diff --git a/test/test_dtype.py b/test/test_dtype.py
index 6cb1aea187..7762166b03 100644
--- a/test/test_dtype.py
+++ b/test/test_dtype.py
@@ -7,7 +7,7 @@ from tinygrad.helpers import getenv, DEBUG, CI
 from tinygrad.dtype import DType, DTYPES_DICT, least_upper_dtype, fp8_to_float, float_to_fp8, _to_np_dtype, _to_torch_dtype, truncate
 from tinygrad.renderer.ptx import PTXRenderer
 from tinygrad import Device, Tensor, dtypes
-from hypothesis import assume, given, settings, strategies as strat
+from hypothesis import given, settings, strategies as strat
 from test.helpers import rand_for_dtype
 from test.unit.test_dtype_spec import _assert_eq, core_dtypes, dtype_ints, dtype_floats, FP8E4M3_MAX, FP8E5M2_MAX
 import pytest
@@ -52,8 +52,6 @@ def _test_cast(a:Tensor, target_dtype:DType):
   if target_dtype in dtypes.fp8s: expected = list(map(lambda x: truncate[target_dtype](x), expected))
   _test_op(lambda: a.cast(target_dtype), target_dtype, expected)
 def _test_bitcast(a:Tensor, target_dtype:DType, target=None):
-  if isinstance(Device[Device.DEFAULT].renderer, PTXRenderer) and a.dtype == dtypes.int8 and target_dtype.itemsize != a.dtype.itemsize:
-    raise unittest.SkipTest("shape changing bitcast of int8 broken on PTX")
   expected = torch.tensor(a.tolist(), dtype=_to_torch_storage_type(a.dtype)).view(_to_torch_dtype(target_dtype)).tolist()
   if target_dtype in dtypes.fp8s: expected = list(map(lambda x: fp8_to_float(x, target_dtype), expected))
   _test_op(lambda: a.bitcast(target_dtype), target_dtype, target or expected)
@@ -294,7 +292,6 @@ class TestInt8DType(TestDType):
   def test_int8_to_uint16_negative(self):
     _test_op(lambda: Tensor([-1, -2, -3, -4], dtype=dtypes.int8).cast(dtypes.uint16), dtypes.uint16, [2**16-1, 2**16-2, 2**16-3, 2**16-4])
 
-  @unittest.skipIf(isinstance(Device[Device.DEFAULT].renderer, PTXRenderer), "broken in ptx")
   def test_bitcast_alt(self):
     a = Tensor([72, -90, 27, 40, -53, 70, 96, 51], dtype=dtypes.int8).bitcast(dtypes.short)
     self.assertListEqual(a.tolist(), [-22968, 10267, 18123, 13152])
@@ -308,8 +305,6 @@ class TestUint8DType(TestDType):
 class TestBitCast(unittest.TestCase):
   @given(strat.sampled_from(dtype_ints + dtype_floats), strat.sampled_from(dtype_ints + dtype_floats))
   def test_shape_change_bitcast(self, dt1, dt2):
-    # NOTE: this has to be assume to prevent hypothesis from skipping all samples
-    assume(not (isinstance(Device[Device.DEFAULT].renderer, PTXRenderer) and dt1 == dtypes.int8)) # TODO: bitcasting int8 fails in PTX
     data = rand_for_dtype(dt1, 32).reshape(2, 2, 8)
     expected = torch.tensor(data.tolist(), dtype=_to_torch_storage_type(dt1)).view(_to_torch_dtype(dt2))
     if dt2 in dtypes.fp8s: