diff --git a/thinc/tests/backends/test_ops.py b/thinc/tests/backends/test_ops.py
index e095142b1..0d06d4833 100644
--- a/thinc/tests/backends/test_ops.py
+++ b/thinc/tests/backends/test_ops.py
@@ -8,8 +8,8 @@
 from packaging.version import Version
 from thinc.api import NumpyOps, CupyOps, Ops, get_ops
 from thinc.api import get_current_ops, use_ops
-from thinc.util import torch2xp, xp2torch, gpu_is_available
-from thinc.compat import has_torch, torch_version
+from thinc.util import torch2xp, xp2torch
+from thinc.compat import has_cupy_gpu, has_torch, torch_version
 from thinc.api import fix_random_seed
 from thinc.api import LSTM
 from thinc.types import Floats2d
@@ -26,7 +26,7 @@
 BLIS_OPS = NumpyOps(use_blis=True)
 CPU_OPS = [NUMPY_OPS, VANILLA_OPS]
 XP_OPS = [NUMPY_OPS]
-if CupyOps.xp is not None and gpu_is_available():
+if has_cupy_gpu:
     XP_OPS.append(CupyOps())
 ALL_OPS = XP_OPS + [VANILLA_OPS]
 
@@ -591,9 +591,7 @@ def test_backprop_seq2col_window_two(ops, dtype):
     ops.xp.testing.assert_allclose(seq, expected, atol=0.001, rtol=0.001)
 
 
-@pytest.mark.skipif(
-    CupyOps.xp is None or not gpu_is_available(), reason="needs GPU/CuPy"
-)
+@pytest.mark.skipif(not has_cupy_gpu, reason="needs GPU/CuPy")
 @pytest.mark.parametrize("nW", [1, 2])
 def test_large_seq2col_gpu_against_cpu(nW):
     cupy_ops = CupyOps()
@@ -615,9 +613,7 @@ def test_large_seq2col_gpu_against_cpu(nW):
     assert_allclose(cols, cols_gpu.get())
 
 
-@pytest.mark.skipif(
-    CupyOps.xp is None or not gpu_is_available(), reason="needs GPU/CuPy"
-)
+@pytest.mark.skipif(not has_cupy_gpu, reason="needs GPU/CuPy")
 @pytest.mark.parametrize("nW", [1, 2])
 def test_large_backprop_seq2col_gpu_against_cpu(nW):
     cupy_ops = CupyOps()
diff --git a/thinc/tests/layers/test_tensorflow_wrapper.py b/thinc/tests/layers/test_tensorflow_wrapper.py
index ff254ffc0..c1b85da3b 100644
--- a/thinc/tests/layers/test_tensorflow_wrapper.py
+++ b/thinc/tests/layers/test_tensorflow_wrapper.py
@@ -2,8 +2,8 @@
 import pytest
 from thinc.api import Adam, ArgsKwargs, Linear, Model, TensorFlowWrapper
 from thinc.api import get_current_ops, keras_subclass, tensorflow2xp, xp2tensorflow
-from thinc.util import gpu_is_available, to_categorical
-from thinc.compat import has_tensorflow
+from thinc.util import to_categorical
+from thinc.compat import has_cupy_gpu, has_tensorflow
 
 from ..util import check_input_converters, make_tempdir
 
@@ -359,7 +359,7 @@ def test_tensorflow_wrapper_to_cpu(tf_model):
 
 
 @pytest.mark.skipif(not has_tensorflow, reason="needs TensorFlow")
-@pytest.mark.skipif(not gpu_is_available(), reason="needs GPU/cupy")
+@pytest.mark.skipif(not has_cupy_gpu, reason="needs GPU/cupy")
 def test_tensorflow_wrapper_to_gpu(model, X):
     model.to_gpu(0)
 
diff --git a/thinc/tests/model/test_model.py b/thinc/tests/model/test_model.py
index 9ec71fc93..087e481c5 100644
--- a/thinc/tests/model/test_model.py
+++ b/thinc/tests/model/test_model.py
@@ -6,8 +6,7 @@
 from thinc.api import Shim, Softmax, chain, change_attr_values
 from thinc.api import concatenate, set_dropout_rate
 from thinc.api import use_ops, with_debug, wrap_model_recursive
-from thinc.util import gpu_is_available
-from thinc.compat import has_cupy
+from thinc.compat import has_cupy_gpu
 import numpy
 
 from ..util import make_tempdir
@@ -410,7 +409,7 @@ def test_model_gpu():
     import ml_datasets
 
     ops = "cpu"
-    if has_cupy and gpu_is_available():
+    if has_cupy_gpu:
         ops = "cupy"
 
     with use_ops(ops):
diff --git a/thinc/util.py b/thinc/util.py
index 16f0f0196..cdfdf4c1e 100644
--- a/thinc/util.py
+++ b/thinc/util.py
@@ -44,7 +44,7 @@ def fix_random_seed(seed: int = 0) -> None:  # pragma: no cover
     numpy.random.seed(seed)
     if has_torch:
         torch.manual_seed(seed)
-    if has_cupy and gpu_is_available():
+    if has_cupy_gpu:
         cupy.random.seed(seed)
         if has_torch and has_torch_gpu:
             torch.cuda.manual_seed_all(seed)
@@ -125,8 +125,8 @@ def to_numpy(data):  # pragma: no cover
 
 def set_active_gpu(gpu_id: int) -> "cupy.cuda.Device":  # pragma: no cover
     """Set the current GPU device for cupy and torch (if available)."""
-    if not gpu_is_available():
-        raise ValueError("No GPU devices detected")
+    if not has_cupy_gpu:
+        raise ValueError("No CUDA GPU devices detected")
 
     device = cupy.cuda.device.Device(gpu_id)
     device.use()
@@ -151,9 +151,7 @@ def require_cpu() -> bool:  # pragma: no cover
 
 def prefer_gpu(gpu_id: int = 0) -> bool:  # pragma: no cover
     """Use GPU if it's available. Returns True if so, False otherwise."""
-    from .backends.cupy_ops import CupyOps
-
-    if not gpu_is_available():
+    if not has_cupy_gpu:
         return False
     else:
         require_gpu(gpu_id=gpu_id)
@@ -163,8 +161,8 @@ def prefer_gpu(gpu_id: int = 0) -> bool:  # pragma: no cover
 def require_gpu(gpu_id: int = 0) -> bool:  # pragma: no cover
     from .backends import set_current_ops, CupyOps
 
-    if not gpu_is_available():
-        raise ValueError("No GPU devices detected")
+    if not has_cupy_gpu:
+        raise ValueError("No CUDA GPU devices detected")
 
     set_current_ops(CupyOps())
     set_active_gpu(gpu_id)