diff --git a/test/test_ops.py b/test/test_ops.py
index 1d4c8f67a2..10fbd9dc6d 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -98,6 +98,31 @@ class TestOps(unittest.TestCase):
     helper_test_op([], lambda: torch.eye(10), lambda: Tensor.eye(10), forward_only=True)
     helper_test_op([], lambda: torch.eye(1), lambda: Tensor.eye(1), forward_only=True)
 
+  def test_chunk(self):
+    tor = torch.arange(13).repeat(8, 1).chunk(6, 1)
+    ten = Tensor.arange(13).repeat((8, 1)).chunk(6, 1)
+    assert len(tor) == len(ten)
+    for i in range(len(tor)):
+      helper_test_op([], lambda: tor[i], lambda: ten[i], forward_only=True)
+
+    tor = torch.arange(13).repeat(8, 1).chunk(6, 0)
+    ten = Tensor.arange(13).repeat((8, 1)).chunk(6, 0)
+    assert len(tor) == len(ten)
+    for i in range(len(tor)):
+      helper_test_op([], lambda: tor[i], lambda: ten[i], forward_only=True)
+
+    tor = torch.arange(13).repeat(8, 1).chunk(3, -1)
+    ten = Tensor.arange(13).repeat((8, 1)).chunk(3, -1)
+    assert len(tor) == len(ten)
+    for i in range(len(tor)):
+      helper_test_op([], lambda: tor[i], lambda: ten[i], forward_only=True)
+
+    tor = torch.arange(13).repeat(8, 3, 3).chunk(3, -2)
+    ten = Tensor.arange(13).repeat((8, 3, 3)).chunk(3, -2)
+    assert len(tor) == len(ten)
+    for i in range(len(tor)):
+      helper_test_op([], lambda: tor[i], lambda: ten[i], forward_only=True)
+
   def test_arange(self):
     helper_test_op([], lambda: torch.arange(10), lambda: Tensor.arange(10), forward_only=True)
     helper_test_op([], lambda: torch.arange(5, 10, 3), lambda: Tensor.arange(10, 5, 3), forward_only=True)
diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index fb48361e07..544b3652b7 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -340,10 +340,10 @@ class Tensor:
 
   # TODO: make this nicer with syntactic sugar in slice
   def chunk(self, num, dim):
-    slice_params = [[(0, s) for s in self.shape] for _ in range(num)]
-    for i,k in enumerate(range(0, self.shape[dim], self.shape[dim]//num)):
-      slice_params[i][dim] = (k, min(self.shape[dim], k+self.shape[dim]//num))
-    return [self.slice(p) for p in slice_params]
+    slice_params = [[slice(None) for s in self.shape] for _ in range(ceil(self.shape[dim]/ceil(self.shape[dim]/num)))]
+    for i, k in enumerate(range(0, self.shape[dim], ceil(self.shape[dim]/num))):
+      slice_params[i][dim] = slice(k, k + ceil(self.shape[dim]/num))
+    return [self[tuple(sl)] for sl in slice_params]
 
   def squeeze(self, dim=None):
     if dim is None: return self if 1 not in self.shape else self.reshape(*[size for size in self.shape if size != 1])