diff --git a/test/test_const_folding.py b/test/test_const_folding.py
index a117baadd9..86d33abd0a 100644
--- a/test/test_const_folding.py
+++ b/test/test_const_folding.py
@@ -174,9 +174,9 @@ class TestMovedConstFolding(unittest.TestCase):
     if is_dtype_supported(dtypes.uint16):
       _check_ast_count(0, Tensor.full(4, fill_value=-1).pad(((1, 1),)).cast(dtypes.uint16))
       np.testing.assert_equal(Tensor.full(4, fill_value=-1).pad(((1, 1),)).cast(dtypes.uint16).numpy(), [0, 65535, 65535, 65535, 65535, 0])
-    # not folded
+    # folded
     if is_dtype_supported(dtypes.int64):
-      _check_ast_count(1, Tensor.ones(4).pad(((1, 1),)).cast(dtypes.int64))
+      _check_ast_count(0, Tensor.ones(4).pad(((1, 1),)).cast(dtypes.int64))
       np.testing.assert_equal(Tensor.ones(4).pad(((1, 1),)).cast(dtypes.int64).numpy(), [0, 1, 1, 1, 1, 0])
 
 class TestReduceOpsConstFolding(unittest.TestCase):
diff --git a/test/test_schedule.py b/test/test_schedule.py
index c6312a8fc4..68833b7c4d 100644
--- a/test/test_schedule.py
+++ b/test/test_schedule.py
@@ -6,6 +6,7 @@ import unittest
 import numpy as np
 import functools
 from typing import List, Optional, Union, cast
+from hypothesis import assume, given, strategies as strat
 
 from tinygrad import nn, dtypes, Device, Tensor
 from tinygrad.device import is_dtype_supported
@@ -1705,13 +1706,15 @@ class TestSchedule(unittest.TestCase):
     run_schedule(check_schedule(realized_const_view, 1))
     self.assertListEqual(realized_const_view.tolist(), [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]])
 
-  def test_cast_padded_const(self):
-    a = Tensor(1, dtype=dtypes.int32).reshape(1, 1).pad(((1, 1), None))
-    casted_view = a.cast(dtypes.float32)
+  @given(strat.sampled_from(dtypes.all), strat.sampled_from(dtypes.all))
+  def test_cast_padded_const(self, dt1, dt2):
+    assume(is_dtype_supported(dt1) and is_dtype_supported(dt2))
+    a = Tensor(1, dtype=dt1).reshape(1, 1).pad(((1, 1), None))
+    casted_view = a.cast(dt2)
     run_schedule(check_schedule(casted_view, 0))
     realized_const_view = casted_view.contiguous()
     run_schedule(check_schedule(realized_const_view, 1))
-    self.assertListEqual(realized_const_view.tolist(), [[0], [1], [0]])
+    np.testing.assert_equal(realized_const_view.numpy(), [[0], [1], [0]])
 
 class TestIndexing(unittest.TestCase):
   def check_schedule(self, xt:Union[Tensor,List[Tensor]], cnt:int):
diff --git a/tinygrad/engine/grouper.py b/tinygrad/engine/grouper.py
index cf55891473..e4e45d0675 100644
--- a/tinygrad/engine/grouper.py
+++ b/tinygrad/engine/grouper.py
@@ -84,6 +84,8 @@ sym = symbolic_simple+PatternMatcher([
   # remove cast to image when it's already a contiguous image
   (UPat(Ops.CAST, name="cast", src=(UPat(Ops.VIEW, name="vm", src=(UPat(Ops.CONTIGUOUS, name="base"),)),)),
    lambda cast,base,vm: base.view(vm.st) if isinstance(cast.dtype, ImageDType) and isinstance(base.dtype, ImageDType) else None),
+  # CAST before masking constants
+  (UPat.cvar("x").view().cast(name="c"), lambda x,c: x.cast(c.dtype).view(c.src[0].arg)),
   # make things that can't be images not images
   (UPat(GroupOp.All-{Ops.BUFFER, Ops.VIEW, Ops.CONST, Ops.DEVICE}, name="u"), lambda u: u.replace(dtype=dt.base) if isinstance(dt:=u.dtype,ImageDType)
    and (prod(u.shape) != prod(dt.shape) or not any(u.shape[x]%4 == 0 for x in u.st.unit_stride_axes())) else None),