diff --git a/test/quantization/test_qat.py b/test/quantization/test_qat.py
index cef78b32e..232fbef81 100644
--- a/test/quantization/test_qat.py
+++ b/test/quantization/test_qat.py
@@ -423,7 +423,7 @@ def test_qat_4w_primitives(self):
     @unittest.skipIf(not TORCH_VERSION_AT_LEAST_2_4, "skipping when torch version is 2.4 or lower")
     @unittest.skipIf(not _CUDA_IS_AVAILABLE, "skipping when cuda is not available")
     # TODO: remove once we fix int4 error: https://github.com/pytorch/ao/pull/517
-    @unittest.skip(TORCH_VERSION_AFTER_2_4, "assert input.dtype == torch.float32" )
+    @unittest.skipIf(TORCH_VERSION_AT_LEAST_2_4, "assert input.dtype == torch.float32" )
     @unittest.skipIf(TORCH_VERSION_AT_LEAST_2_5, "int4 doesn't work for 2.5+ right now")
     def test_qat_4w_linear(self):
         from torchao.quantization.prototype.qat.api import Int4WeightOnlyQATLinear
@@ -454,7 +454,7 @@ def test_qat_4w_linear(self):
     @unittest.skipIf(not TORCH_VERSION_AT_LEAST_2_4, "skipping when torch version is 2.4 or lower")
     @unittest.skipIf(not _CUDA_IS_AVAILABLE, "skipping when cuda is not available")
     # TODO: remove once we fix int4 error: https://github.com/pytorch/ao/pull/517
-    @unittest.skip(TORCH_VERSION_AFTER_2_4, "assert input.dtype == torch.float32" )
+    @unittest.skipIf(TORCH_VERSION_AT_LEAST_2_4, "assert input.dtype == torch.float32" )
     @unittest.skipIf(TORCH_VERSION_AT_LEAST_2_5, "int4 doesn't work for 2.5+ right now")
     def test_qat_4w_quantizer(self):
         from torchao.quantization.prototype.qat import Int4WeightOnlyQATQuantizer