diff --git a/array_api_compat/common/_aliases.py b/array_api_compat/common/_aliases.py
index 8ea9162a..00490e2c 100644
--- a/array_api_compat/common/_aliases.py
+++ b/array_api_compat/common/_aliases.py
@@ -7,7 +7,7 @@
 import inspect
 from typing import TYPE_CHECKING, Any, NamedTuple, Optional, Sequence, cast
 
-from ._helpers import _check_device, array_namespace
+from ._helpers import _device_ctx, array_namespace
 from ._helpers import device as _get_device
 from ._helpers import is_cupy_namespace as _is_cupy_namespace
 from ._typing import Array, Device, DType, Namespace
@@ -32,8 +32,8 @@ def arange(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.arange(start, stop=stop, step=step, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device):
+        return xp.arange(start, stop=stop, step=step, dtype=dtype, **kwargs)
 
 
 def empty(
@@ -44,8 +44,8 @@ def empty(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.empty(shape, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device):
+        return xp.empty(shape, dtype=dtype, **kwargs)
 
 
 def empty_like(
@@ -57,8 +57,8 @@ def empty_like(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.empty_like(x, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device, like=x):
+        return xp.empty_like(x, dtype=dtype, **kwargs)
 
 
 def eye(
@@ -72,8 +72,8 @@ def eye(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.eye(n_rows, M=n_cols, k=k, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device):
+        return xp.eye(n_rows, M=n_cols, k=k, dtype=dtype, **kwargs)
 
 
 def full(
@@ -85,8 +85,8 @@ def full(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.full(shape, fill_value, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device):
+        return xp.full(shape, fill_value, dtype=dtype, **kwargs)
 
 
 def full_like(
@@ -99,8 +99,8 @@ def full_like(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.full_like(x, fill_value, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device, like=x):
+        return xp.full_like(x, fill_value, dtype=dtype, **kwargs)
 
 
 def linspace(
@@ -115,8 +115,8 @@ def linspace(
     endpoint: bool = True,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.linspace(start, stop, num, dtype=dtype, endpoint=endpoint, **kwargs)
+    with _device_ctx(xp, device):
+        return xp.linspace(start, stop, num, dtype=dtype, endpoint=endpoint, **kwargs)
 
 
 def ones(
@@ -127,8 +127,8 @@ def ones(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.ones(shape, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device):
+        return xp.ones(shape, dtype=dtype, **kwargs)
 
 
 def ones_like(
@@ -140,8 +140,8 @@ def ones_like(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.ones_like(x, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device, like=x):
+        return xp.ones_like(x, dtype=dtype, **kwargs)
 
 
 def zeros(
@@ -152,8 +152,8 @@ def zeros(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.zeros(shape, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device):
+        return xp.zeros(shape, dtype=dtype, **kwargs)
 
 
 def zeros_like(
@@ -165,8 +165,8 @@ def zeros_like(
     device: Device | None = None,
     **kwargs: object,
 ) -> Array:
-    _check_device(xp, device)
-    return xp.zeros_like(x, dtype=dtype, **kwargs)
+    with _device_ctx(xp, device, like=x):
+        return xp.zeros_like(x, dtype=dtype, **kwargs)
 
 
 # np.unique() is split into four functions in the array API:
diff --git a/array_api_compat/common/_helpers.py b/array_api_compat/common/_helpers.py
index 77175d0d..ca4d16d0 100644
--- a/array_api_compat/common/_helpers.py
+++ b/array_api_compat/common/_helpers.py
@@ -8,6 +8,7 @@
 
 from __future__ import annotations
 
+import contextlib
 import inspect
 import math
 import sys
@@ -657,26 +658,42 @@ def your_function(x, y):
 get_namespace = array_namespace
 
 
-def _check_device(bare_xp: Namespace, device: Device) -> None:  # pyright: ignore[reportUnusedFunction]
-    """
-    Validate dummy device on device-less array backends.
+def _device_ctx(
+    bare_xp: Namespace, device: Device, like: Array | None = None
+) -> Generator[None]:
+    """Context manager which changes the current device in CuPy.
 
-    Notes
-    -----
-    This function is also invoked by CuPy, which does have multiple devices
-    if there are multiple GPUs available.
-    However, CuPy multi-device support is currently impossible
-    without using the global device or a context manager:
-
-    https://github.com/data-apis/array-api-compat/pull/293
+    Used internally by array creation functions in common._aliases.
     """
-    if bare_xp is sys.modules.get("numpy"):
-        if device not in ("cpu", None):
+    if device is None:
+        if like is None:
+            return contextlib.nullcontext()    
+        device = _device(like)
+
+    if bare_xp is sys.modules.get('numpy'):
+        if device != "cpu":
             raise ValueError(f"Unsupported device for NumPy: {device!r}")
+        return contextlib.nullcontext()
 
-    elif bare_xp is sys.modules.get("dask.array"):
-        if device not in ("cpu", _DASK_DEVICE, None):
+    if bare_xp is sys.modules.get('dask.array'):
+        if device not in ("cpu", _DASK_DEVICE):
             raise ValueError(f"Unsupported device for Dask: {device!r}")
+        return contextlib.nullcontext()
+
+    if bare_xp is sys.modules.get('cupy'):
+        if not isinstance(device, bare_xp.cuda.Device):
+            raise TypeError(f"device is not a cupy.cuda.Device: {device!r}")
+        return device
+
+    # PyTorch doesn't have a "current device" context manager and you
+    # can't use array creation functions from common._aliases.
+    raise AssertionError("unreachable")  # pragma: nocover
+
+
+def _check_device(bare_xp: Namespace, device: Device) -> None:
+    """Validate dummy device on device-less array backends."""
+    with _device_ctx(bare_xp, device):
+        pass
 
 
 # Placeholder object to represent the dask device
diff --git a/array_api_compat/cupy/_aliases.py b/array_api_compat/cupy/_aliases.py
index adb74bff..c1ea532c 100644
--- a/array_api_compat/cupy/_aliases.py
+++ b/array_api_compat/cupy/_aliases.py
@@ -86,7 +86,8 @@ def asarray(
     See the corresponding documentation in the array library and/or the array API
     specification for more details.
     """
-    with cp.cuda.Device(device):
+    like = obj if isinstance(obj, cp.ndarray) else None
+    with _helpers._device_ctx(cp, device, like=like):
         if copy is None:
             return cp.asarray(obj, dtype=dtype, **kwargs)
         else: