diff --git a/tinygrad/tensor.py b/tinygrad/tensor.py
index 51c7321e09..7ea368540a 100644
--- a/tinygrad/tensor.py
+++ b/tinygrad/tensor.py
@@ -238,10 +238,10 @@ class Tensor(OpMixin):
       param = UOp.param(slot, self.dtype, self.uop.shard_shape, self.device).multi(self.uop.axis)
     else:
       param = UOp.param(slot, self.dtype, self.shape, self.device)
-    return Tensor(param, device=self.device)
+    return Tensor(param)
   def call(self, *lst:Tensor, fxn:Tensor|UOp, grad_fxn:Callable|None=None) -> Tensor:
     fret = (fxn.uop if isinstance(fxn, Tensor) else fxn).call(*[t.uop for t in (self,)+lst], grad_fxn=grad_fxn)
-    return Tensor(fret.gettuple(0), device=self.device)
+    return Tensor(fret.gettuple(0))
 
   def custom_kernel(self, *lst:Tensor, fxn:Callable, grad_fxn:Callable|None=None) -> list[Tensor]:
     """
@@ -324,7 +324,7 @@ class Tensor(OpMixin):
     """
     Returns a new tensor with the same data as this tensor, but detached from the autograd graph.
     """
-    return Tensor(self.uop.detach(), device=self.device, requires_grad=False)
+    return Tensor(self.uop.detach(), requires_grad=False)
 
   def _buffer(self) -> Buffer:
     from tinygrad.engine.realize import capturing
@@ -803,7 +803,7 @@ class Tensor(OpMixin):
     if kwargs.get("device") is not None: raise RuntimeError("cannot specify `device` on `*_like` of a multi device tensor")
     if self.uop.axis is None: return fxn(self.shape, *args, dtype=dtype, **kwargs).shard(self.device)
     stacked = UOp(Ops.MSTACK, dtype=dtype, src=tuple([fxn(self.uop.shard_shape, *args, device=d, dtype=dtype, **kwargs).uop for d in self.device]))
-    return Tensor(UOp.multi(stacked, axis=self.uop.axis), device=self.device, dtype=dtype)
+    return Tensor(UOp.multi(stacked, axis=self.uop.axis), dtype=dtype)
 
   def full_like(self, fill_value:PyConst, **kwargs) -> Tensor:
     """