diff --git a/test/float8/test_float8_utils.py b/test/float8/test_float8_utils.py
index c253af55ea..be5ff46f5c 100644
--- a/test/float8/test_float8_utils.py
+++ b/test/float8/test_float8_utils.py
@@ -10,11 +10,14 @@
 
 from torchao.float8.float8_utils import _round_scale_down_to_power_of_2
 from torchao.testing.utils import skip_if_rocm
+from torchao.utils import get_current_accelerator_device
+
+_DEVICE = get_current_accelerator_device()
 
 
 # source for notable single-precision cases:
 # https://en.wikipedia.org/wiki/Single-precision_floating-point_format
-@unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
+@unittest.skipIf(not torch.accelerator.is_available(), "GPU not available")
 @pytest.mark.parametrize(
     "test_case",
     [
@@ -38,8 +41,8 @@ def test_round_scale_down_to_power_of_2_valid_inputs(
 ):
     test_case_name, input, expected_result = test_case
     input_tensor, expected_tensor = (
-        torch.tensor(input, dtype=torch.float32).cuda(),
-        torch.tensor(expected_result, dtype=torch.float32).cuda(),
+        torch.tensor(input, dtype=torch.float32).to(_DEVICE),
+        torch.tensor(expected_result, dtype=torch.float32).to(_DEVICE),
     )
     result = _round_scale_down_to_power_of_2(input_tensor)
 
diff --git a/test/hqq/test_hqq_affine.py b/test/hqq/test_hqq_affine.py
index 09bdfa8e61..b103e8ccf0 100644
--- a/test/hqq/test_hqq_affine.py
+++ b/test/hqq/test_hqq_affine.py
@@ -14,12 +14,14 @@
     ZeroPointDomain,
     quantize_,
 )
-from torchao.testing.utils import skip_if_rocm
+from torchao.testing.utils import skip_if_rocm, skip_if_xpu
+from torchao.utils import get_current_accelerator_device
 
-cuda_available = torch.cuda.is_available()
+cuda_available = torch.accelerator.is_available()
+_DEVICE = get_current_accelerator_device()
 
 # Parameters
-device = "cuda:0"
+device = f"{_DEVICE}:0"
 compute_dtype = torch.bfloat16
 group_size = 64
 mapping_type = MappingType.ASYMMETRIC
@@ -114,6 +116,7 @@ def test_hqq_plain_5bit(self):
         )
 
     @skip_if_rocm("ROCm enablement in progress")
+    @skip_if_xpu("XPU enablement in progress")
     def test_hqq_plain_4bit(self):
         self._test_hqq(
             dtype=torch.uint4,