diff --git a/test/test_schedule.py b/test/test_schedule.py
index 0b8351fc5b..4f8fa2542d 100644
--- a/test/test_schedule.py
+++ b/test/test_schedule.py
@@ -698,7 +698,6 @@ class TestSchedule(unittest.TestCase):
     c = (a.sum(2).contiguous() + b).contiguous()
     check_schedule(c, 2)
 
-  @expect_rangeify_fails
   def test_kernelize(self):
     a = Tensor.empty(10)
     b = Tensor.empty(10)
@@ -706,20 +705,20 @@ class TestSchedule(unittest.TestCase):
     d = c+2
     check_schedule(d, 2)
 
-  @expect_rangeify_fails
   def test_kernelize_view(self):
     a = Tensor.empty(4,1)
     b = a*2
     c = b.kernelize()+Tensor.empty(4,4)
     check_schedule(c, 2)
 
-  @expect_rangeify_fails
   def test_kernelize_diamond(self):
     a = Tensor([0]).realize()
     prev_a = (a+1).contiguous()
     a.assign(Tensor([2]))
     a.kernelize(prev_a)
-    assert prev_a.uop in a.uop.src, "contiguous usage must run before assign"
+    # RANGEIFY doesn't apply the post diamond graph, it's fine since we can always apply the fixup on each kernelize call
+    if not RANGEIFY:
+      assert prev_a.uop in a.uop.src, "contiguous usage must run before assign"
     self.assertEqual((prev_a+a*3).item(), 1+2*3)
 
   @expect_rangeify_fails
@@ -734,7 +733,6 @@ class TestSchedule(unittest.TestCase):
     self.assertEqual(b.buffer.numpy(), [12])
 
   # unlike schedule, kernelize can be called multiple times on a Tensor
-  @expect_rangeify_fails
   def test_double_kerenlize(self):
     a = Tensor.empty(10)
     b = Tensor.empty(10)
@@ -743,7 +741,6 @@ class TestSchedule(unittest.TestCase):
     e = c.kernelize()+d.kernelize()
     check_schedule(e, 3)
 
-  @expect_rangeify_fails
   def test_kernelize_bw(self):
     a = Tensor.full((3,), 2.0, requires_grad=True).contiguous()
     b = Tensor.full((3,), 3.0, requires_grad=True).contiguous()
@@ -754,7 +751,6 @@ class TestSchedule(unittest.TestCase):
     self.assertEqual(z.item(), 18.0)
     self.assertEqual(z.grad.item(), 1.0)
 
-  @expect_rangeify_fails
   def test_kernelize_bw_view(self):
     a = Tensor.full((3,1), 2.0, requires_grad=True).contiguous()
     b = Tensor.full((3,1), 3.0, requires_grad=True).contiguous()
diff --git a/tinygrad/schedule/rangeify.py b/tinygrad/schedule/rangeify.py
index a6aadb674a..a93cd2a8e2 100644
--- a/tinygrad/schedule/rangeify.py
+++ b/tinygrad/schedule/rangeify.py
@@ -13,7 +13,7 @@ from tinygrad.uop.ops import track_rewrites, graph_rewrite, identity_element, si
 
 ALWAYS_CONTIGUOUS: set[Ops] = {Ops.CONTIGUOUS, Ops.ASSIGN, Ops.COPY, Ops.BUFFER, Ops.BUFFER_VIEW,
                      Ops.CONST, Ops.BIND, Ops.DEVICE, Ops.MSELECT, Ops.MSTACK, Ops.DEFINE_GLOBAL,
-                     Ops.DEFINE_LOCAL, Ops.DEFINE_REG, Ops.LOAD}
+                     Ops.DEFINE_LOCAL, Ops.DEFINE_REG, Ops.LOAD, Ops.KERNEL}
 
 double_reshape = PatternMatcher([
   # RESHAPE on RESHAPE is the second reshape
@@ -343,7 +343,8 @@ pm_rangeify = pm_mops+PatternMatcher([
 
   # handle assign
   (UPat(Ops.INDEX, src=(UPat(Ops.ASSIGN, name="assign"),), allow_any_len=True, name="x"),
-    lambda x,assign: assign.replace(src=tuple([s.index(*x.src[1:]) for s in assign.src])+(assign.src[0],))),
+    lambda x,assign: assign.replace(src=tuple([s.index(*x.src[1:]) for s in assign.src])+(assign.src[0],)) \
+        if assign.src[1].op is not Ops.KERNEL else None),
 
   # move MAP through elementwise ALU / reduce. these are the items with cost
   (UPat(Ops.INDEX, src=(UPat(GroupOp.Elementwise.union(