diff --git a/tests/python/direct/test_cutlass_nvfp4_gemm.py b/tests/python/direct/test_cutlass_nvfp4_gemm.py
index 8b73f384338..22cdb7aaca4 100644
--- a/tests/python/direct/test_cutlass_nvfp4_gemm.py
+++ b/tests/python/direct/test_cutlass_nvfp4_gemm.py
@@ -6,15 +6,8 @@
 import pytest
 import torch
 from nvfuser_direct import nvf_cutlass
-
-compute_cap = torch.cuda.get_device_capability()
-if compute_cap < (10, 0) or compute_cap >= (12, 0):
-    pytest.skip(
-        reason="Nvfp4 Requires compute capability 10.",
-        allow_module_level=True,
-    )
-
 from python.direct_utils import (
+    microarchitecture_is,
     FLOAT4_E2M1_MAX,
     FLOAT8_E4M3_MAX,
     dequantize_to_dtype,
@@ -52,6 +45,10 @@ def get_ref_results(
     return torch.matmul(a_in_dtype, b_in_dtype.t())
 
 
+@pytest.mark.skipif(
+    not microarchitecture_is(10, 0),
+    reason="Does not support blackwell compute 12.0, other arches are not tested.",
+)
 @pytest.mark.parametrize("dtype", [torch.float16, torch.bfloat16])
 @pytest.mark.parametrize(
     "shape", [(128, 128, 64), (128, 128, 128), (256, 128, 64), (128, 256, 128)]
@@ -100,6 +97,10 @@ def test_nvfp4_gemm(
     torch.testing.assert_close(out, expected_out.to(dtype=dtype), atol=1e-1, rtol=1e-1)
 
 
+@pytest.mark.skipif(
+    not microarchitecture_is(10, 0),
+    reason="Does not support blackwell compute 12.0, other arches are not tested.",
+)
 @pytest.mark.parametrize("dtype", [torch.float16, torch.bfloat16])
 @pytest.mark.parametrize(
     "shape", [(128, 128, 64), (128, 128, 128), (256, 128, 64), (128, 256, 128)]
@@ -175,6 +176,10 @@ def test_nvfp4_gemm_epilogue(
     )
 
 
+@pytest.mark.skipif(
+    not microarchitecture_is(10, 0),
+    reason="Does not support blackwell compute 12.0, other arches are not tested.",
+)
 @pytest.mark.parametrize("config", [[1024, 128, 256]])
 @pytest.mark.parametrize("tokens_per_expert_neg_one", [[115, 144, 8]])
 @pytest.mark.parametrize("out_dtype", [torch.bfloat16, torch.float16])
diff --git a/tests/python/direct/test_narrow_precision.py b/tests/python/direct/test_narrow_precision.py
index 8e16b7abc09..591be769e56 100644
--- a/tests/python/direct/test_narrow_precision.py
+++ b/tests/python/direct/test_narrow_precision.py
@@ -16,6 +16,8 @@
     pytorch_nvfp4_quantize,
     is_pre_blackwell,
     microarchitecture_is_pre,
+    is_blackwell,
+    microarchitecture_is,
     linear_to_swizzled_128_4,
     round_up,
     activation_scale_to_nvfp4,
@@ -241,10 +243,8 @@ def nvfuser_fusion_id0(fd: FusionDefinition):
 
 # cannot use opinfo test, because the input tensor dtype and fusion definition dtype doesn't match
 @pytest.mark.skipif(
-    is_pre_blackwell(), reason="Only supported on blackwell and newer devices."
-)
-@pytest.mark.skipif(
-    not microarchitecture_is_pre(12), reason="Does not support blackwell compute 12.0"
+    not microarchitecture_is(10, 0),
+    reason="Does not support blackwell compute 12.0, other arches are not tested.",
 )
 @pytest.mark.parametrize("config", [[128, 256, 512], [128, 256, 512]])
 @pytest.mark.parametrize("out_dtype", [torch.bfloat16])
@@ -323,9 +323,7 @@ def nvfuser_fusion_id0(fd: FusionDefinition) -> None:
     torch.testing.assert_close(outputs[0], ref_outputs, rtol=1e-1, atol=1e-2)
 
 
-@pytest.mark.skipif(
-    is_pre_blackwell(), reason="Only supported on blackwell and newer devices."
-)
+@pytest.mark.skipif(not is_blackwell(), reason="Only supported on blackwell.")
 @pytest.mark.parametrize("config", [[1024, 1024, 1024]])
 @pytest.mark.parametrize("out_dtype", [torch.bfloat16])
 def test_scaled_mm_nv_quantized(
@@ -454,10 +452,8 @@ def fusion_baseline(fd: FusionDefinition) -> None:
 
 
 @pytest.mark.skipif(
-    is_pre_blackwell(), reason="Only supported on blackwell and newer devices."
-)
-@pytest.mark.skipif(
-    not microarchitecture_is_pre(12), reason="Does not support blackwell compute 12.0"
+    not microarchitecture_is(10, 0),
+    reason="Does not support blackwell compute 12.0, other arches are not tested.",
 )
 @pytest.mark.parametrize("config", [[1024, 128, 256]])
 @pytest.mark.parametrize("tokens_per_expert_neg_one", [[115, 144, 8]])
@@ -661,10 +657,8 @@ def nvfuser_fusion_id0(fd: FusionDefinition) -> None:
 #     1. inputs data needs to be changed from `torch.testing.make_tensor` to `torch.randn`;
 #     2. output errors are much more relaxed.
 @pytest.mark.skipif(
-    is_pre_blackwell(), reason="Only supported on blackwell and newer devices."
-)
-@pytest.mark.skipif(
-    not microarchitecture_is_pre(12), reason="Does not support blackwell compute 12.0"
+    not microarchitecture_is(10, 0),
+    reason="Does not support blackwell compute 12.0, other arches are not tested.",
 )
 @pytest.mark.parametrize("config", [[1024, 128, 256]])
 @pytest.mark.parametrize("tokens_per_expert_neg_one", [[115, 144, 8]])
diff --git a/tests/python/direct/test_with_id_model_indexer.py b/tests/python/direct/test_with_id_model_indexer.py
index b251a1da190..c701f677946 100644
--- a/tests/python/direct/test_with_id_model_indexer.py
+++ b/tests/python/direct/test_with_id_model_indexer.py
@@ -15,8 +15,7 @@
     FLOAT8_E4M3_EPS,
     FLOAT8_E4M3_MAX,
     pytorch_nvfp4_quantize,
-    is_pre_blackwell,
-    microarchitecture_is_pre,
+    microarchitecture_is,
     linear_to_swizzled_128_4,
     round_up,
     activation_scale_to_nvfp4,
@@ -31,10 +30,8 @@
 # assertion. Having this as a separate test file would avoid environment
 # variable contamination from others.
 @pytest.mark.skipif(
-    is_pre_blackwell(), reason="Only supported on blackwell and newer devices."
-)
-@pytest.mark.skipif(
-    not microarchitecture_is_pre(12), reason="Does not support blackwell compute 12.0"
+    not microarchitecture_is(10, 0),
+    reason="Does not support blackwell compute 12.0, other arches are not tested.",
 )
 @pytest.mark.parametrize("config", [[1024, 128, 256]])
 @pytest.mark.parametrize("tokens_per_expert_neg_one", [[115, 144, 8]])
diff --git a/tests/python/direct_utils/utils.py b/tests/python/direct_utils/utils.py
index f5eb652a39e..9b156a51437 100644
--- a/tests/python/direct_utils/utils.py
+++ b/tests/python/direct_utils/utils.py
@@ -35,6 +35,19 @@ def is_pre_blackwell():
     return microarchitecture_is_pre(10)
 
 
+# 10.0 (B200 and GB200)
+# 10.3 (B300 and GB300)
+# 12.0 (RTX PRO 6000 and RTX 50XX)
+# 12.1 (DGX Spark)
+def is_blackwell():
+    return (
+        microarchitecture_is(10, 0)
+        or microarchitecture_is(10, 3)
+        or microarchitecture_is(12, 0)
+        or microarchitecture_is(12, 1)
+    )
+
+
 # Get string representation for FusionDefinition
 # Run captured python definition
 # Check that the result of captured python definition matches original results