diff --git a/test/test_ops.py b/test/test_ops.py
index 7043f57f8c..37298d7db7 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -1122,9 +1122,9 @@ class TestOps(unittest.TestCase):
     helper_test_op([()], lambda x: x.reshape([]))
     helper_test_op([(1,)], lambda x: x.reshape([]))
     helper_test_op([()], lambda x: x.reshape([1]))
-    helper_test_op([()], lambda x: x.reshape([1, 1, 1]))
-    self.helper_test_exception([(3, 4)], lambda x: x.reshape((-1, -1, 2)), lambda x: x.reshape((-1, -1, 2)), expected=RuntimeError)
-    self.helper_test_exception([(3, 4)], lambda x: x.reshape((-1, -1, -1, 2)), lambda x: x.reshape((-1, -1, -1, 2)), expected=RuntimeError)
+    helper_test_op([()], lambda x: x.reshape([1,1,1]))
+    self.helper_test_exception([(3,4)], lambda x: x.reshape((-1,-1,2)), lambda x: x.reshape((-1,-1,2)), expected=RuntimeError)
+    self.helper_test_exception([(3,4)], lambda x: x.reshape((-1,-1,-1,2)), lambda x: x.reshape((-1,-1,-1,2)), expected=RuntimeError)
 
     with self.assertRaises(ValueError):
       x = Tensor.ones((4,3,6,6))
@@ -1139,7 +1139,10 @@ class TestOps(unittest.TestCase):
     helper_test_op([(4,3,6,6)], lambda x: x.flip((-1,)))
     helper_test_op([()], lambda x: x.flip(()))
     helper_test_op([(1,)], lambda x: x.flip(()))
-    helper_test_op([(4, 3, 6, 6)], lambda x: x.flip(()))
+    helper_test_op([(4,3,6,6)], lambda x: x.flip(()))
+    self.helper_test_exception([(3,4)], lambda x: x.flip((0,0)), lambda x: x.flip((0,0)), expected=RuntimeError)
+    self.helper_test_exception([(3,4)], lambda x: x.flip((1,1)), lambda x: x.flip((1,1)), expected=RuntimeError)
+    self.helper_test_exception([(3,4)], lambda x: x.flip((1,-1)), lambda x: x.flip((1,-1)), expected=RuntimeError)
 
   def test_squeeze(self):
     helper_test_op([(1,3,6,6)], lambda x: x.squeeze(0))
diff --git a/tinygrad/function.py b/tinygrad/function.py
index 36a5c32951..395acc7274 100644
--- a/tinygrad/function.py
+++ b/tinygrad/function.py
@@ -205,7 +205,7 @@ class Shrink(Function):
 
 class Flip(Function):
   def forward(self, x:LazyBuffer, axis:Tuple[int, ...]) -> LazyBuffer:
-    self.arg = tuple([-1 if i in set(axis) else 1 for i in range(len(x.shape))])
+    self.arg = tuple([-1 if i in axis else 1 for i in range(len(x.shape))])
     return x.stride(self.arg)
 
   def backward(self, grad_output:LazyBuffer) -> LazyBuffer: return grad_output.stride(self.arg)
diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index 66e1f49c7e..d034e93bd9 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -7,7 +7,7 @@ from collections import defaultdict
 import numpy as np
 
 from tinygrad.dtype import DType, dtypes, ImageDType, ConstType, least_upper_float, least_upper_dtype, sum_acc_dtype
-from tinygrad.helpers import argfix, make_pair, flatten, prod, all_int, round_up, merge_dicts, argsort, getenv, get_shape, fully_flatten
+from tinygrad.helpers import argfix, make_pair, flatten, prod, all_int, round_up, merge_dicts, argsort, getenv, get_shape, fully_flatten, dedup
 from tinygrad.helpers import IMAGE, DEBUG, WINO, THREEFRY
 from tinygrad.lazy import LazyBuffer
 from tinygrad.multi import MultiLazyBuffer
@@ -817,7 +817,9 @@ class Tensor:
     print(t.flip((0, 1)).numpy())
     ```
     """
-    return F.Flip.apply(self, axis=[x if x >= 0 else x+len(self.shape) for x in argfix(axis, *args)])
+    axis_arg = tuple(self._resolve_dim(x) for x in argfix(axis, *args))
+    if len(axis_arg) != len(dedup(axis_arg)): raise RuntimeError(f"dim can appear at least once, getting {axis_arg}")
+    return F.Flip.apply(self, axis=axis_arg)
 
   def shrink(self, arg:Tuple[Optional[Tuple[sint, sint]], ...]) -> Tensor:
     """