diff --git a/test/backend/test_tensor.py b/test/backend/test_tensor.py
index 708264d9c3..bab2267d45 100644
--- a/test/backend/test_tensor.py
+++ b/test/backend/test_tensor.py
@@ -36,6 +36,16 @@ class TestTinygrad(unittest.TestCase):
     self.assertTrue(t.uop.has_buffer_identity())
     np.testing.assert_equal(t.numpy(), 2.0)
 
+  def test_to_deviceless_const(self):
+    t = Tensor(UOp.const(dtypes.float, 2.0))
+    self.assertIs(t.to(f"{Device.DEFAULT}:1"), t)
+    self.assertIs(t.to_(f"{Device.DEFAULT}:1"), t)
+
+  def test_shard_deviceless_const(self):
+    t = Tensor(UOp.const(dtypes.float, 2.0))
+    self.assertIs(t.shard((f"{Device.DEFAULT}:0", f"{Device.DEFAULT}:1")), t)
+    self.assertIs(t.shard_((f"{Device.DEFAULT}:0", f"{Device.DEFAULT}:1")), t)
+
   def test_plus_equals(self):
     a = Tensor.randn(10,10)
     b = Tensor.randn(10,10)
diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index 8bf49a1d89..f3b9496266 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -364,6 +364,7 @@ class Tensor(OpMixin):
     """
     Moves the tensor to the given device.
     """
+    if self.uop._device is None: return self
     if (device:=canonicalize_device(device)) == self.device: return self
     ret = Tensor(self.uop.copy_to_device(device), requires_grad=self.requires_grad)
     if self.grad is not None: ret.grad = self.grad.to(device)
@@ -386,6 +387,7 @@ class Tensor(OpMixin):
     print(t.shard((t.device, t.device), axis=1).uop)
     ```
     """
+    if self.uop._device is None: return self
     if not isinstance(self.device, str): raise RuntimeError("can't shard a multi-device tensor")
     if len(devices) == 1: return self.to(devices[0])
     devices = cast(tuple[str, ...], canonicalize_device(devices))