diff --git a/test/test_testing.py b/test/test_testing.py
index af74106c92b..3dfa44c9bf0 100644
--- a/test/test_testing.py
+++ b/test/test_testing.py
@@ -2329,12 +2329,10 @@ class TestImports(TestCase):
                     raise RuntimeError(f"Failed to import {mod_name}: {e}") from e
                 self.assertTrue(inspect.ismodule(mod))
 
-    @unittest.skipIf(IS_WINDOWS, "TODO enable on Windows")
     def test_lazy_imports_are_lazy(self) -> None:
         out = self._check_python_output("import sys;import torch;print(all(x not in sys.modules for x in torch._lazy_modules))")
         self.assertEqual(out.strip(), "True")
 
-    @unittest.skipIf(IS_WINDOWS, "importing torch+CUDA on CPU results in warning")
     def test_no_warning_on_import(self) -> None:
         out = self._check_python_output("import torch")
         self.assertEqual(out, "")
@@ -2350,7 +2348,6 @@ class TestImports(TestCase):
                          "  - Use TYPE_CHECKING if you are using sympy + strings if you are using sympy on type annotations\n"
                          "  - Import things that depend on SymPy locally")
 
-    @unittest.skipIf(IS_WINDOWS, "importing torch+CUDA on CPU results in warning")
     @parametrize('path', ['torch', 'functorch'])
     def test_no_mutate_global_logging_on_import(self, path) -> None:
         # Calling logging.basicConfig, among other things, modifies the global
diff --git a/test/test_torch.py b/test/test_torch.py
index ae22247d898..4733cf0a1f2 100644
--- a/test/test_torch.py
+++ b/test/test_torch.py
@@ -36,7 +36,7 @@ from torch.testing._internal.common_optimizers import (
 
 from torch.testing._internal.common_utils import (  # type: ignore[attr-defined]
     MI300_ARCH, TEST_WITH_TORCHINDUCTOR, TEST_WITH_ROCM, run_tests, IS_JETSON,
-    IS_WINDOWS, IS_FILESYSTEM_UTF8_ENCODING, NO_MULTIPROCESSING_SPAWN,
+    IS_FILESYSTEM_UTF8_ENCODING, NO_MULTIPROCESSING_SPAWN,
     IS_SANDCASTLE, IS_FBCODE, IS_REMOTE_GPU, skipIfRocmArch, skipIfTorchInductor, load_tests, slowTest, slowTestIf,
     skipIfCrossRef, TEST_WITH_CROSSREF, skipIfTorchDynamo, skipRocmIfTorchInductor, set_default_dtype,
     skipCUDAMemoryLeakCheckIf, BytesIOContext,
@@ -6111,7 +6111,6 @@ else:
         self._run_scaling_case(device.type, run, unskipped=3, skipped=1)
 
     @onlyNativeDeviceTypes
-    @unittest.skipIf(IS_WINDOWS, 'FIXME: fix this test for Windows')
     def test_grad_scaling_penalty(self, device):
         device = torch.device(device)
 
@@ -9591,11 +9590,10 @@ tensor([[[1.+1.j, 1.+1.j, 1.+1.j,  ..., 1.+1.j, 1.+1.j, 1.+1.j],
         self.assertNotEqual(output, None)
         self.assertIn('Unhandled exception caught in c10/util/AbortHandler.h', output)
 
-    # FIXME: port to a distributed test suite -- also... how could this be OOMing on Windows CUDA?
+    # FIXME: port to a distributed test suite
     @slowTest
     @unittest.skipIf(NO_MULTIPROCESSING_SPAWN, "Disabled for environments that \
                         don't support multiprocessing with spawn start method")
-    @unittest.skipIf(IS_WINDOWS, 'FIXME: CUDA OOM error on Windows')
     def test_multinomial_invalid_probs(self):
         def _spawn_method(self, method, arg):
             try:
diff --git a/test/test_unary_ufuncs.py b/test/test_unary_ufuncs.py
index 8a6d111364c..ca5ab1e7df3 100644
--- a/test/test_unary_ufuncs.py
+++ b/test/test_unary_ufuncs.py
@@ -41,7 +41,6 @@ from torch.testing._internal.common_methods_invocations import (
 from torch.testing._internal.common_utils import (
     gradcheck,
     is_iterable_of_tensors,
-    IS_WINDOWS,
     numpy_to_torch_dtype_dict,
     run_tests,
     skipIfNoSciPy,
@@ -549,9 +548,7 @@ class TestUnaryUfuncs(TestCase):
         x = torch.tensor(0.0 - 1.0e20j, dtype=dtype, device=device)
         self.compare_with_numpy(torch.sqrt, np.sqrt, x)
         # acos test reference: https://github.com/pytorch/pytorch/issue/42952
-        # Skip on Windows, as CUDA acos  returns conjugate value
-        # see https://github.com/pytorch/pytorch/issues/52299
-        if not (IS_WINDOWS and dtype == torch.cdouble and "cuda" in device):
+        if not (dtype == torch.cdouble and "cuda" in device):
             self.compare_with_numpy(torch.acos, np.arccos, x)
 
         x = torch.tensor(