test_fp4_kv_cache_quant_method.py
index 2c31bf238..a6ae13fb2 100644
--- a/test/registered/unit/layers/quantization/test_fp4_kv_cache_quant_method.py
+++ b/test/registered/unit/layers/quantization/test_fp4_kv_cache_quant_method.py
@@ -11,9 +11,13 @@ import torch
 from sglang.test.test_utils import CustomTestCase
 
 
-def skip_if_no_cuda(func):
-    """Skip test if CUDA is not available."""
-    return unittest.skipUnless(torch.cuda.is_available(), "CUDA not available")(func)
+def skip_if_no_blackwell_nvfp4(func):
+    """Skip test if Blackwell NVFP4 is not available."""
+    from sglang.srt.utils import is_blackwell
+
+    return unittest.skipUnless(
+        is_blackwell(), "Blackwell (SM100/SM120) with CUDA >= 12.8 is required"
+    )(func)
 
 
 class TestKVCacheQuantRegistry(CustomTestCase):
@@ -116,14 +120,16 @@ class TestNVFP4KVMethod(CustomTestCase):
         self.assertTrue(torch.all(m.v_scales_gpu == 1.0))
         self.assertEqual(len(m.k_scales_gpu), 4)
 
-    @skip_if_no_cuda
+    @skip_if_no_blackwell_nvfp4
     def test_quantize_dequantize_roundtrip(self):
         """Test NVFP4 quantize→dequantize roundtrip on CUDA."""
         from sglang.srt.layers.quantization.fp4_kv_cache_quant_method import (
             NVFP4KVMethod,
         )
 
-        m = NVFP4KVMethod(num_layers=1, device="cuda", sm_version=120)
+        major, minor = torch.cuda.get_device_capability()
+        m = NVFP4KVMethod(num_layers=1, device="cuda", sm_version=major * 10 + minor)
+
         size, heads, dim = 32, 8, 128
         bufs = m.create_buffers(size, heads, dim, 1, "cuda")