diff --git a/test/test_dtype.py b/test/test_dtype.py
index d5e253ad8a..471a9a669f 100644
--- a/test/test_dtype.py
+++ b/test/test_dtype.py
@@ -120,7 +120,9 @@ class TestDType(unittest.TestCase):
     data = [1., 2., 0., 0.5, -1.5, 5.25]
     for dt in dtypes:
       arr = np.asarray(data).astype(dt)
-      tin = Tensor(arr).numpy()
+      tensor = Tensor(arr)
+      if not is_dtype_supported(tensor.dtype): continue
+      tin = tensor.numpy()
       tor = torch.as_tensor(arr).detach().numpy()
       assert dt == tin.dtype == tor.dtype, f"dtype mismatch: expected={dt} | tinygrad={tin.dtype} | torch={tor.dtype}"
       np.testing.assert_allclose(tin, tor, atol=1e-6, rtol=1e-3)
diff --git a/test/test_tiny.py b/test/test_tiny.py
index cd276f4141..04544d825f 100644
--- a/test/test_tiny.py
+++ b/test/test_tiny.py
@@ -46,8 +46,9 @@ class TestTiny(unittest.TestCase):
       nonlocal cnt
       cnt += 1
       return a+b
-    fa,fb = Tensor([1.,2,3]), Tensor([4.,5,6])
-    for _ in range(3): fxn(fa, fb)
+    for _ in range(3):
+      fa,fb = Tensor([1.,2,3]), Tensor([4.,5,6])
+      fxn(fa, fb)
     # function is only called twice
     self.assertEqual(cnt, 2)