diff --git a/array_api_strict/_creation_functions.py b/array_api_strict/_creation_functions.py
index b34af5a..63bc9c4 100644
--- a/array_api_strict/_creation_functions.py
+++ b/array_api_strict/_creation_functions.py
@@ -107,8 +107,12 @@ def asarray(
 
     res = np.array(obj, dtype=_np_dtype, copy=copy)
 
-    # numpy default dtype may differ; if so, adjust the dtype
-    if dtype is None and device is not None:
+    # numpy default dtype may differ; if so, adjust the dtype---
+    # unless `obj` is already an array, potentially from some other library.
+    # In the latter case, `obj.dtype` is a thing, numpy has already done the
+    # conversion and `res.dtype` is the numpy analog of `obj.dtype`
+    # (if numpy failed to convert `obj`, it has already raised an exception).
+    if dtype is None and device is not None and not hasattr(obj, "dtype"):
         res_dtype = DType(res.dtype)
         # The dtype selected by Numpy might not be the default dtype
         # on this device. We thus find the default dtype for the dtype "kind", and
diff --git a/array_api_strict/tests/test_creation_functions.py b/array_api_strict/tests/test_creation_functions.py
index 7031120..06c5d87 100644
--- a/array_api_strict/tests/test_creation_functions.py
+++ b/array_api_strict/tests/test_creation_functions.py
@@ -368,6 +368,13 @@ def test_asarray_device_2():
     assert y.dtype == float64
 
 
+def test_asarray_device_1():
+    # regression test for https://github.com/data-apis/array-api-strict/issues/222
+    x = np.ones(3, dtype=np.float32)
+    y = asarray(x, device=Device('device1'))
+    assert y.dtype == float32
+
+
 @pytest.mark.parametrize("api_version", ['2021.12', '2022.12', '2023.12'])
 def from_dlpack_2023_12(api_version):
     if api_version != '2022.12':