diff --git a/test/test_linearizer.py b/test/test_linearizer.py
index c955a0e65c..43552d662e 100644
--- a/test/test_linearizer.py
+++ b/test/test_linearizer.py
@@ -1062,16 +1062,14 @@ class TestLinearizer(unittest.TestCase):
   @unittest.skipUnless(Device[Device.DEFAULT].renderer.tensor_cores, "test requires tensor cores")
   def test_tensor_cores(self):
     for tc in Device[Device.DEFAULT].renderer.tensor_cores:
-      if (getenv("EMULATE_CUDA") or getenv("EMULATE_INTEL") or getenv("EMULATE_METAL") or getenv("EMULATE_AMD_MFMA") or getenv("EMULATE_AMD")) and \
-        (tc.dtype_in == dtypes.bfloat16 or tc.dtype_out == dtypes.bfloat16): continue
-      if CI and Device.DEFAULT in ("METAL", "AMD") and (tc.dtype_in == dtypes.bfloat16 or tc.dtype_out == dtypes.bfloat16): continue
+      if not is_dtype_supported(tc.dtype_in) or not is_dtype_supported(tc.dtype_out): continue
       # for AMX, tc.dims[2] == 1 so reduceop is None thus tensor_cores are not triggered
       helper_tc_allclose(tc.dims[0], tc.dims[1], 2 if AMX else tc.dims[2], tc.dtype_in, tc.dtype_out, axis=0, tc_opt=0)
 
   @unittest.skipUnless(Device[Device.DEFAULT].renderer.tensor_cores, "test requires tensor cores")
   def test_tensor_cores_codegen(self):
     for tc in Device[Device.DEFAULT].renderer.tensor_cores:
-      if CI and Device.DEFAULT == "AMD" and (tc.dtype_in == dtypes.bfloat16 or tc.dtype_out == dtypes.bfloat16): continue
+      if not is_dtype_supported(tc.dtype_in) or not is_dtype_supported(tc.dtype_out): continue
       n, m, k = tc.dims[0], tc.dims[1], 2 if AMX else tc.dims[2]
       a, b = Tensor.rand(m, k, dtype=tc.dtype_in), Tensor.rand(k, n, dtype=tc.dtype_in)
       r = a.matmul(b, dtype=tc.dtype_out)
@@ -1092,16 +1090,14 @@ class TestLinearizer(unittest.TestCase):
   @unittest.skipUnless(Device[Device.DEFAULT].renderer.tensor_cores, "test requires tensor cores")
   def test_tensor_cores_padded(self):
     for tc in Device[Device.DEFAULT].renderer.tensor_cores:
-      if (getenv("EMULATE_CUDA") or getenv("EMULATE_METAL") or getenv("EMULATE_AMD_MFMA") or getenv("EMULATE_AMD")) and \
-        (tc.dtype_in == dtypes.bfloat16 or tc.dtype_out == dtypes.bfloat16): continue
-      if CI and Device.DEFAULT in ("METAL", "AMD") and (tc.dtype_in == dtypes.bfloat16 or tc.dtype_out == dtypes.bfloat16): continue
+      if not is_dtype_supported(tc.dtype_in) or not is_dtype_supported(tc.dtype_out): continue
       helper_tc_allclose(tc.dims[0]+(pad:=1), tc.dims[1]+pad, tc.dims[2]+pad, tc.dtype_in, tc.dtype_out, tc_opt=2)
 
   @unittest.skipUnless(Device.DEFAULT in {"AMD"}, "Test for AMD device")
   @unittest.skipUnless(Device[Device.DEFAULT].renderer.tensor_cores, "test requires tensor cores")
   def test_tensor_cores_padded_amd(self):
     for tc in Device[Device.DEFAULT].renderer.tensor_cores:
-      if CI and (tc.dtype_in == dtypes.bfloat16 or tc.dtype_out == dtypes.bfloat16): continue
+      if not is_dtype_supported(tc.dtype_in) or not is_dtype_supported(tc.dtype_out): continue
       helper_tc_allclose(tc.dims[0]+(pad:=3), tc.dims[1]+pad, tc.dims[2]+pad, tc.dtype_in, tc.dtype_out, tc_opt=2)
 
   @unittest.skipUnless(Device[Device.DEFAULT].renderer.tensor_cores, "test requires tensor cores")
@@ -1129,7 +1125,7 @@ class TestLinearizer(unittest.TestCase):
   @unittest.skipUnless(Device[Device.DEFAULT].renderer.tensor_cores, "test requires tensor cores")
   def test_tensor_cores_multi_reduce(self):
     for tc in Device[Device.DEFAULT].renderer.tensor_cores:
-      if tc.dtype_in == dtypes.bfloat16 or tc.dtype_out == dtypes.bfloat16: continue
+      if not is_dtype_supported(tc.dtype_in) or not is_dtype_supported(tc.dtype_out): continue
       # this will be a M=G16, N=G32, M=G16, M=G16, K=R16, K=R16, K=R16 with 9 choices of TC MNK axes
       golden_result = None
       for axis in range(9):