diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index ed87315cea..2cb2934838 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -267,6 +267,8 @@ jobs:
       run: python -c "from tinygrad import Device; assert Device.DEFAULT == 'CPU', Device.DEFAULT"
     - name: Run unit tests
       run: CPU=1 python -m pytest -n=auto test/unit/ --durations=20
+    - name: Check SPEC=1
+      run: SPEC=1 python3 test/test_tiny.py
     - name: Run targetted tests on NULL backend
       run: NULL=1 python3 -m unittest test.test_multitensor.TestMultiTensor.test_data_parallel_resnet_train_step test/device/test_null.py
     # TODO: too slow
diff --git a/test/test_uops.py b/test/test_uops.py
index 0f22c56816..e1147ebd9b 100644
--- a/test/test_uops.py
+++ b/test/test_uops.py
@@ -568,5 +568,13 @@ class TestUOpChildren(unittest.TestCase):
     del c
     self.assertEqual(len(a.children), 0)
 
+class TestUOpRender(unittest.TestCase):
+  def test_render_vectorize_same(self):
+    u = UOp(Ops.VECTORIZE, src=(UOp.const(dtypes.int, 0), UOp.const(dtypes.int, 0), UOp.const(dtypes.int, 0)))
+    self.assertEqual(u.render(), "{0, ...}")
+  def test_render_vectorize_different(self):
+    u = UOp(Ops.VECTORIZE, src=(UOp.const(dtypes.int, 0), UOp.const(dtypes.int, 1), UOp.const(dtypes.int, 2)))
+    self.assertEqual(u.render(), "{0,1,2}")
+
 if __name__ == '__main__':
   unittest.main(verbosity=2)
diff --git a/tinygrad/uop/ops.py b/tinygrad/uop/ops.py
index e261e3bd9b..62f1cd32b8 100644
--- a/tinygrad/uop/ops.py
+++ b/tinygrad/uop/ops.py
@@ -1042,7 +1042,7 @@ if TRACK_MATCH_STATS or PROFILE:
 
 # *** simple graph rewrite engine ***
 
-SENTINEL = UOp(Ops.SENTINEL)
+with Context(SPEC=0): SENTINEL = UOp(Ops.SENTINEL)
 class RewriteNotReady(Exception): pass
 class BottomUpGate(Exception): pass
 class RewriteContext:
@@ -1197,7 +1197,7 @@ renderer = PatternMatcher([
   (UPat((Ops.INDEX, Ops.BUFFERIZE), name="x"), lambda x:
    UOp(Ops.NOOP, arg=''.join([f"[{strip_parens(y.arg)}]" for y in x.src[1:]])) if all(y.op is Ops.NOOP for y in x.src[1:]) else None),
   (UPat(Ops.VECTORIZE, src=UPat(Ops.NOOP), name="x"),
-   lambda x: UOp(Ops.NOOP, arg=f"[{','.join([y.arg for y in x.src])}]" if not all_same(x.src) else f"{len(x.src)}x[{x.src[0].arg}]")),
+   lambda x: UOp(Ops.NOOP, arg=f"{{{','.join([y.arg for y in x.src])}}}" if not all_same(x.src) else f"{{{x.src[0].arg}, ...}}")),
 ])
 renderer_infer = PatternMatcher([
   (UPat(Ops.MOD, src=UPat(Ops.NOOP), name="x"), lambda x: UOp(Ops.NOOP, arg=f"cmod({x.src[0].arg}, {x.src[1].arg})")),
diff --git a/tinygrad/uop/spec.py b/tinygrad/uop/spec.py
index 185ec25d8e..3b13e94d23 100644
--- a/tinygrad/uop/spec.py
+++ b/tinygrad/uop/spec.py
@@ -258,6 +258,9 @@ full_non_rangeify_spec = PatternMatcher([]) if RANGEIFY else PatternMatcher([
 ])
 
 full_spec = PatternMatcher([
+  # SENTINEL should never be in the graph
+  (UPat(Ops.SENTINEL), lambda: False),
+
   # Invalid must have type Index
   (UPat(Ops.CONST, arg=Invalid, name="x"), lambda x: x.dtype.scalar() == dtypes.index),
   # where on index in rhs position is fine