diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 667748f1..5fc017a1 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -89,6 +89,8 @@ jobs:
               no-coverage: true,
               x64_runner: ubuntu-latest,
             }
+          - environment: tests-mlx
+            runs-on: macos-15
           - {environment: tests-run-deps, task: tests-run-deps-cov}
         exclude:
           - {environment: tests-numpy1, platform: windows} # data-apis/array-api-extra#901
diff --git a/pixi.lock b/pixi.lock
index 083d931c..13a72d25 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -6,14 +6,6 @@ platforms:
   - __linux=4.18
   - __glibc=2.28
   - __archspec=0=x86_64
-- name: linux-64-cuda-12-9
-  subdir: linux-64
-  virtual-packages:
-  - __cuda=12.9
-  - __unix=0=0
-  - __linux=4.18
-  - __glibc=2.28
-  - __archspec=0=x86_64
 - name: linux-aarch64
   virtual-packages:
   - __unix=0=0
@@ -30,16 +22,30 @@ platforms:
   - __unix=0=0
   - __osx=13.0
   - __archspec=0=m1
-- name: win-64
+- name: p1
+  subdir: osx-arm64
   virtual-packages:
-  - __win=10.0
+  - __osx=14.5
+  - __unix=0=0
+  - __archspec=0=m1
+- name: p2
+  subdir: linux-64
+  virtual-packages:
+  - __cuda=12.9
+  - __unix=0=0
+  - __linux=4.18
+  - __glibc=2.28
   - __archspec=0=x86_64
-- name: win-64-cuda-12-9
+- name: p3
   subdir: win-64
   virtual-packages:
   - __cuda=12.9
   - __win=10.0
   - __archspec=0=x86_64
+- name: win-64
+  virtual-packages:
+  - __win=10.0
+  - __archspec=0=x86_64
 environments:
   default:
     channels:
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-      - conda: https://prefix.dev/conda-forge/linux-64/libpython-3.14.7-hdc7f604_104_cp314.conda
-      - conda: https://prefix.dev/conda-forge/linux-64/libsqlite-3.53.4-h13e7031_1.conda
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   - cuda-nvrtc >=12.9.86,<13.0a0
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-  - openssl >=3.5.7,<4.0a0
-  - libzlib >=1.3.2,<2.0a0
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   license: Apache-2.0
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+  md5: 47b1b869b1ab505c05a35f7afc1cbbf9
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   - libcusparse-dev
   - __glibc >=2.17,<3.0.a0
-  - libstdcxx >=15
   - libgcc >=15
+  - libstdcxx >=15
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-  - libcurand >=10.3.10.19,<11.0a0
-  - libabseil >=20260107.1,<20260108.0a0
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-  - cuda-cupti >=12.9.79,<13.0a0
   - cuda-nvrtc >=12.9.86,<13.0a0
+  - libzlib >=1.3.2,<2.0a0
   - libcusparse >=12.5.10.65,<13.0a0
+  - libcufft >=11.4.1.4,<12.0a0
   - onednn >=3.12,<4.0a0
-  - python_abi 3.14.* *_cp314
+  - libcublas >=12.9.2.10,<13.0a0
+  - cuda-cupti >=12.9.79,<13.0a0
+  - libcusolver >=11.7.5.82,<12.0a0
+  - nccl >=2.30.7.1,<3.0a0
+  - libabseil >=20260107.1,<20260108.0a0
+  - libabseil * cxx17*
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+  - flatbuffers >=25.9.23,<25.9.24.0a0
   - cuda-nvtx >=12.9.79,<13.0a0
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-  - libcufft >=11.4.1.4,<12.0a0
-  - libcusolver >=11.7.5.82,<12.0a0
+  - python_abi 3.14.* *_cp314
+  - libre2-11 >=2025.11.5
+  - re2
+  - openssl >=3.5.8,<4.0a0
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   license: Apache-2.0
   license_family: APACHE
   run_exports: {}
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-  timestamp: 1783084338485
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-  md5: f78fad0e72a1f4f92879b598c6fec543
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+  md5: 1bd6be4f3491936e4a358c6188c6d810
   license: MIT
   license_family: MIT
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-  size: 5417564
-  timestamp: 1787921208374
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 - conda: https://prefix.dev/conda-forge/linux-64/libabseil-20260107.1-cxx17_h7b12aa8_0.conda
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-- conda: https://prefix.dev/conda-forge/linux-64/libblas-3.11.0-10_h4a7cf45_openblas.conda
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-  md5: e2ca3eadd889d39b4e4b6b1ecc671816
+- conda: https://prefix.dev/conda-forge/linux-64/libblas-3.11.0-11_h4a7cf45_openblas.conda
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-  - libcblas   3.11.0   10*_openblas
-  - liblapack  3.11.0   10*_openblas
-  - liblapacke 3.11.0   10*_openblas
+  - blas 2.311   openblas
+  - libcblas   3.11.0   11*_openblas
+  - liblapack  3.11.0   11*_openblas
+  - liblapacke 3.11.0   11*_openblas
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-  md5: fe1a5ccbcba308212c58f9a8059c4b5a
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+  md5: 8db4ae3941966215baa885eb004aded5
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-  - libcblas   3.11.0   10*_mkl
-  - liblapack  3.11.0   10*_mkl
-  - liblapacke 3.11.0   10*_mkl
+  - blas 2.311   mkl
+  - libcblas   3.11.0   11*_mkl
+  - liblapack  3.11.0   11*_mkl
+  - liblapacke 3.11.0   11*_mkl
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   - blas_mkl
   - blas_mkl_2
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+  md5: df210655e30a05e3b069c91b7aaddd2d
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-- conda: https://prefix.dev/conda-forge/linux-64/libbrotlidec-1.2.0-ha411449_3.conda
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-  - libbrotlicommon 1.2.0 h39a168f_3
+  - libbrotlicommon 1.2.0 h39a168f_4
   - libgcc >=15
   license: MIT
   license_family: MIT
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-  - libbrotlicommon 1.2.0 h39a168f_3
+  - libbrotlicommon 1.2.0 h39a168f_4
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-  size: 298639
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   timestamp: 1786025967663
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-  md5: a275bd95aa4e22c24120bf6ece6eb056
+- conda: https://prefix.dev/conda-forge/linux-64/libcblas-3.11.0-11_h0358290_openblas.conda
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-  - liblapack  3.11.0   10*_openblas
-  - liblapacke 3.11.0   10*_openblas
+  - blas 2.311   openblas
+  - liblapack  3.11.0   11*_openblas
+  - liblapacke 3.11.0   11*_openblas
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-  - blas 2.310   mkl
-  - liblapack  3.11.0   10*_mkl
-  - liblapacke 3.11.0   10*_mkl
+  size: 18196
+  timestamp: 1789061068819
+- conda: https://prefix.dev/conda-forge/linux-64/libcblas-3.11.0-11_hfef963f_mkl.conda
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+  md5: 5100a1707606a71eebcb00ace3b23339
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+  - liblapack  3.11.0   11*_mkl
+  - liblapacke 3.11.0   11*_mkl
   track_features:
   - blas_mkl
   license: BSD-3-Clause
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-  size: 18127
-  timestamp: 1788077011041
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   timestamp: 1785917328200
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-  - libgcc >=14
+  - libgcc >=15
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+  - expat 2.8.5.*
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   license_family: MIT
   run_exports: {}
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-  - libgomp 16.2.0 he0feb66_4
+  - libgcc-ng ==16.2.0=*_7
+  - libgomp 16.2.0 he0feb66_7
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+  - libgfortran-ng ==16.2.0=*_7
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+  md5: d904c7ddd95e026254b4b80808ee9e12
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+  - _python_abi3_support 1.*
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+  - exceptiongroup >=1.0.0
   - libgcc >=15
-  - python_abi 3.14.* *_cp314
+  - python_abi 3.14.* *_cp314t
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   license: MPL-2.0
   license_family: MOZILLA
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-  - python_abi 3.11.* *_cp311
-  - libgrpc >=1.78.1,<1.79.0a0
+  - libstdcxx >=15
+  - flatbuffers >=25.9.23,<25.9.24.0a0
   - libabseil >=20260107.1,<20260108.0a0
   - libabseil * cxx17*
-  - openssl >=3.5.7,<4.0a0
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   - numpy >=1.23,<3
+  - onednn >=3.12,<4.0a0
+  - python_abi 3.11.* *_cp311
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   license: Apache-2.0
   license_family: APACHE
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+  - numpy >=1.25,<3
   - onednn >=3.12,<4.0a0
   - flatbuffers >=25.9.23,<25.9.24.0a0
   - libre2-11 >=2025.11.5
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-  - numpy >=1.25,<3
   - libabseil >=20260107.1,<20260108.0a0
   - libabseil * cxx17*
+  - openssl >=3.5.8,<4.0a0
+  - python_abi 3.14.* *_cp314
+  - libzlib >=1.3.2,<2.0a0
+  - libgrpc >=1.78.1,<1.79.0a0
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   license: Apache-2.0
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+  md5: 09b30ac099061448d754828aa2fa00bb
   license: MIT
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-  timestamp: 1787921221124
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 - conda: https://prefix.dev/conda-forge/linux-aarch64/libabseil-20260107.1-cxx17_h6983b43_0.conda
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-  - liblapack  3.11.0   10*_openblas
-  - liblapacke 3.11.0   10*_openblas
+  - blas 2.311   openblas
+  - libcblas   3.11.0   11*_openblas
+  - liblapack  3.11.0   11*_openblas
+  - liblapacke 3.11.0   11*_openblas
   - mkl <2027
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+  md5: fcf455f3f376d5a881e4c38de3943c31
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+  - libbrotlicommon 1.2.0 h384ecca_4
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+  - libbrotlicommon 1.2.0 h384ecca_4
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-  - liblapack  3.11.0   10*_openblas
-  - liblapacke 3.11.0   10*_openblas
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+  constrains:
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+  - liblapack  3.11.0   11*_openblas
+  - liblapacke 3.11.0   11*_openblas
   license: BSD-3-Clause
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+  md5: e5a973222327d9183c25eddfc3a80828
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-  - libgcc >=14
+  - libgcc >=15
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+  - expat 2.8.5.*
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+  - libgcc-ng ==16.2.0=*_7
+  - libgomp 16.2.0 h8acb6b2_7
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-  - libcblas   3.11.0   10*_openblas
-  - liblapacke 3.11.0   10*_openblas
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+  - libcblas   3.11.0   11*_openblas
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+  - openmp 23.1.2|23.1.2.*
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+  md5: 2848c0ca920cd3ce577296b545c3ceb2
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+  - libbrotlicommon 1.2.0 he0616a4_4
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   license_family: MIT
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-- conda: https://prefix.dev/conda-forge/osx-64/brotli-python-1.2.0-py314h21a1a37_3.conda
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   constrains:
-  - libbrotlicommon 1.2.0 he0616a4_3
+  - libbrotlicommon 1.2.0 he0616a4_4
   license: MIT
   license_family: MIT
   run_exports: {}
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-  timestamp: 1786623591011
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 - conda: https://prefix.dev/conda-forge/osx-64/bzip2-1.0.8-h374f1ed_10.conda
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+  md5: 357fea11fbf258be4ee4ef97f6c0cc46
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+  md5: bd40e574751ed6792d0a369e18040356
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   license_family: APACHE
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-  timestamp: 1787965836380
+  size: 445053
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-- conda: https://prefix.dev/conda-forge/osx-64/gmpy2-2.3.1-py311h3f86e42_0.conda
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+  md5: 532cdaf374b2814fcf136f741fddcbd0
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+  - gmp >=6.3.0,<7.0a0
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+  - python_abi 3.11.* *_cp311
   - mpc >=1.4.0,<2.0a0
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-  - mpfr >=4.2.2,<5.0a0
   - python_abi 3.14.* *_cp314
   - mpc >=1.4.0,<2.0a0
+  - gmp >=6.3.0,<7.0a0
+  - mpfr >=4.2.2,<5.0a0
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+  - _python_abi3_support 1.*
+  - cpython >=3.11
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   license_family: MOZILLA
   run_exports: {}
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+  - exceptiongroup >=1.0.0
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-  - python_abi 3.14.* *_cp314
+  - python_abi 3.14.* *_cp314t
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   - __osx >=11.0
   license: MPL-2.0
   license_family: MOZILLA
   run_exports: {}
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-- conda: https://prefix.dev/conda-forge/osx-64/jaxlib-0.10.2-cpu_py311h3ac22a7_0.conda
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+- conda: https://prefix.dev/conda-forge/osx-64/jaxlib-0.10.2-cpu_py311h5575e1a_1.conda
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   - python 3.11.* *_cpython
+  - libcxx >=22
   - __osx >=11.0
-  - libcxx >=20
+  - python_abi 3.11.* *_cp311
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-  - flatbuffers >=25.9.23,<25.9.24.0a0
-  - libzlib >=1.3.2,<2.0a0
+  - openssl >=3.5.8,<4.0a0
+  - numpy >=1.23,<3
   - libabseil >=20260107.1,<20260108.0a0
   - libabseil * cxx17*
-  - python_abi 3.11.* *_cp311
+  - flatbuffers >=25.9.23,<25.9.24.0a0
   - libre2-11 >=2025.11.5
   - re2
-  - openssl >=3.5.7,<4.0a0
-  - numpy >=1.23,<3
+  - onednn >=3.12,<4.0a0
+  - libzlib >=1.3.2,<2.0a0
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   license: Apache-2.0
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-  - numpy >=1.25,<3
   - libre2-11 >=2025.11.5
   - re2
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+  - numpy >=1.25,<3
   - python_abi 3.14.* *_cp314
+  - libabseil >=20260107.1,<20260108.0a0
+  - libabseil * cxx17*
+  - flatbuffers >=25.9.23,<25.9.24.0a0
+  - libzlib >=1.3.2,<2.0a0
+  - openssl >=3.5.8,<4.0a0
+  - onednn >=3.12,<4.0a0
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   license: Apache-2.0
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   license: MIT
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-- conda: https://prefix.dev/conda-forge/osx-64/libblas-3.11.0-10_he492b99_openblas.conda
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   - libopenblas >=0.3.34,<1.0a0
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-  - libcblas   3.11.0   10*_openblas
-  - liblapack  3.11.0   10*_openblas
-  - liblapacke 3.11.0   10*_openblas
+  - blas 2.311   openblas
+  - libcblas   3.11.0   11*_openblas
+  - liblapack  3.11.0   11*_openblas
+  - liblapacke 3.11.0   11*_openblas
   - mkl <2027
   license: BSD-3-Clause
   license_family: BSD
   run_exports:
     weak:
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 - conda: https://prefix.dev/conda-forge/osx-64/libblas-3.9.0-20_osx64_mkl.conda
   build_number: 20
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-- conda: https://prefix.dev/conda-forge/osx-64/libbrotlicommon-1.2.0-he0616a4_3.conda
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+- conda: https://prefix.dev/conda-forge/osx-64/libbrotlicommon-1.2.0-he0616a4_4.conda
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   noarch: python
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   - _python_abi3_support 1.*
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+  - libbrotlicommon 1.2.0 hf02afa3_4
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-  - cupy >=14.2.0,<14.3.0a0
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-  - liblapacke 3.11.0   10*_mkl
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+  - libcblas   3.11.0   11*_mkl
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+  - pytorch 2.13.0 cpu_mkl_*_103
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   - libzlib >=1.3.2,<2.0a0
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     - libtorch >=2.13.0,<2.14.0a0
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-  timestamp: 1786392950037
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   timestamp: 1770223460931
-- conda: https://prefix.dev/conda-forge/win-64/ruff-0.16.7-hcc30601_0.conda
+- conda: https://prefix.dev/conda-forge/win-64/ruff-0.16.9-hcc30601_0.conda
   noarch: python
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-  md5: 9bce6eb98ca3a26401f82ce7d486cbe5
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+  md5: 0a1dd63e375d534f22c6b63310b71b1a
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@@ -19960,8 +21301,8 @@ packages:
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   license_family: MIT
   run_exports: {}
-  size: 9332759
-  timestamp: 1789115768076
+  size: 9341190
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-  - numpy <2.7
-  - numpy >=1.23,<3
+  - numpy <2.8
+  - numpy >=1.25,<3
   - numpy >=2.0.0
   - python >=3.14,<3.15.0a0
-  - python_abi 3.14.* *_cp314
+  - python_abi 3.14.* *_cp314t
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   - vc14_runtime >=14.44.35208
   license: BSD-3-Clause
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-  - numpy >=1.23,<3
+  - numpy <2.8
+  - numpy >=1.25,<3
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-  - python_abi 3.14.* *_cp314t
+  - 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
   run_exports: {}
-  size: 15466992
-  timestamp: 1781914347820
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-  md5: 8ee01a693aecff5432069eaaf1183c45
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   license_family: APACHE
   run_exports: {}
-  size: 156515
-  timestamp: 1778673901757
+  size: 157295
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-  md5: de00482a3f33d0982c9f61e282f16362
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   - ucrt >=10.0.20348.0
+  - liblzma >=5.8.3,<6.0a0
+  - zstd >=1.5.7,<1.6.0a0
   license: Apache-2.0 OR MIT
   run_exports: {}
-  size: 15645482
-  timestamp: 1787888335535
+  size: 15959965
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@@ -20202,6 +21545,22 @@ packages:
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   size: 21386
   timestamp: 1785359368990
+- conda: https://prefix.dev/conda-forge/win-64/wcwidth-0.9.1-py311h98f8659_1.conda
+  noarch: python
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+  md5: 114139ea7372464ed2779494febb86eb
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+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  - ucrt >=10.0.20348.0
+  - _python_abi3_support 1.*
+  - cpython >=3.11
+  license: MIT
+  license_family: MIT
+  run_exports: {}
+  size: 294476
+  timestamp: 1790370047084
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-- conda_source: array-api-extra[0794595c] @ .
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-  - conda: https://prefix.dev/conda-forge/osx-arm64/zstd-1.5.7-hf451053_7.conda
-- conda_source: array-api-extra[1e2d4812] @ .
+- conda_source: array-api-extra[797037ae] @ .
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   host_packages:
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-  - conda: https://prefix.dev/conda-forge/noarch/meson-python-0.20.0-pyh7e86bf3_0.conda
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-  - conda: https://prefix.dev/conda-forge/noarch/python_abi-3.14-8_cp314.conda
+  - conda: https://prefix.dev/conda-forge/noarch/python_abi-3.14-9_cp314.conda
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-  - conda: https://prefix.dev/conda-forge/osx-arm64/libexpat-2.8.1-hf6b4638_1.conda
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-  - conda: https://prefix.dev/conda-forge/osx-arm64/libpython-3.14.7-h4311e70_104_cp314.conda
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-  - conda: https://prefix.dev/conda-forge/osx-arm64/python-3.14.7-h0ae1c2c_104_cp314.conda
+  - conda: https://prefix.dev/conda-forge/osx-arm64/python-3.14.7-h0ae1c2c_106_cp314.conda
   - conda: https://prefix.dev/conda-forge/osx-arm64/readline-8.3-h8b90a29_1.conda
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-  - conda: https://prefix.dev/conda-forge/osx-arm64/uv-0.12.7-h0e72303_0.conda
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-- conda_source: array-api-extra[33e33072] @ .
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-  - python *
-  - array-api-compat >=1.15.0,<2
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-  host_packages:
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-- conda_source: array-api-extra[48057a9f] @ .
+- conda_source: array-api-extra[854c64bf] @ .
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-  - conda: https://prefix.dev/conda-forge/linux-aarch64/libgomp-16.2.0-h8acb6b2_4.conda
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-  - conda: https://prefix.dev/conda-forge/noarch/meson-1.12.0-pyhcf101f3_0.conda
-  - conda: https://prefix.dev/conda-forge/noarch/meson-python-0.20.0-pyh7e86bf3_0.conda
+  - conda: https://prefix.dev/conda-forge/noarch/meson-1.12.1-pyh5ded981_0.conda
+  - conda: https://prefix.dev/conda-forge/noarch/meson-python-0.22.0-pyh3b9e9f2_0.conda
   - conda: https://prefix.dev/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://prefix.dev/conda-forge/noarch/pyproject-metadata-0.12.1-pyhd8ed1ab_0.conda
-  - conda: https://prefix.dev/conda-forge/noarch/python_abi-3.14-8_cp314.conda
+  - conda: https://prefix.dev/conda-forge/noarch/python_abi-3.14-9_cp314.conda
   - conda: https://prefix.dev/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://prefix.dev/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-- conda_source: array-api-extra[fb215163] @ .
+  - conda: https://prefix.dev/conda-forge/osx-64/bzip2-1.0.8-h374f1ed_10.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/libcxx-23.1.2-h19cb2f5_0.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/libexpat-2.8.5-h6e061ac_0.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/libffi-3.7.0-h6b3a05b_1.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/liblzma-5.8.3-hbb4bfdb_1.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/libmpdec-4.0.0-ha1e9b39_2.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/libpython-3.14.7-hfe304d0_106_cp314.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/libsqlite-3.53.4-ha5db789_1.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/libzlib-1.3.2-hbb4bfdb_3.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/ncurses-6.6-hcc0dc9a_1.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/ninja-1.13.2-hebe015c_1.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/openssl-3.6.4-h332eb6d_0.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/python-3.14.7-hafa0b4b_106_cp314.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/readline-8.3-h000c2f7_1.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/tk-8.6.13-ha6c374e_4.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/uv-0.12.18-hdfb64f4_0.conda
+  - conda: https://prefix.dev/conda-forge/osx-64/zstd-1.5.7-hbc1a06c_7.conda
+- conda_source: array-api-extra[e10544e5] @ .
   variants:
     target_platform: noarch
   depends:
@@ -20589,28 +21764,49 @@ packages:
   license: MIT
   host_packages:
   - conda: https://prefix.dev/conda-forge/noarch/ca-certificates-2026.7.22-h4c7d964_0.conda
-  - conda: https://prefix.dev/conda-forge/noarch/meson-1.12.0-pyhcf101f3_0.conda
-  - conda: https://prefix.dev/conda-forge/noarch/meson-python-0.20.0-pyh7e86bf3_0.conda
+  - conda: https://prefix.dev/conda-forge/noarch/meson-1.12.1-pyh5ded981_0.conda
+  - conda: https://prefix.dev/conda-forge/noarch/meson-python-0.22.0-pyh3b9e9f2_0.conda
   - conda: https://prefix.dev/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://prefix.dev/conda-forge/noarch/pyproject-metadata-0.12.1-pyhd8ed1ab_0.conda
-  - conda: https://prefix.dev/conda-forge/noarch/python_abi-3.14-8_cp314.conda
+  - conda: https://prefix.dev/conda-forge/noarch/python_abi-3.14-9_cp314.conda
   - conda: https://prefix.dev/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://prefix.dev/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
   - conda: https://prefix.dev/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_10.conda
-  - conda: https://prefix.dev/conda-forge/win-64/libexpat-2.8.1-hac47afa_1.conda
+  - conda: https://prefix.dev/conda-forge/win-64/libexpat-2.8.5-hac47afa_0.conda
   - conda: https://prefix.dev/conda-forge/win-64/libffi-3.7.0-h3d046cb_1.conda
   - conda: https://prefix.dev/conda-forge/win-64/liblzma-5.8.3-hfd05255_1.conda
   - conda: https://prefix.dev/conda-forge/win-64/libmpdec-4.0.0-hfd05255_2.conda
-  - conda: https://prefix.dev/conda-forge/win-64/libpython-3.14.7-h4f90d01_104_cp314.conda
+  - conda: https://prefix.dev/conda-forge/win-64/libpython-3.14.7-h4f90d01_106_cp314.conda
   - conda: https://prefix.dev/conda-forge/win-64/libsqlite-3.53.4-hf5d6505_1.conda
   - conda: https://prefix.dev/conda-forge/win-64/libzlib-1.3.2-hfd05255_3.conda
   - conda: https://prefix.dev/conda-forge/win-64/ninja-1.13.2-h477610d_1.conda
   - conda: https://prefix.dev/conda-forge/win-64/openssl-3.6.4-hf411b9b_0.conda
-  - conda: https://prefix.dev/conda-forge/win-64/python-3.14.7-h53f6dd8_104_cp314.conda
+  - conda: https://prefix.dev/conda-forge/win-64/python-3.14.7-h53f6dd8_106_cp314.conda
   - conda: https://prefix.dev/conda-forge/win-64/tk-8.6.13-h967ab96_4.conda
   - conda: https://prefix.dev/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda
-  - conda: https://prefix.dev/conda-forge/win-64/uv-0.12.7-hc31ddbc_0.conda
+  - conda: https://prefix.dev/conda-forge/win-64/uv-0.12.19-h8a923dc_0.conda
   - conda: https://prefix.dev/conda-forge/win-64/vc-14.5-ha367084_41.conda
   - conda: https://prefix.dev/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
   - conda: https://prefix.dev/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
   - conda: https://prefix.dev/conda-forge/win-64/zstd-1.5.7-h534d264_7.conda
+- pypi: https://files.pythonhosted.org/packages/35/c8/d4f7c648d6ea7baee986047ca30647a5733df5b9c77bb0a262dc5aca0843/mlx-0.32.2-cp314-cp314-macosx_14_0_arm64.whl
+  name: mlx
+  version: 0.32.2
+  sha256: c99e3b6451bb4a55071cf19594f564435bd88de77008f377e611a40a8bbfb328
+  requires_dist:
+  - mlx-metal==0.32.2 ; sys_platform == 'darwin'
+  - ml-dtypes ; extra == 'dev'
+  - numpy>=2 ; extra == 'dev'
+  - pre-commit ; extra == 'dev'
+  - torch>=2.9 ; extra == 'dev'
+  - typing-extensions ; extra == 'dev'
+  - mlx-cuda-12==0.32.2 ; sys_platform == 'linux' and extra == 'cuda'
+  - mlx-cuda-12==0.32.2 ; sys_platform == 'linux' and extra == 'cuda12'
+  - mlx-cuda-13==0.32.2 ; sys_platform == 'linux' and extra == 'cuda13'
+  - mlx-cpu==0.32.2 ; sys_platform == 'linux' and extra == 'cpu'
+  requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/f7/ab/ba1952908c5d2a5070cf1cfbfea0161c4751ea62299e2776819810917483/mlx_metal-0.32.2-py3-none-macosx_14_0_arm64.whl
+  name: mlx-metal
+  version: 0.32.2
+  sha256: 3825fff379dbc107dd3413e564a06caeaa24819910ec49c0439e454c06a1b9b8
+  requires_python: '>=3.10'
diff --git a/pixi.toml b/pixi.toml
index 09c6a749..9fc6a5e2 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -7,6 +7,7 @@ platforms = [
   "linux-aarch64",
   "osx-64",
   "osx-arm64",
+  { name = "osx-arm64-macos14", platform = "osx-arm64", macos = "14.5" },
   "win-64",
   { platform = "linux-64", cuda = "12.9" },
   { platform = "win-64", cuda = "12.9" },
@@ -69,6 +70,7 @@ tests-backends = {
   solve-group = "backends",
 }
 tests-backends-py311.features = ["py311", "tests", "backends"]
+tests-mlx = { features = ["py314", "tests", "mlx"], solve-group = "mlx" }
 
 # CUDA not available on free github actions and on some developers' PCs
 dev-cuda = {
@@ -378,6 +380,12 @@ mparray = ">=0.2.2"
 [feature.backends.target.unix.dependencies]
 jax = ">=0.10.2"  # waiting for conda-forge/jaxlib-feedstock#326
 
+[feature.mlx.target.osx-arm64.pypi-dependencies]
+mlx = ">=0.32.2"
+
+[feature.mlx]
+platforms = ["osx-arm64-macos14"]
+
 # Backends that require a GPU host and a CUDA driver.
 [feature.cuda-backends]
 platforms = ["linux-64-cuda-12-9", "win-64-cuda-12-9"]
diff --git a/pyproject.toml b/pyproject.toml
index b936ec0d..83968325 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -80,7 +80,7 @@ disable_error_code = ["no-any-return"]
 
 [[tool.mypy.overrides]]
 # slow or unavailable on Windows; do not add to the lint env
-module = ["cupy.*", "jax.*", "sparse.*", "torch.*"]
+module = ["cupy.*", "jax.*", "mlx.*", "sparse.*", "torch.*"]
 ignore_missing_imports = true
 
 [[tool.mypy.overrides]]
diff --git a/src/array_api_extra/_lib/_backends.py b/src/array_api_extra/_lib/_backends.py
index a4760f7a..7fadf95b 100644
--- a/src/array_api_extra/_lib/_backends.py
+++ b/src/array_api_extra/_lib/_backends.py
@@ -30,6 +30,7 @@ class Backend(Enum):  # numpydoc ignore=PR02
     NUMPY_READONLY = "numpy:readonly"
     MPARRAY = "mparray"
     CUPY = "cupy"
+    MLX = "mlx.core"
     TORCH = "torch"
     TORCH_GPU = "torch:gpu"
     DASK = "dask.array"
diff --git a/src/array_api_extra/_lib/_compat.py b/src/array_api_extra/_lib/_compat.py
index 17300805..147716c0 100644
--- a/src/array_api_extra/_lib/_compat.py
+++ b/src/array_api_extra/_lib/_compat.py
@@ -2,11 +2,27 @@
 # Allow packages that vendor both `array-api-extra` and
 # `array-api-compat` to override the import location
 
-# pylint: disable=duplicate-code
+from functools import cache
+from types import ModuleType
+from typing import TYPE_CHECKING, ClassVar
+
+if TYPE_CHECKING:  # pragma: no cover
+    from typing_extensions import override
+else:
+
+    def override(func):
+        return func
+
+
+# pylint: disable=duplicate-code,redefined-outer-name
 try:
     from ..._array_api_compat_vendor import (
-        array_namespace,
-        device,
+        array_namespace as _array_namespace,
+    )
+    from ...._array_api_compat_vendor import (
+        device as _device,
+    )
+    from ...._array_api_compat_vendor import (
         is_array_api_obj,
         is_array_api_strict_namespace,
         is_cupy_array,
@@ -24,12 +40,18 @@
         is_torch_namespace,
         is_writeable_array,
         size,
-        to_device,
+    )
+    from ...._array_api_compat_vendor import (
+        to_device as _to_device,
     )
 except ImportError:
     from array_api_compat import (
-        array_namespace,
-        device,
+        array_namespace as _array_namespace,
+    )
+    from array_api_compat import (
+        device as _device,
+    )
+    from array_api_compat import (
         is_array_api_obj,
         is_array_api_strict_namespace,
         is_cupy_array,
@@ -47,8 +69,131 @@
         is_torch_namespace,
         is_writeable_array,
         size,
-        to_device,
     )
+    from array_api_compat import (
+        to_device as _to_device,
+    )
+
+
+class _MLXNamespaceInfo:
+    def __init__(self, info: object) -> None:
+        self._info = info
+
+    def __getattr__(self, name: str) -> object:
+        return getattr(self._info, name)
+
+    def default_dtypes(self, *, device: object = None) -> object:
+        _ = device
+        return self._info.default_dtypes()  # type: ignore[attr-defined]
+
+
+class _MLXNamespace(ModuleType):
+    _device_functions: ClassVar[set[str]] = {
+        "arange",
+        "asarray",
+        "empty",
+        "eye",
+        "full",
+        "linspace",
+        "ones",
+        "zeros",
+    }
+
+    def __init__(self, namespace: ModuleType) -> None:
+        super().__init__(namespace.__name__)
+        self._namespace = namespace
+
+    @override
+    def __getattr__(self, name: str) -> object:
+        if name == "__array_api_version__":
+            return "2024.12"
+        if name == "bool":
+            return self._namespace.bool_
+        if name == "__array_namespace_info__":
+            info = getattr(self._namespace, name)
+            return lambda: _MLXNamespaceInfo(info())
+        if name == "signbit":
+            return lambda x: x < 0
+        function = getattr(self._namespace, name)
+        if name not in {"argsort", "astype", "result_type", "sort"} and (
+            name not in self._device_functions
+        ):
+            return function
+
+        def compatible_call(
+            *args: object,
+            device: object = None,
+            copy: bool | None = None,
+            **kwargs: object,
+        ) -> object:
+            if name == "full" and "fill_value" in kwargs:
+                args = (*args, kwargs.pop("fill_value"))
+            if name == "asarray" and copy is not None:
+                kwargs["copy"] = copy
+            if name == "asarray" and "dtype" not in kwargs:
+                input_array = args[0] if args else kwargs.get("a")
+                input_dtype = getattr(input_array, "dtype", None)
+                dtype_name = getattr(input_dtype, "name", None)
+                if dtype_name is not None and hasattr(self._namespace, dtype_name):
+                    kwargs["dtype"] = getattr(self._namespace, dtype_name)
+            if name == "astype":
+                _ = copy
+                return function(*args, **kwargs)
+            if name in {"argsort", "sort"}:
+                kwargs.pop("stable", None)
+            if name == "result_type":
+                import mlx.core as mx
+
+                args = tuple(
+                    mx.asarray(value)
+                    if isinstance(value, int | float | complex | bool)
+                    else value
+                    for value in args
+                )
+            if device is None:
+                return function(*args, **kwargs)
+            import mlx.core as mx
+
+            with mx.stream(device):
+                return function(*args, **kwargs)
+
+        return compatible_call
+
+
+@cache
+def _wrap_mlx_namespace(namespace: ModuleType) -> ModuleType:
+    return _MLXNamespace(namespace)
+
+
+def array_namespace(
+    *xs: object, api_version: str | None = None, use_compat: bool | None = None
+) -> ModuleType:
+    namespace = _array_namespace(*xs, api_version=api_version, use_compat=use_compat)
+    if namespace.__name__ == "mlx.core":
+        return _wrap_mlx_namespace(namespace)
+    return namespace
+
+
+def device(x: object, /) -> object:
+    if type(x).__module__.startswith("mlx."):
+        import mlx.core as mx
+
+        return mx.default_device()
+    return _device(x)
+
+
+def to_device(x: object, device: object, /, *, stream: object = None) -> object:
+    if type(x).__module__.startswith("mlx."):
+        import mlx.core as mx
+
+        if device == "cpu":
+            device = mx.cpu
+        elif device == "gpu":
+            device = mx.gpu
+        with mx.stream(device):
+            return mx.array(x)
+    return _to_device(x, device, stream=stream)
+
 
 __all__ = [
     "array_namespace",
diff --git a/tests/main/conftest.py b/tests/main/conftest.py
index 7a83fe37..c40990d0 100644
--- a/tests/main/conftest.py
+++ b/tests/main/conftest.py
@@ -148,6 +148,14 @@ def xp(
         _setup_jax(library)
     elif library.like(Backend.TORCH):
         _setup_torch(library)
+    elif library is Backend.MLX:
+        _setup_mlx()
+
+        import mlx.core as mx
+
+        with mx.stream(mx.cpu), patch_lazy_xp_functions(request, xp=xp):
+            yield xp
+        return
 
     # On Dask and JAX, monkey-patch all functions tagged by `lazy_xp_function`
     # in the global scope of the module containing the test function.
@@ -189,6 +197,12 @@ def _setup_torch(library: Backend) -> None:
         torch.set_default_device("cpu")
 
 
+def _setup_mlx() -> None:
+    import mlx.core as mx
+
+    mx.set_default_device(mx.cpu)
+
+
 # Can select the test with `pytest -k dask`
 @pytest.fixture(params=[Backend.DASK.pytest_param()])
 def da(
@@ -244,6 +258,6 @@ def device(
 @pytest.fixture
 def infinity(library: Backend) -> float:
     """Retrieve the positive infinity value for the given backend."""
-    if library in (Backend.TORCH, Backend.TORCH_GPU):
+    if library in (Backend.MLX, Backend.TORCH, Backend.TORCH_GPU):
         return 3.4028235e38
     return 1.7976931348623157e308
diff --git a/tests/main/test_at.py b/tests/main/test_at.py
index aa1e7d77..542ea153 100644
--- a/tests/main/test_at.py
+++ b/tests/main/test_at.py
@@ -121,6 +121,7 @@ def assert_copy(
 )
 def test_update_ops(
     xp: ArrayNamespace,
+    library: Backend,
     copy: bool | None,
     op: _AtOp,
     y: float,
@@ -129,6 +130,8 @@ def test_update_ops(
     x_ndim: int,
     y_ndim: int,
 ):
+    if bool_mask and library is Backend.MLX:
+        pytest.skip("MLX does not support boolean indexing")
     if x_ndim == 1:
         x = xp.asarray([10.0, 20.0, 30.0])
         idx = xp.asarray([False, True, True]) if bool_mask else slice(1, None)
@@ -153,6 +156,7 @@ def test_update_ops(
 
 
 @pytest.mark.parametrize("op", list(_AtOp))
+@pytest.mark.skip_xp_backend(Backend.MLX, reason="boolean indexing is unsupported")
 def test_copy_default(xp: ArrayNamespace, library: Backend, op: _AtOp):
     """
     Test that the default copy behaviour is False for writeable arrays
@@ -235,6 +239,8 @@ def test_incompatible_dtype(
     UFuncTypeError: Cannot cast ufunc 'divide' output from dtype('float64')
     to dtype('int64') with casting rule 'same_kind'
     """
+    if bool_mask and library is Backend.MLX:
+        pytest.skip("MLX does not support boolean indexing")
     x = xp.asarray([2, 4])
     idx = xp.asarray([True, False]) if bool_mask else slice(None)
     z = None
@@ -254,6 +260,13 @@ def test_incompatible_dtype(
         with pytest.raises(Exception, match=r"cast|promote|dtype"):
             _ = at_op(x, idx, op, 1.1, copy=copy)
 
+    elif library is Backend.MLX:
+        if op is _AtOp.DIVIDE:
+            with pytest.raises(Exception, match="cast"):
+                _ = at_op(x, idx, op, 1.1, copy=copy)
+        else:
+            z = at_op(x, idx, op, 1.1, copy=copy)
+
     elif op in (_AtOp.SET, _AtOp.MIN, _AtOp.MAX):
         # There is no __i<op>__ version of min/max.
         # libraries other than array-api-strict are happy with
@@ -277,7 +290,9 @@ def test_bool_mask_nd(xp: ArrayNamespace):
 
 
 @pytest.mark.parametrize("bool_mask", [False, True])
-def test_no_inf_warnings(xp: ArrayNamespace, bool_mask: bool):
+def test_no_inf_warnings(xp: ArrayNamespace, library: Backend, bool_mask: bool):
+    if bool_mask and library is Backend.MLX:
+        pytest.skip("MLX does not support boolean indexing")
     x = xp.asarray([math.inf, 1.0, 2.0])
     idx = ~xp.isinf(x) if bool_mask else slice(1, None)
     # inf - inf -> nan with a warning
diff --git a/tests/main/test_creation.py b/tests/main/test_creation.py
index 358efa09..53df5beb 100644
--- a/tests/main/test_creation.py
+++ b/tests/main/test_creation.py
@@ -49,6 +49,9 @@ def test_2d(self, xp: ArrayNamespace):
     @pytest.mark.skip_xp_backend(
         Backend.ARRAY_API_STRICTEST, reason="backend doesn't support Boolean indexing"
     )
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX, reason="backend doesn't support Boolean indexing"
+    )
     def test_abstract_size(self, xp: ArrayNamespace):
         x = xp.arange(5)
         x = x[x > 2]
diff --git a/tests/main/test_elementwise.py b/tests/main/test_elementwise.py
index 4ae2973f..ac1fc3bb 100644
--- a/tests/main/test_elementwise.py
+++ b/tests/main/test_elementwise.py
@@ -398,6 +398,9 @@ def test_bool_dtype(self, xp: ArrayNamespace):
 
     @pytest.mark.skip_xp_backend(Backend.SPARSE, reason="index by sparse array")
     @pytest.mark.skip_xp_backend(Backend.ARRAY_API_STRICTEST, reason="unknown shape")
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX, reason="backend doesn't support Boolean indexing"
+    )
     def test_none_shape(self, xp: ArrayNamespace):
         a = xp.asarray([1, 5, 0])
         b = xp.asarray([1, 4, 2])
@@ -407,6 +410,9 @@ def test_none_shape(self, xp: ArrayNamespace):
 
     @pytest.mark.skip_xp_backend(Backend.SPARSE, reason="index by sparse array")
     @pytest.mark.skip_xp_backend(Backend.ARRAY_API_STRICTEST, reason="unknown shape")
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX, reason="backend doesn't support Boolean indexing"
+    )
     def test_none_shape_bool(self, xp: ArrayNamespace):
         a = xp.asarray([True, True, False])
         b = xp.asarray([True, False, True])
@@ -604,6 +610,9 @@ def test_dtype(self, xp: ArrayNamespace, x: complex):
         with pytest.raises(ValueError, match="real floating data type"):
             _ = sinc(xp.asarray(x))
 
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX, reason="float32 precision is insufficient for this assertion"
+    )
     def test_3d(self, xp: ArrayNamespace):
         x = np.arange(18, dtype=np.float64).reshape((3, 3, 2))
         expected = np.zeros_like(x)
@@ -627,6 +636,7 @@ def test_simple(self, xp: ArrayNamespace):
         expected = xp.asarray([0.0, 0.0], dtype=res.dtype)
         assert_equal(res, expected)
 
+    @pytest.mark.skip_xp_backend(Backend.MLX, reason="backend has no complex128 dtype")
     def test_basic(self, xp: ArrayNamespace):
         x = xp.asarray(
             [
diff --git a/tests/main/test_helpers.py b/tests/main/test_helpers.py
index 34e1bc8c..1432b78f 100644
--- a/tests/main/test_helpers.py
+++ b/tests/main/test_helpers.py
@@ -31,6 +31,7 @@
 
 @pytest.mark.xfail_xp_backend(Backend.SPARSE, reason="no unique_inverse")
 @pytest.mark.skip_xp_backend(Backend.ARRAY_API_STRICTEST, reason="no unique_inverse")
+@pytest.mark.skip_xp_backend(Backend.MLX, reason="no unique_values or unique_inverse")
 class TestIn1D:
     # cover both code paths
     @pytest.mark.parametrize(
@@ -96,8 +97,15 @@ class TestAsArrays:
         ],
     )
     def test_array_vs_scalar(
-        self, dtype: str, b: complex, defined: bool, xp: ArrayNamespace
+        self,
+        dtype: str,
+        b: complex,
+        defined: bool,
+        xp: ArrayNamespace,
+        library: Backend,
     ):
+        if library is Backend.MLX and dtype == "complex128":
+            pytest.skip("MLX does not support complex128")
         a = xp.asarray(1, dtype=getattr(xp, dtype))
 
         xa, xb = asarrays(a, b, xp)
@@ -134,11 +142,15 @@ def test_scalar_vs_scalar(self, xp: ArrayNamespace):
 
     @pytest.mark.parametrize("a_type", ALL_TYPES)
     @pytest.mark.parametrize("b_type", ALL_TYPES)
-    def test_array_vs_array(self, a_type: str, b_type: str, xp: ArrayNamespace):
+    def test_array_vs_array(
+        self, a_type: str, b_type: str, xp: ArrayNamespace, library: Backend
+    ):
         """
         Test that when both inputs of asarray are already Array API objects,
         they are returned unchanged.
         """
+        if library is Backend.MLX and "complex128" in (a_type, b_type):
+            pytest.skip("MLX does not support complex128")
         a = xp.asarray(1, dtype=getattr(xp, a_type))
         b = xp.asarray(1, dtype=getattr(xp, b_type))
         xa, xb = asarrays(a, b, xp)
@@ -166,6 +178,7 @@ def test_ndindex(shape: tuple[int, ...]):
 
 @pytest.mark.skip_xp_backend(Backend.SPARSE, reason="index by sparse array")
 @pytest.mark.skip_xp_backend(Backend.ARRAY_API_STRICTEST, reason="boolean indexing")
+@pytest.mark.skip_xp_backend(Backend.MLX, reason="boolean indexing is unsupported")
 def test_eager_shape(xp: ArrayNamespace, library: Backend):
     a = xp.asarray([1, 2, 3])
     # Lazy arrays, like Dask, have an eager shape until you slice them with
diff --git a/tests/main/test_indexing.py b/tests/main/test_indexing.py
index 4b2c83ae..4160fa32 100644
--- a/tests/main/test_indexing.py
+++ b/tests/main/test_indexing.py
@@ -16,6 +16,9 @@
 
 @pytest.mark.xfail_xp_backend(Backend.SPARSE, reason="no arange", strict=False)
 class TestDiagIndices:
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX, reason="backend uses int32 for generated indices"
+    )
     def test_basic(self, xp: ArrayNamespace):
         rows, cols = diag_indices(5, xp=xp)
         ref_rows, ref_cols = np.diag_indices(5)
@@ -24,6 +27,9 @@ def test_basic(self, xp: ArrayNamespace):
 
     @pytest.mark.parametrize("n", [2, 4, 7])
     @pytest.mark.parametrize("ndim", [1, 2, 3, 4])
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX, reason="backend uses int32 for generated indices"
+    )
     def test_ndim(self, xp: ArrayNamespace, n: int, ndim: int):
         idx = diag_indices(n, ndim=ndim, xp=xp)
         assert len(idx) == ndim
@@ -58,6 +64,7 @@ def test_device(self, xp: ArrayNamespace, device: Device):
     reason="generic path uses nonzero (data-dependent)",
     strict=False,
 )
+@pytest.mark.skip_xp_backend(Backend.MLX, reason="backend does not provide nonzero")
 @pytest.mark.parametrize(
     ("xpx_fn", "np_fn"),
     [(tril_indices, np.tril_indices), (triu_indices, np.triu_indices)],
diff --git a/tests/main/test_inspection.py b/tests/main/test_inspection.py
index 203d6169..99f71328 100644
--- a/tests/main/test_inspection.py
+++ b/tests/main/test_inspection.py
@@ -1,6 +1,7 @@
 import pytest
 
 from array_api_extra import default_dtype
+from array_api_extra._lib._backends import Backend
 from array_api_extra._lib._typing import ArrayNamespace, Device
 from array_api_extra.testing import lazy_xp_function
 
@@ -11,6 +12,10 @@ class TestDefaultDType:
     def test_basic(self, xp: ArrayNamespace):
         assert default_dtype(xp) == xp.empty(0).dtype
 
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX,
+        reason="backend's default indexing dtype is int32",
+    )
     def test_kind(self, xp: ArrayNamespace):
         assert default_dtype(xp, "real floating") == xp.empty(0).dtype
         assert default_dtype(xp, "complex floating") == (xp.empty(0) * 1j).dtype
diff --git a/tests/main/test_lazy.py b/tests/main/test_lazy.py
index 1493f372..ba512d5a 100644
--- a/tests/main/test_lazy.py
+++ b/tests/main/test_lazy.py
@@ -216,6 +216,7 @@ def helloworld(x: Array) -> Array:
     assert "helloworld" in prefixes
 
 
+@pytest.mark.skip_xp_backend(Backend.MLX, reason="no unique_values or unique_counts")
 def test_lazy_apply_none_shape_in_args(xp: ArrayNamespace, library: Backend):
     x = xp.asarray([1, 1, 2, 2, 2])
 
@@ -267,6 +268,7 @@ def f(x: Array) -> Array:
 @pytest.mark.skip_xp_backend(Backend.JAX, reason="boolean indexing")
 @pytest.mark.skip_xp_backend(Backend.JAX_GPU, reason="boolean indexing")
 @pytest.mark.skip_xp_backend(Backend.ARRAY_API_STRICTEST, reason="boolean indexing")
+@pytest.mark.skip_xp_backend(Backend.MLX, reason="boolean indexing is unsupported")
 def test_lazy_apply_none_shape_broadcast(xp: ArrayNamespace):
     """Broadcast from input array with unknown shape"""
     x = xp.asarray([1, 2, 2])
diff --git a/tests/main/test_set.py b/tests/main/test_set.py
index 3048b23a..e7fd16bf 100644
--- a/tests/main/test_set.py
+++ b/tests/main/test_set.py
@@ -17,6 +17,9 @@ class TestNUnique:
     @pytest.mark.skip_xp_backend(
         Backend.ARRAY_API_STRICT, reason="array-agnostic fallback"
     )
+    @pytest.mark.skip_xp_backend(
+        Backend.MLX, reason="backend does not provide unique_counts"
+    )
     @pytest.mark.skip_xp_backend(
         Backend.ARRAY_API_STRICTEST, reason="array-agnostic fallback"
     )
@@ -86,6 +89,9 @@ def test_xp(self, xp: ArrayNamespace):
 
 @pytest.mark.xfail_xp_backend(Backend.SPARSE, reason="no argsort")
 @pytest.mark.skip_xp_backend(Backend.ARRAY_API_STRICTEST, reason="no unique_values")
+@pytest.mark.skip_xp_backend(
+    Backend.MLX, reason="backend does not provide unique_values or Boolean indexing"
+)
 class TestSetDiff1D:
     @pytest.mark.xfail_xp_backend(Backend.DASK, reason="NaN-shaped arrays")
     @pytest.mark.xfail_xp_backend(
@@ -232,6 +238,7 @@ def test_kind(self, xp: ArrayNamespace, library: Backend):
     Backend.ARRAY_API_STRICTEST,
     reason="data_dependent_shapes flag for unique_values is disabled",
 )
+@pytest.mark.skip_xp_backend(Backend.MLX, reason="backend does not provide unique_values")
 class TestUnion1d:
     def test_simple(self, xp: ArrayNamespace):
         a = xp.asarray([-1, 1, 0])
diff --git a/tests/main/test_statistical.py b/tests/main/test_statistical.py
index 41963894..b1d65f01 100644
--- a/tests/main/test_statistical.py
+++ b/tests/main/test_statistical.py
@@ -24,6 +24,7 @@ def test_basic(self, xp: ArrayNamespace):
             xp.asarray([[1.0, -1.0], [-1.0, 1.0]], dtype=xp.float64),
         )
 
+    @pytest.mark.skip_xp_backend(Backend.MLX, reason="backend has no complex128 dtype")
     def test_complex(self, xp: ArrayNamespace):
         actual = cov(xp.asarray([[1, 2, 3], [1j, 2j, 3j]], dtype=xp.complex128))
         expect = xp.asarray([[1.0, -1.0j], [1.0j, 1.0]], dtype=xp.complex128)
@@ -93,6 +94,7 @@ def test_xp(self, xp: ArrayNamespace):
             xp.asarray([[1.0, -1.0], [-1.0, 1.0]], dtype=xp.float64),
         )
 
+    @pytest.mark.skip_xp_backend(Backend.MLX, reason="batched matmul is unsupported")
     def test_batch(self, xp: ArrayNamespace):
         rng = np.random.default_rng(8847643423)
         batch_shape = (3, 4)
@@ -117,6 +119,7 @@ def test_bias(self, xp: ArrayNamespace, bias: bool):
         )
 
     @pytest.mark.parametrize("bias", [True, False, 0, 1])
+    @pytest.mark.skip_xp_backend(Backend.MLX, reason="batched matmul is unsupported")
     def test_bias_batch(self, xp: ArrayNamespace, bias: bool):
         rng = np.random.default_rng(8847643423)
         batch_shape = (3, 4)
@@ -186,6 +189,7 @@ def test_both_weights(self, xp: ArrayNamespace):
             )
             assert_close(res, xp.asarray(ref))
 
+    @pytest.mark.skip_xp_backend(Backend.MLX, reason="batched matmul is unsupported")
     def test_batch_with_weights(self, xp: ArrayNamespace):
         rng = np.random.default_rng(20260417)
         batch_shape = (2, 3)
diff --git a/tests/main/test_testing.py b/tests/main/test_testing.py
index 609c917f..00491001 100644
--- a/tests/main/test_testing.py
+++ b/tests/main/test_testing.py
@@ -31,13 +31,13 @@ class TestAsNumPyArray:
     def test_basic(self, xp: ArrayNamespace):
         x = xp.asarray([1, 2, 3])
         y = _as_numpy_array(x, xp=xp)
-        assert_equal(y, np.asarray([1, 2, 3]))  # type: ignore[arg-type]  # pyright: ignore[reportArgumentType]
+        assert_equal(y, np.asarray([1, 2, 3], dtype=y.dtype))  # type: ignore[arg-type]  # pyright: ignore[reportArgumentType]
 
     @pytest.mark.skip_xp_backend(Backend.TORCH, reason="materialize 'meta' device")
     def test_device(self, xp: ArrayNamespace, device: Device):
         x = xp.asarray([1, 2, 3], device=device)
         y = _as_numpy_array(x, xp=xp)
-        assert_equal(y, np.asarray([1, 2, 3]))  # type: ignore[arg-type]  # pyright: ignore[reportArgumentType]
+        assert_equal(y, np.asarray([1, 2, 3], dtype=y.dtype))  # type: ignore[arg-type]  # pyright: ignore[reportArgumentType]
 
 
 class TestAssertEqualCloseLess:
@@ -172,6 +172,7 @@ def test_assert_less(self, xp: ArrayNamespace):
     )
     @pytest.mark.skip_xp_backend(Backend.SPARSE, reason="index by sparse array")
     @pytest.mark.skip_xp_backend(Backend.ARRAY_API_STRICTEST, reason="boolean indexing")
+    @pytest.mark.skip_xp_backend(Backend.MLX, reason="boolean indexing is unsupported")
     def test_none_shape(self, xp: ArrayNamespace, func: Callable[..., None]):
         """On Dask and other lazy backends, test that a shape with NaN's or None's
         can be compared to a real shape.
@@ -362,6 +363,9 @@ def test_lazy_xp_function_deprecated_static_argnames():
 
 
 @pytest.mark.skip_xp_backend(Backend.TORCH_GPU, reason="device->host copy")
+@pytest.mark.skip_xp_backend(
+    Backend.MLX, reason="SciPy Cython ufunc returns NumPy arrays"
+)
 @pytest.mark.skip_xp_backend(Backend.MPARRAY, reason="mparray lacks __array_ufunc__")
 @pytest.mark.filterwarnings("ignore:__array_wrap__:DeprecationWarning")  # PyTorch
 def test_lazy_xp_function_cython_ufuncs(xp: ArrayNamespace, library: Backend):