diff --git a/aten/src/ATen/native/sparse/cuda/SparseSemiStructuredLinear.cu b/aten/src/ATen/native/sparse/cuda/SparseSemiStructuredLinear.cu
index e997f49f3f43..35ae7dc102e7 100644
--- a/aten/src/ATen/native/sparse/cuda/SparseSemiStructuredLinear.cu
+++ b/aten/src/ATen/native/sparse/cuda/SparseSemiStructuredLinear.cu
@@ -628,12 +628,12 @@ Tensor _sparse_semi_structured_linear(
                 "_sparse_semi_structured_linear: Setting out_dtype is only "
                 "supported for int8 input and int32 output");
 
-    // For now, only CC 8.x devices are supported.
+    // For now, only CC 8.x and 9.x devices are supported.
     const auto dprops = at::cuda::getCurrentDeviceProperties();
-    const auto is_sm8x = dprops->major == 8;
-    TORCH_CHECK(is_sm8x,
+    const auto is_sm8x_sm9x = dprops->major == 8 || dprops->major == 9;
+    TORCH_CHECK(is_sm8x_sm9x,
                 "_sparse_semi_structured_linear: Supported only on GPUs with "
-                "compute capability 8.x");
+                "compute capability 8.x and 9.x");
 
     // Validate datatypes of input tensors.
     TORCH_CHECK(tensor_a.dtype() == at::kChar ||
diff --git a/test/test_sparse_semi_structured.py b/test/test_sparse_semi_structured.py
index aa9e0a97e168..6426273820dd 100644
--- a/test/test_sparse_semi_structured.py
+++ b/test/test_sparse_semi_structured.py
@@ -41,9 +41,9 @@ CUSPARSELT_MIXED_DTYPE_SUPPORT = [torch.float16, torch.bfloat16, torch.int32]
 SEMI_STRUCTURED_SUPPORTED_DTYPES = [torch.float16, torch.bfloat16, torch.float32, torch.int8]
 SEMI_STRUCTURED_SUPPORTED_BACKENDS = []
 
-_IS_SM8X = False
+_IS_SM8X_SM9X = False
 if torch.cuda.is_available():
-    _IS_SM8X = torch.cuda.get_device_capability(0)[0] == 8
+    _IS_SM8X_SM9X = torch.cuda.get_device_capability(0)[0] in {8, 9}
     SEMI_STRUCTURED_SUPPORTED_BACKENDS.append("cutlass")
 
     # check if cslt is available for now using this:
@@ -146,8 +146,8 @@ def rand_sparse_semi_structured_all_patterns(r, c, dtype, device):
 class SparseSemiStructuredTensorCompileTest(torch._dynamo.test_case.TestCase):
 
     def setUp(self):
-        if not _IS_SM8X:
-            self.skipTest('Only runs on SM80')
+        if not _IS_SM8X_SM9X:
+            self.skipTest('Only runs on SM80 and SM90')
         super().setUp()
 
     def tearDown(self):
@@ -219,8 +219,8 @@ class SparseSemiStructuredTensorCompileTest(torch._dynamo.test_case.TestCase):
 class TestSparseSemiStructured(TestCase):
 
     def setUp(self):
-        if not _IS_SM8X:
-            self.skipTest('Only runs on SM80')
+        if not _IS_SM8X_SM9X:
+            self.skipTest('Only runs on SM80 and SM90')
 
     @dtypes(*SEMI_STRUCTURED_SUPPORTED_DTYPES)
     @parametrize("backend", SEMI_STRUCTURED_SUPPORTED_BACKENDS)
@@ -632,8 +632,8 @@ class TestCUSPARSELT(TestCase):
     """
 
     def setUp(self):
-        if not _IS_SM8X:
-            self.skipTest('Only runs on SM80')
+        if not _IS_SM8X_SM9X:
+            self.skipTest('Only runs on SM80 and SM90')
         if "cusparselt" not in SEMI_STRUCTURED_SUPPORTED_BACKENDS:
             self.skipTest('cuSPARSELt not enabled')
         else: