diff --git a/test/test_multitensor.py b/test/test_multitensor.py
index e7c8aa401c..95d7825f8e 100644
--- a/test/test_multitensor.py
+++ b/test/test_multitensor.py
@@ -1273,19 +1273,20 @@ class TestMultiRamUsage(unittest.TestCase):
     _ = Tensor.zeros(self.N, self.N).contiguous().shard(devices_2, axis=0).contiguous().realize()
     self.assertUsed(self.N*self.N*4) # sharding should not increase total ram usage
 
-  def _test_matmul_half(self, devs):
+  def _test_matmul_half(self, dev_count:int):
     N = 32
     total_mem = {}
+    devs = tuple(f"NULL:{i}" for i in range(dev_count))
     for dtype in {dtypes.float, dtypes.half}:
       GlobalCounters.reset()
-      a = Tensor.empty((N, N), dtype=dtype).shard(devs, axis=0)
-      b = Tensor.empty((N, N), dtype=dtype).shard(devs, axis=None)
+      a = Tensor.empty((N, N), dtype=dtype, device=devs[0]).shard(devs, axis=0)
+      b = Tensor.empty((N, N), dtype=dtype, device=devs[0]).shard(devs, axis=None)
       (a @ b).realize()
       total_mem[dtype] = GlobalCounters.global_mem
     self.assertEqual(total_mem[dtypes.half], total_mem[dtypes.float] // 2)
 
-  def test_matmul_half(self): self._test_matmul_half(devices_2)
-  def test_matmul_half_alt(self): self._test_matmul_half(devices_4)
+  def test_matmul_half(self): self._test_matmul_half(dev_count=2)
+  def test_matmul_half_alt(self): self._test_matmul_half(dev_count=4)
 
 @unittest.skipIf(not_support_multi_device(), "need multi")
 class TestMultiFromUnrenderable(unittest.TestCase):