diff --git a/test/test_softmax_fusion.py b/test/test_softmax_fusion.py
index 660c567e0e..54a801f72c 100644
--- a/test/test_softmax_fusion.py
+++ b/test/test_softmax_fusion.py
@@ -2,7 +2,7 @@ import unittest
 import numpy as np
 from tinygrad import Tensor, GlobalCounters, Context, Device
 from tinygrad.dtype import DTypeLike, dtypes
-from tinygrad.helpers import DEBUG, get_single_element
+from tinygrad.helpers import DEBUG, get_single_element, RANGEIFY
 from tinygrad.engine.realize import lower_schedule_item
 from tinygrad.device import is_dtype_supported
 
@@ -39,6 +39,7 @@ class TestFuse(unittest.TestCase):
     np_multi = fxn(*args, **kwargs).numpy()
     np.testing.assert_allclose(np_single, np_multi, atol=atol)
 
+  @unittest.skipIf(0<RANGEIFY<2, "needs RANGEIFY>1")
   def test_fuse_norm(self):
     a = Tensor.rand(50,50).realize()
     self._test_fuse(lambda a: a / a.mean(axis=1), a)
@@ -47,6 +48,7 @@ class TestFuse(unittest.TestCase):
     a = Tensor.rand(50,50).realize()
     self._test_fuse(lambda a: a.argmax(axis=-1), a)
 
+  @unittest.skipIf(0<RANGEIFY<2, "needs RANGEIFY>1")
   def test_fuse_softmax(self):
     a = Tensor.rand(50,50).realize()
     self._test_fuse(lambda a: a.softmax(axis=-1), a)
@@ -57,6 +59,7 @@ class TestFuse(unittest.TestCase):
     self._test_fuse(lambda a,b: ((a@b).relu()+a).contiguous().softmax(axis=-1), a,b, allow_multiple=True)
 
   @unittest.skipUnless(is_dtype_supported(dtypes.float16, Device.DEFAULT), f"no float16 on {Device.DEFAULT}")
+  @unittest.skipIf(0<RANGEIFY<2, "needs RANGEIFY>1")
   def test_fuse_softmax_dtype(self):
     a = Tensor.rand(50,50).realize()
     self._test_fuse(lambda a: a.softmax(axis=-1, dtype='half'), a, atol=3e-4)
@@ -64,6 +67,7 @@ class TestFuse(unittest.TestCase):
   def test_fuse_arange_eye(self):
     self._test_fuse(lambda: Tensor.arange(10).reshape(10,1).expand(10,10) == Tensor.arange(10).reshape(1,10).expand(10,10))
 
+  @unittest.skipIf(0<RANGEIFY<2, "needs RANGEIFY>1")
   def test_double_gemm(self):
     N = 32
     with Context(TRACK_MATCH_STATS=0, DEBUG=0):
@@ -86,6 +90,7 @@ class TestFuse(unittest.TestCase):
       return (arange == idx).mul(vals).sum(-2, dtype=vals.dtype)
     self._test_fuse(embedding, a, atol=1e-5)
 
+  @unittest.skipIf(0<RANGEIFY<2, "needs RANGEIFY>1")
   def test_attention_kernel_count(self):
     wq = Tensor.empty(32, 32)
     wk = Tensor.empty(32, 32)
@@ -98,6 +103,7 @@ class TestFuse(unittest.TestCase):
     s = attn.schedule()
     self.assertEqual(len(s), 4) # 3 matmul and 1 attention
 
+  @unittest.skipIf(0<RANGEIFY<2, "needs RANGEIFY>1")
   def test_flash_attention(self):
     BS = 4
     HEADS = 2
@@ -165,6 +171,7 @@ class TestSoftmaxFusion(unittest.TestCase):
 
     np.testing.assert_allclose(sout.numpy(), out.numpy(), atol=3e-7)
 
+  @unittest.skipIf(0<RANGEIFY<2, "needs RANGEIFY>1")
   def test_auto_softmax(self):
     print("*** softmax ***")
     with Context(NOOPT=1, DEBUG=max(DEBUG.value, 2)):