diff --git a/test/test_tensor.py b/test/test_tensor.py
index 05c3d6b1a6..025731037d 100644
--- a/test/test_tensor.py
+++ b/test/test_tensor.py
@@ -379,17 +379,17 @@ class TestZeroShapeTensor(unittest.TestCase):
     t = Tensor.empty(3, 2, 0)
     assert t.shape == (3, 2, 0)
     # numpy has stride 0, 0, 0; torch has stride 2, 1, 1
-    assert t.lazydata.st.real_strides() == (0, 0, 1)
+    assert t.lazydata.st.real_strides() == (0, 0, 0)
 
     t = Tensor.empty(3, 0, 2)
     assert t.shape == (3, 0, 2)
     # numpy has stride 0, 0, 0; torch has stride 2, 2, 1
-    assert t.lazydata.st.real_strides() == (0, 2, 1)
+    assert t.lazydata.st.real_strides() == (0, 0, 0)
 
     t = Tensor.empty(0, 0, 0)
     assert t.shape == (0, 0, 0)
     # numpy has stride 0, 0, 0; torch has stride 1, 1, 1
-    assert t.lazydata.st.real_strides() == (0, 0, 1)
+    assert t.lazydata.st.real_strides() == (0, 0, 0)
 
   def test_rand(self):
     t = Tensor.rand(3, 2, 0)
diff --git a/tinygrad/shape/view.py b/tinygrad/shape/view.py
index 92da2b5a35..077eb1a65b 100644
--- a/tinygrad/shape/view.py
+++ b/tinygrad/shape/view.py
@@ -96,6 +96,8 @@ class View:
   @functools.lru_cache(maxsize=None)
   def create(shape:Tuple[sint, ...], strides:Optional[Tuple[sint, ...]]=None, offset:sint=0, mask:Optional[Tuple[Tuple[sint, sint], ...]]=None):
     strides = canonicalize_strides(shape, strides) if strides else strides_for_shape(shape)
+    # canonicalize 0 in shape
+    if 0 in shape: return View(shape, (0,) * len(shape), offset=0, mask=None, contiguous=True)
     # canonicalize empty mask
     if mask is not None and all(m == (0,s) for m,s in zip(mask, shape)): mask = None
     # if any dimension has size >1, but is masked such that only one index in the dimension is unmasked