diff --git a/pixi.lock b/pixi.lock
index a1b4e648..4e7c877e 100644
--- a/pixi.lock
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   timestamp: 1771570027913
+- conda: https://prefix.dev/conda-forge/linux-64/scipy-1.15.2-py311h8f841c2_0.conda
+  sha256: 6d0902775e3ff96dd1d36ac627e03fe6c0b3d2159bb71e115dd16a1f31693b25
+  md5: 5ec0a1732a05376241e1e4c6d50e0e91
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - libgcc >=13
+  - libgfortran
+  - libgfortran5 >=13.3.0
+  - liblapack >=3.9.0,<4.0a0
+  - libstdcxx >=13
+  - numpy <2.5
+  - numpy >=1.19,<3
+  - numpy >=1.23.5
+  - python >=3.11,<3.12.0a0
+  - python_abi 3.11.* *_cp311
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 17193126
+  timestamp: 1739791897768
 - conda: https://prefix.dev/conda-forge/linux-64/scipy-1.16.3-py311hbe70eeb_2.conda
   sha256: a13084f1556674ea74de2ecbe50333d938dab8ef27f536408592ba312363c400
   md5: 1f9587850322d7d77ea14d4fee3d16d8
@@ -13206,6 +13255,29 @@ packages:
   - pkg:pypi/scipy?source=compressed-mapping
   size: 17099824
   timestamp: 1771880736635
+- conda: https://prefix.dev/conda-forge/linux-64/scipy-1.17.1-py313h0dc34c3_0.conda
+  sha256: 7933e9846630b6e5a720c607d0a5ed2154d5e15a21077240f1378d7fa4b5b7eb
+  md5: eb1b9c20267655bf049fb09c155c4d20
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - libgcc >=14
+  - libgfortran
+  - libgfortran5 >=14.3.0
+  - liblapack >=3.9.0,<4.0a0
+  - libstdcxx >=14
+  - numpy <2.7
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313t
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 17175042
+  timestamp: 1771880794357
 - conda: https://prefix.dev/conda-forge/linux-64/scipy-1.17.1-py314hf07bd8e_0.conda
   sha256: 1ae427836d7979779c9005388a05993a3addabcc66c4422694639a4272d7d972
   md5: d0510124f87c75403090e220db1e9d41
@@ -13224,10 +13296,33 @@ packages:
   - python >=3.14,<3.15.0a0
   - python_abi 3.14.* *_cp314
   license: BSD-3-Clause
+  license_family: BSD
   purls:
   - pkg:pypi/scipy?source=compressed-mapping
   size: 17225275
   timestamp: 1771880751368
+- conda: https://prefix.dev/conda-forge/osx-64/scipy-1.15.2-py311h0c91ca8_0.conda
+  sha256: 796252d7772df42edd29a45ae70eb18843a7e476d42c96c273cd6e677ec148c8
+  md5: 58c17d411ed0cd1220ed3e824a3efc82
+  depends:
+  - __osx >=10.13
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - libcxx >=18
+  - libgfortran >=5
+  - libgfortran5 >=13.2.0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.5
+  - numpy >=1.19,<3
+  - numpy >=1.23.5
+  - python >=3.11,<3.12.0a0
+  - python_abi 3.11.* *_cp311
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 15759628
+  timestamp: 1739792317052
 - conda: https://prefix.dev/conda-forge/osx-64/scipy-1.17.1-py311h556693a_0.conda
   sha256: 88c4a0f534b9ca58aea2341a5aff706e66582f09a46425512f088aaaecbca938
   md5: 1f0877b391f47bae72e67b066337c9e5
@@ -13249,6 +13344,28 @@ packages:
   - pkg:pypi/scipy?source=compressed-mapping
   size: 15306181
   timestamp: 1771880807305
+- conda: https://prefix.dev/conda-forge/osx-64/scipy-1.17.1-py313habc7bd5_0.conda
+  sha256: 8abeb45a97e8300e39846e931b7d4a01ad8c85ffa3a3f4a319397875fad3914a
+  md5: 1d5fedd4e2126df7ba1e8182ba74e72a
+  depends:
+  - __osx >=11.0
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - libcxx >=19
+  - libgfortran
+  - libgfortran5 >=14.3.0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.7
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313t
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 15627768
+  timestamp: 1771881574707
 - conda: https://prefix.dev/conda-forge/osx-64/scipy-1.17.1-py314h5727af0_0.conda
   sha256: 115267259f529f1539c6ab1098a18ca488fac02542fa9ca657a7dd46bd9ea675
   md5: adbed17bd17ac00193e6dce1f1a37781
@@ -13266,10 +13383,34 @@ packages:
   - python >=3.14,<3.15.0a0
   - python_abi 3.14.* *_cp314
   license: BSD-3-Clause
+  license_family: BSD
   purls:
   - pkg:pypi/scipy?source=compressed-mapping
   size: 15400833
   timestamp: 1771881194227
+- conda: https://prefix.dev/conda-forge/osx-arm64/scipy-1.15.2-py311h0675101_0.conda
+  sha256: bc3e873e85c55deaaad446c410d9001d12a133c1b48fa2cb0050b4f46f926aa3
+  md5: df904770f3fdb6c0265a09cdc22acf54
+  depends:
+  - __osx >=11.0
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - libcxx >=18
+  - libgfortran >=5
+  - libgfortran5 >=13.2.0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.5
+  - numpy >=1.19,<3
+  - numpy >=1.23.5
+  - python >=3.11,<3.12.0a0
+  - python >=3.11,<3.12.0a0 *_cpython
+  - python_abi 3.11.* *_cp311
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 14569129
+  timestamp: 1739792318601
 - conda: https://prefix.dev/conda-forge/osx-arm64/scipy-1.17.1-py311he9931d0_0.conda
   sha256: f212138a7eb86cf8bcdb46f003ae552967cd7e48d2c539f7f8dd6e800c74b70d
   md5: 40606bef4834281d5f746626338829dc
@@ -13292,6 +13433,29 @@ packages:
   - pkg:pypi/scipy?source=compressed-mapping
   size: 14107248
   timestamp: 1771880859933
+- conda: https://prefix.dev/conda-forge/osx-arm64/scipy-1.17.1-py313hf3ca9c9_0.conda
+  sha256: 683b1d029ce027a9ca059898073d3c450fb049cab2104841cacfc522db33109e
+  md5: 0708282b2709afd240f7d5b8db8c6135
+  depends:
+  - __osx >=11.0
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - libcxx >=19
+  - libgfortran
+  - libgfortran5 >=14.3.0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.7
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.13,<3.14.0a0
+  - python >=3.13,<3.14.0a0 *_cp313t
+  - python_abi 3.13.* *_cp313t
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 14231641
+  timestamp: 1771880960734
 - conda: https://prefix.dev/conda-forge/osx-arm64/scipy-1.17.1-py314hfc1f868_0.conda
   sha256: 6ca2abcaff2cd071aabaabd82b10a87fc7de3a4619f6c98820cc28e90cc2cb20
   md5: 7806ce54b78b0b11517b465a3398e910
@@ -13310,10 +13474,137 @@ packages:
   - python >=3.14,<3.15.0a0 *_cp314
   - python_abi 3.14.* *_cp314
   license: BSD-3-Clause
+  license_family: BSD
   purls:
   - pkg:pypi/scipy?source=compressed-mapping
   size: 13986990
   timestamp: 1771881110844
+- conda: https://prefix.dev/conda-forge/win-64/scipy-1.15.2-py311h99d06ae_0.conda
+  sha256: 62ae1a1e02c919513213351474d1c72480fb70388a345fa81f1c95fa822d98bf
+  md5: c7ec15b5ea6a27bb71af2ea5f7c97cbb
+  depends:
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.5
+  - numpy >=1.19,<3
+  - numpy >=1.23.5
+  - python >=3.11,<3.12.0a0
+  - python_abi 3.11.* *_cp311
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 15487645
+  timestamp: 1739793313482
+- conda: https://prefix.dev/conda-forge/win-64/scipy-1.16.3-py311h9c22a71_2.conda
+  sha256: 49129601dc89d49742d342ace70f4ec0127a5eb24a50d66f95f91db01b3a23d5
+  md5: 4b663de0f0c8ac0fbb4a4d9ee8536b0f
+  depends:
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.6
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.11,<3.12.0a0
+  - python_abi 3.11.* *_cp311
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 15129579
+  timestamp: 1766109708812
+- conda: https://prefix.dev/conda-forge/win-64/scipy-1.16.3-py314h221f224_2.conda
+  sha256: 99d6198dc05171610073083c9d218d2a9adfa756659b391183d21cca55f888f1
+  md5: b600c47282ee91e492b89f65708a5c9a
+  depends:
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.6
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.14,<3.15.0a0
+  - python_abi 3.14.* *_cp314
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 15082636
+  timestamp: 1766109482825
+- conda: https://prefix.dev/conda-forge/win-64/scipy-1.17.1-py311h9c22a71_0.conda
+  sha256: f8b0eed844e466434f115e5cd7da71b59e6939c08fcf42ef52fa5b3f84b20c94
+  md5: 24047b0ff1fa264427c456e4c7f68283
+  depends:
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.7
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.11,<3.12.0a0
+  - python_abi 3.11.* *_cp311
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=compressed-mapping
+  size: 15280874
+  timestamp: 1771881523220
+- conda: https://prefix.dev/conda-forge/win-64/scipy-1.17.1-py313hff732fb_0.conda
+  sha256: 7b351554b9256468ebcd0233c5ec6c74a3384a4d1298399a48c048037a56ff6c
+  md5: cf669ec96a5d028c8fa2bd1620ad50cb
+  depends:
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.7
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313t
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=hash-mapping
+  size: 15201678
+  timestamp: 1771881882965
+- conda: https://prefix.dev/conda-forge/win-64/scipy-1.17.1-py314h221f224_0.conda
+  sha256: d9a7b6d3a306195eef4db814614a74746aae4b63e570f6db15769bd28d19a957
+  md5: cfcd38938ee0137f4bf0ca824dfb0887
+  depends:
+  - libblas >=3.9.0,<4.0a0
+  - libcblas >=3.9.0,<4.0a0
+  - liblapack >=3.9.0,<4.0a0
+  - numpy <2.7
+  - numpy >=1.23,<3
+  - numpy >=1.25.2
+  - python >=3.14,<3.15.0a0
+  - python_abi 3.14.* *_cp314
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/scipy?source=compressed-mapping
+  size: 14970549
+  timestamp: 1771881565717
 - conda: https://prefix.dev/conda-forge/noarch/setuptools-82.0.0-pyh332efcf_0.conda
   sha256: fd7201e38e38bf7f25818d624ca8da97b8998957ca9ae3fb7fdc9c17e6b25fcd
   md5: 1d00d46c634177fc8ede8b99d6089239
diff --git a/pyproject.toml b/pyproject.toml
index 15e4d8c8..1bd40c6f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -134,6 +134,7 @@ pytest-cov = ">=7.0.0"
 hypothesis = ">=6.151.2"
 array-api-strict = ">=2.4.1,<2.5"
 numpy = ">=1.22.0"
+scipy = ">=1.15.2,<2"
 
 [tool.pixi.feature.tests.tasks]
 tests = { cmd = "pytest -v", description = "Run tests" }
diff --git a/src/array_api_extra/testing.py b/src/array_api_extra/testing.py
index d40fea1a..9f2b0d38 100644
--- a/src/array_api_extra/testing.py
+++ b/src/array_api_extra/testing.py
@@ -10,8 +10,9 @@
 import enum
 import warnings
 from collections.abc import Callable, Generator, Iterator, Sequence
-from functools import wraps
-from types import ModuleType
+from functools import update_wrapper, wraps
+from inspect import getattr_static
+from types import FunctionType, ModuleType
 from typing import TYPE_CHECKING, Any, ParamSpec, TypeVar, cast
 
 from ._lib._utils._compat import is_dask_namespace, is_jax_namespace
@@ -48,8 +49,21 @@ class Deprecated(enum.Enum):
 DEPRECATED = Deprecated.DEPRECATED
 
 
+def _clone_function(f: Callable[..., Any]) -> Callable[..., Any]:
+    """Returns a clone of an existing function."""
+    f_new = FunctionType(
+        f.__code__,
+        f.__globals__,
+        name=f.__name__,
+        argdefs=f.__defaults__,
+        closure=f.__closure__,
+    )
+    f_new.__kwdefaults__ = f.__kwdefaults__
+    return update_wrapper(f_new, f)
+
+
 def lazy_xp_function(
-    func: Callable[..., Any],
+    func: Callable[..., Any] | tuple[type, str],
     *,
     allow_dask_compute: bool | int = False,
     jax_jit: bool = True,
@@ -69,8 +83,9 @@ def lazy_xp_function(
 
     Parameters
     ----------
-    func : callable
-        Function to be tested.
+    func : callable | tuple[type, str]
+        Function to be tested, or a tuple containing an (uninstantiated) class and a
+        method name to specify a class method to be tested.
     allow_dask_compute : bool | int, optional
         Whether `func` is allowed to internally materialize the Dask graph, or maximum
         number of times it is allowed to do so. This is typically triggered by
@@ -204,15 +219,49 @@ def test_myfunc(xp):
             DeprecationWarning,
             stacklevel=2,
         )
-    tags = {
+    tags: dict[str, bool | int | type] = {
         "allow_dask_compute": allow_dask_compute,
         "jax_jit": jax_jit,
     }
 
+    if isinstance(func, tuple):
+        # Replace the method with a clone before adding tags
+        # to avoid adding unwanted tags to a parent method when
+        # the method was inherited from a parent class.
+        # Note: can't just accept an unbound method `cls.method_name` because in
+        # case of inheritance it would be impossible to attribute it to the child class.
+        # This also makes it so tagged methods will appear in their class's ``__dict__``
+        # and thus findable by ``iter_tagged_modules`` below.
+        cls, method_name = func
+        # The method might be a staticmethod or classmethod so we need to do a dance
+        # to ensure that this is preserved.
+        raw_attr = getattr_static(cls, method_name)
+        method = getattr(cls, method_name)
+        if isinstance(raw_attr, classmethod):
+            method = method.__func__
+        cloned_method = _clone_function(method)
+
+        method_to_set: Any
+        if isinstance(raw_attr, staticmethod):
+            method_to_set = staticmethod(cloned_method)
+        elif isinstance(raw_attr, classmethod):
+            method_to_set = classmethod(cloned_method)
+        else:
+            method_to_set = cloned_method
+
+        setattr(cls, method_name, method_to_set)
+        f = getattr(cls, method_name)
+        if isinstance(raw_attr, classmethod):
+            f = f.__func__
+        # Annotate that cls owns this method so we can check that later.
+        tags["owner"] = cls
+    else:
+        f = func
+
     try:
-        func._lazy_xp_function = tags  # type: ignore[attr-defined]  # pylint: disable=protected-access  # pyright: ignore[reportFunctionMemberAccess]
+        f._lazy_xp_function = tags  # pylint: disable=protected-access  # pyright: ignore[reportFunctionMemberAccess]
     except AttributeError:  # @cython.vectorize
-        _ufuncs_tags[func] = tags
+        _ufuncs_tags[f] = tags
 
 
 def patch_lazy_xp_functions(
@@ -224,10 +273,11 @@ def patch_lazy_xp_functions(
     """
     Test lazy execution of functions tagged with :func:`lazy_xp_function`.
 
-    If ``xp==jax.numpy``, search for all functions which have been tagged with
-    :func:`lazy_xp_function` in the globals of the module that defines the current test,
-    as well as in the ``lazy_xp_modules`` list in the globals of the same module,
-    and wrap them with :func:`jax.jit`. Unwrap them at the end of the test.
+    If ``xp==jax.numpy``, search for all functions and methods which have been tagged
+    with :func:`lazy_xp_function` in the globals of the module that defines the current
+    test, as well as in the ``lazy_xp_modules`` list in the globals of the same module,
+    and wrap them with :func:`jax.jit`.
+    Unwrap them at the end of the test.
 
     If ``xp==dask.array``, wrap the functions with a decorator that disables
     ``compute()`` and ``persist()`` and ensures that exceptions and warnings are raised
@@ -271,18 +321,34 @@ def xp(request):
     the example above.
     """
     mod = cast(ModuleType, request.module)
-    mods = [mod, *cast(list[ModuleType], getattr(mod, "lazy_xp_modules", []))]
-
-    to_revert: list[tuple[ModuleType, str, object]] = []
-
-    def temp_setattr(mod: ModuleType, name: str, func: object) -> None:
+    search_targets: list[ModuleType | type] = [
+        mod,
+        *cast(list[ModuleType], getattr(mod, "lazy_xp_modules", [])),
+    ]
+    # Also search for classes within the above modules which have had lazy_xp_function
+    # applied to methods through ``lazy_xp_function((cls, method_name))`` syntax.
+    # We might end up adding classes incidentally imported into modules, so using a
+    # set here to cut down on potential redundancy.
+    classes: set[type] = set()
+    for target in search_targets:
+        for obj in target.__dict__.values():
+            if isinstance(obj, type):
+                classes.add(obj)
+    search_targets.extend(classes)
+
+    to_revert: list[tuple[ModuleType | type, str, object]] = []
+
+    def temp_setattr(target: ModuleType | type, name: str, func: object) -> None:
         """
         Variant of monkeypatch.setattr, which allows monkey-patching only selected
         parameters of a test so that pytest-run-parallel can run on the remainder.
         """
-        assert hasattr(mod, name)
-        to_revert.append((mod, name, getattr(mod, name)))
-        setattr(mod, name, func)
+        assert hasattr(target, name)
+        # Need getattr_static because the attr could be a staticmethod or other
+        # descriptor and we don't want that to be stripped away.
+        original = getattr_static(target, name)
+        to_revert.append((target, name, original))
+        setattr(target, name, func)
 
     if monkeypatch is not None:
         warnings.warn(
@@ -298,10 +364,19 @@ def temp_setattr(mod: ModuleType, name: str, func: object) -> None:
         temp_setattr = monkeypatch.setattr  # type: ignore[assignment]  # pyright: ignore[reportAssignmentType]
 
     def iter_tagged() -> Iterator[
-        tuple[ModuleType, str, Callable[..., Any], dict[str, Any]]
+        tuple[ModuleType | type, str, Any, Callable[..., Any], dict[str, Any]]
     ]:
-        for mod in mods:
-            for name, func in mod.__dict__.items():
+        for target in search_targets:
+            for name, attr in target.__dict__.items():
+                # attr might be a staticmethod or classmethod. If so we need
+                # to peel it back and wrap the underlying function and later
+                # make sure not to accidentally replace it with a regular
+                # method.
+                func: Any = (
+                    attr.__func__
+                    if isinstance(attr, (staticmethod, classmethod))
+                    else attr
+                )
                 tags: dict[str, Any] | None = None
                 with contextlib.suppress(AttributeError):
                     tags = func._lazy_xp_function  # pylint: disable=protected-access
@@ -309,23 +384,49 @@ def iter_tagged() -> Iterator[
                     with contextlib.suppress(KeyError, TypeError):
                         tags = _ufuncs_tags[func]
                 if tags is not None:
-                    yield mod, name, func, tags
-
+                    if isinstance(target, type) and tags.get("owner") is not target:
+                        # There's a common pattern to wrap functions in namespace
+                        # classes to bypass lazy_xp_function like this:
+                        #
+                        # class naked:
+                        #     myfunc = mymodule.myfunc
+                        #
+                        # To ensure this still works when checking for tags in
+                        # attributes of classes, ensure that target is the actual
+                        # owning class where func was defined.
+                        continue
+                    # put attr, and func in the outputs so we can later tell
+                    # if this was a staticmethod or classmethod.
+                    yield target, name, attr, func, tags
+
+    wrapped: Any
     if is_dask_namespace(xp):
-        for mod, name, func, tags in iter_tagged():
+        for target, name, attr, func, tags in iter_tagged():
             n = tags["allow_dask_compute"]
             if n is True:
                 n = 1_000_000
             elif n is False:
                 n = 0
             wrapped = _dask_wrap(func, n)
-            temp_setattr(mod, name, wrapped)
+            # If we're dealing with a staticmethod or classmethod, make
+            # sure things stay that way.
+            if isinstance(attr, staticmethod):
+                wrapped = staticmethod(wrapped)
+            elif isinstance(attr, classmethod):
+                wrapped = classmethod(wrapped)
+            temp_setattr(target, name, wrapped)
 
     elif is_jax_namespace(xp):
-        for mod, name, func, tags in iter_tagged():
+        for target, name, attr, func, tags in iter_tagged():
             if tags["jax_jit"]:
                 wrapped = jax_autojit(func)
-                temp_setattr(mod, name, wrapped)
+                # If we're dealing with a staticmethod or classmethod, make
+                # sure things stay that way.
+                if isinstance(attr, staticmethod):
+                    wrapped = staticmethod(wrapped)
+                elif isinstance(attr, classmethod):
+                    wrapped = classmethod(wrapped)
+                temp_setattr(target, name, wrapped)
 
     # We can't just decorate patch_lazy_xp_functions with
     # @contextlib.contextmanager because it would not work with the
@@ -335,8 +436,8 @@ def revert_on_exit() -> Generator[None]:
         try:
             yield
         finally:
-            for mod, name, orig_func in to_revert:
-                setattr(mod, name, orig_func)
+            for target, name, orig_func in to_revert:
+                setattr(target, name, orig_func)
 
     return revert_on_exit()
 
diff --git a/tests/test_testing.py b/tests/test_testing.py
index 7e72ffbf..b70de734 100644
--- a/tests/test_testing.py
+++ b/tests/test_testing.py
@@ -1,9 +1,10 @@
 from collections.abc import Callable, Iterator
 from types import ModuleType
-from typing import cast
+from typing import Any, cast, final
 
 import numpy as np
 import pytest
+from typing_extensions import override
 
 from array_api_extra._lib._backends import Backend
 from array_api_extra._lib._testing import (
@@ -321,6 +322,128 @@ def test_lazy_xp_function_cython_ufuncs(xp: ModuleType, library: Backend):
         xp_assert_equal(cast(Array, erf(x)), xp.asarray([1.0, 1.0]))
 
 
+class A:
+    def __init__(self, x: Array):
+        xp = array_namespace(x)
+        self._xp: ModuleType = xp
+        self.x: Any = np.asarray(x)
+
+    def f(self, y: Array) -> Array:
+        return self._xp.asarray(np.matmul(self.x, np.asarray(y)))
+
+    def g(self, y: Array, z: Array) -> Array:
+        return self.f(y) + self.f(z)
+
+    def h(self, y: Array) -> bool:
+        return bool(self._xp.any(y))
+
+
+class B(A):
+    @override
+    def __init__(self, x: Array):  # pyright: ignore[reportMissingSuperCall]
+        xp = array_namespace(x)
+        self._xp: ModuleType = xp
+        self.x: Any = xp.asarray(x)
+
+    @override
+    def f(self, y: Array) -> Array:
+        return self._xp.matmul(self.x, y)
+
+    @staticmethod
+    def k(y: Array) -> "B":
+        return B(2.0 * y)
+
+    @staticmethod
+    def j(y: Array) -> "B":
+        xp = array_namespace(y)
+        y = xp.asarray(y)
+        if bool(xp.any(y)):
+            return B(y)
+        return B(y + 1.0)
+
+    @classmethod
+    def w(cls, y: Array) -> "B":
+        xp = array_namespace(y)
+        y = xp.asarray(y)
+        if bool(xp.any(y)):
+            return B(y)
+        return B(y + 1.0)
+
+
+@final
+class eager:
+    # this needs to be a staticmethod to appease the type checker
+    non_materializable5 = staticmethod(non_materializable5)
+
+
+lazy_xp_function((B, "g"))
+lazy_xp_function((B, "h"))
+lazy_xp_function((B, "k"))
+lazy_xp_function((B, "j"))
+lazy_xp_function((B, "w"))
+
+
+class TestLazyXpFunctionClasses:
+    def test_parent_method_not_tagged(self):
+        assert hasattr(B.g, "_lazy_xp_function")
+        assert not hasattr(A.g, "_lazy_xp_function")
+
+    @pytest.mark.skip_xp_backend(Backend.SPARSE, reason="converts to NumPy")
+    @pytest.mark.skip_xp_backend(Backend.CUPY, reason="converts to NumPy")
+    @pytest.mark.skip_xp_backend(Backend.JAX_GPU, reason="converts to NumPy")
+    @pytest.mark.skip_xp_backend(Backend.TORCH_GPU, reason="converts to NumPy")
+    def test_lazy_xp_function_classes(self, xp: ModuleType, library: Backend):
+        x = xp.asarray([1.1, 2.2, 3.3])
+        y = xp.asarray([1.0, 2.0, 3.0])
+        foo = A(x)
+        bar = B(x)
+
+        if library.like(Backend.JAX):
+            with pytest.raises(
+                TypeError, match="Attempted boolean conversion of traced array"
+            ):
+                assert bar.h(y)
+
+        assert foo.h(y)
+
+    def test_static_methods_preserved(self, xp: ModuleType):
+        # Tests that static methods stay static methods when
+        # lazy_xp_function is applied.
+        x = xp.asarray([1.1, 2.2, 3.3])
+        foo = B(x)
+        bar = foo.k(x)
+        xp_assert_equal(bar.x, 2.0 * foo.x)
+
+    @pytest.mark.skip_xp_backend(Backend.DASK, reason="calls dask.compute()")
+    def test_static_methods_wrapped(self, xp: ModuleType, library: Backend):
+        x = xp.asarray([1.1, 2.2, 3.3])
+        foo = B(x)
+
+        if library.like(Backend.JAX):
+            with pytest.raises(
+                TypeError, match="Attempted boolean conversion of traced array"
+            ):
+                assert isinstance(foo.j(x), B)
+        else:
+            assert isinstance(foo.j(x), B)
+
+    @pytest.mark.skip_xp_backend(Backend.DASK, reason="calls dask.compute()")
+    def test_class_methods_wrapped(self, xp: ModuleType, library: Backend):
+        x = xp.asarray([1.1, 2.2, 3.3])
+        if library.like(Backend.JAX):
+            with pytest.raises(
+                TypeError, match="Attempted boolean conversion of traced array"
+            ):
+                assert isinstance(B.w(x), B)
+        else:
+            assert isinstance(B.w(x), B)
+
+    def test_circumvention(self, xp: ModuleType):
+        x = xp.asarray([1.0, 2.0])
+        y = eager.non_materializable5(x)
+        xp_assert_equal(y, x)
+
+
 def dask_raises(x: Array) -> Array:
     def _raises(x: Array) -> Array:
         # Test that map_blocks doesn't eagerly call the function;