diff --git a/test/test_dtype.py b/test/test_dtype.py
index bb5948d014..2bdfffb040 100644
--- a/test/test_dtype.py
+++ b/test/test_dtype.py
@@ -413,7 +413,6 @@ class TestTypeSpec(unittest.TestCase):
     # _assert_eq(Tensor.ones((2,3,0), dtype=dtypes.default_int).sum(2), dtypes.default_int, np.zeros((2, 3)))
     _assert_eq(Tensor.ones((2,3,0), dtype=dtypes.int32).sum(2), dtypes.int32, np.zeros((2, 3)))
 
-  @unittest.skipIf(Device.DEFAULT=="RHIP", "failed in HIP CI")
   @given(strat.sampled_from(dtype_ints), strat.sampled_from(dtype_floats))
   def test_arange(self, default_int, default_float):
     dtypes.default_int, dtypes.default_float = default_int, default_float
diff --git a/test/test_ops.py b/test/test_ops.py
index 9bcb9aff63..9092b84bb7 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -131,7 +131,6 @@ class TestOps(unittest.TestCase):
     helper_test_op([], lambda: torch.eye(1), lambda: Tensor.eye(1), forward_only=True)
     helper_test_op([], lambda: torch.eye(0), lambda: Tensor.eye(0), forward_only=True)
 
-  @unittest.skipIf(Device.DEFAULT=="RHIP", "broken in HIP CI")
   def test_split(self):
     def tensor(s): return torch.arange(math.prod(s), dtype=torch.int32).reshape(s), Tensor.arange(math.prod(s)).reshape(s)
     test_cases = [
diff --git a/test/test_randomness.py b/test/test_randomness.py
index 289fda02e2..999ca5451c 100644
--- a/test/test_randomness.py
+++ b/test/test_randomness.py
@@ -104,8 +104,7 @@ class TestRandomness(unittest.TestCase):
     self.assertTrue(equal_distribution(Tensor.randn, torch.randn, lambda x: np.random.randn(*x)))
 
   @given(strat.sampled_from([dtypes.float, dtypes.float16, dtypes.bfloat16]))
-  @unittest.skipIf(Device.DEFAULT=="RHIP", "float16 broken in HIP CI")
-  @unittest.skipIf(Device.DEFAULT=="HSA", "bfloat16 local buffer broken in HSA")
+  @unittest.skipIf(Device.DEFAULT in ["HSA", "RHIP"], "bfloat16 local buffer broken in HSA")
   def test_randn_finite(self, default_float):
     if not is_dtype_supported(default_float): return
     old_default_float = dtypes.default_float