FBGEMM_GPU

FBGEMM_GPU-CPU CI FBGEMM_GPU-CUDA CI FBGEMM_GPU-ROCm CI

FBGEMM_GPU (FBGEMM GPU Kernels Library) is a collection of high-performance PyTorch GPU operator libraries for training and inference. The library provides efficient table batched embedding bag, data layout transformation, and quantization supports.

See the full Documentation for more information on building, installing, and developing with FBGEMM_GPU, as well as the most up-to-date support matrix for this library.

Join the FBGEMM_GPU Community

For questions, support, news updates, or feature requests, please feel free to:

For contributions, please see the CONTRIBUTING file for ways to help out.

License

FBGEMM_GPU is BSD licensed, as found in the LICENSE file.

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (2026.8.15)

2 maintainers

PyPI data
Data sourced directly from PyPI's database.
Avatar for fbgemm from gravatar.com fbgemm Avatar for jianyuhuang from gravatar.com jianyuhuang

Credits

Author: FBGEMM Team

License

BSD License (BSD-3)

Tags

PyTorch Recommendation Models High Performance Computing GPU CUDA

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

fbgemm_gpu_nightly_cpu-2026.7.31-cp314-cp314-manylinux_2_28_x86_64.whl (6.3 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ x86-64

fbgemm_gpu_nightly_cpu-2026.7.31-cp314-cp314-manylinux_2_28_aarch64.whl (4.9 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ ARM64

fbgemm_gpu_nightly_cpu-2026.7.31-cp313-cp313-manylinux_2_28_x86_64.whl (6.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

fbgemm_gpu_nightly_cpu-2026.7.31-cp313-cp313-manylinux_2_28_aarch64.whl (4.9 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ ARM64

fbgemm_gpu_nightly_cpu-2026.7.31-cp312-cp312-manylinux_2_28_x86_64.whl (6.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

fbgemm_gpu_nightly_cpu-2026.7.31-cp312-cp312-manylinux_2_28_aarch64.whl (4.9 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ ARM64

fbgemm_gpu_nightly_cpu-2026.7.31-cp311-cp311-manylinux_2_28_x86_64.whl (6.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

fbgemm_gpu_nightly_cpu-2026.7.31-cp311-cp311-manylinux_2_28_aarch64.whl (4.9 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ ARM64

fbgemm_gpu_nightly_cpu-2026.7.31-cp310-cp310-manylinux_2_28_x86_64.whl (6.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

fbgemm_gpu_nightly_cpu-2026.7.31-cp310-cp310-manylinux_2_28_aarch64.whl (4.9 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ ARM64

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp314-cp314-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp314-cp314-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a152ba85f1674e13ce392c37fcd80d39294ec070a44c0b98e28001fc19c7f5f2
MD5 bc3a3846b9319f9d861c0ef6871b47f7
BLAKE2b-256 9be70499041b3ec8fd958add242ed7227277d14b984acd37429a3e0566f82440

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp314-cp314-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp314-cp314-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 f80b0276b9427062a2cf5d497cd4503b050acbf00b76bbf40260d2b635ab682b
MD5 327cffaf44f778e16dea257f0b2c2ea0
BLAKE2b-256 5f37554f9314614e1addc9b392e890f3f18beab9c2814dbbc26b6bd353dcd799

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 add67f6c84cf5f6ff954b980d1060f92253c67b18e28d6d029a7045b25b67525
MD5 066dd1ccc800549422946110b32d9b1b
BLAKE2b-256 8a02488d26cf5264fc0e8e2b544ab4c063b1278ea3041a87cce3311783d0b17c

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp313-cp313-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp313-cp313-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 5c107d81e98bb063387fd48733540045ba118eb493cc822623b625944c6e1526
MD5 d68df76997fa3754cfbbfd26f60f501a
BLAKE2b-256 1db958cb0535f7832d8f183ff4b0de44fe038773d86b57591f1d27deae74257b

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a512dbd30745c1614262cea922f2e621b0622953d8642a6ca7e0261e958ffaca
MD5 e860b651447e4e7bcdeb5274b6ca2cf2
BLAKE2b-256 e9350f6747970da84dc4c7d70c99be9171c938e265c1ac3423e920c80438cfe3

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp312-cp312-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp312-cp312-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 786220f4a9fc639cb0f5b6ad140486394504a46cd80f04568afea6e0408ba98a
MD5 115bce0fb9121a139e8d53c19be183ab
BLAKE2b-256 550bd8e708c8def9d23b22d81b858f6a3cd0d996dbd21bae82b626ffbe73ad54

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 825d5886f8aac4334610020bfcb69bb6438c3fd0e76bfd7a9b162769cdaffc42
MD5 b93bea2ae802a04b0f4cb40e79f31e22
BLAKE2b-256 2ac296a419fb95e5304fbf312cd41579874b64b104f2c52e96715707f8828818

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 42362be5a525ffe8599164d513d732cde4e1288a3558afe5c0d0906ea01e43e5
MD5 7fc8b9bef48fed5d647881a765e57ed7
BLAKE2b-256 ad292a0fa90c3911e3cd4ea226de6c2f7f7695e6c0b75d9e93d4a7328d24f7c6

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d21302c5006ef86017a02fe5ccd6643262fe4e3306c5f4069d0078f6d4ea827e
MD5 6a6605a0d8dc63e0ddc1a260bf8144bb
BLAKE2b-256 3141e0dfe6cfec3fdf416bf16126f7b96b0f041ef0fe8bc9558fb175cfc0a761

See more details on using hashes here.

File details

Details for the file fbgemm_gpu_nightly_cpu-2026.7.31-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for fbgemm_gpu_nightly_cpu-2026.7.31-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 8003c0b81cd18aee9e7f769095bcae0af14176d181d3ad4cc43e8169d7956956
MD5 652218d47d1b2ed9a7ea6e469dc3948f
BLAKE2b-256 3dc7e61e3b3f2c253527c883d91da1c349538f3428125aaf0e8cc18bd215d1b7

See more details on using hashes here.

Release history Release notifications | RSS feed

2026.8.15

2026.8.14

2026.8.13

2026.8.12

2026.8.11

2026.8.10

2026.8.9

2026.8.8

2026.8.7

2026.8.6

2026.8.5

2026.8.4

2026.8.3

2026.8.2

2026.8.1

This release

2026.7.31

2026.7.30

2026.7.29

2026.7.28

2026.7.27

2026.7.26

2026.7.25

2026.7.24

2026.7.21

2026.7.20

2026.7.19

2026.7.18

2026.7.17

2026.7.16

2026.7.15

2026.7.14

2026.7.13

2026.7.12

2026.7.11

2026.7.10

2026.7.9

2026.7.8

2026.7.7

2026.7.6

2026.7.5

2026.7.4

2026.7.3

2026.7.2

2026.7.1

2026.6.30

2026.6.29

2026.6.28

2026.6.27

2026.6.26

2026.6.25

2026.6.24

2026.6.23

2026.6.22

2026.6.21

2026.6.20

2026.6.19

2026.6.18

2026.6.16

2026.6.15

2026.6.14

2026.6.13

2026.6.12

2026.6.11

2026.6.10

2026.6.9

2026.6.8

2026.6.7

2026.6.6

2026.6.5

2026.6.4

2026.6.3

2026.6.2

2026.6.1

2026.5.31

2026.5.30

2026.5.29

2026.5.28

2026.5.27

2026.5.26

2026.5.25

2026.5.24

2026.5.23

2026.5.22

2026.5.21

2026.5.20

2026.5.19

2026.5.18

2026.5.17

2026.5.16

2026.5.15

2026.5.14

2026.5.13

2026.5.8

2026.5.7

2026.5.6

2026.5.5

2026.5.4

2026.5.3

2026.5.2

2026.5.1

2026.4.30

2026.4.29

2026.4.27

2026.4.26

2026.4.25

2026.4.22

2026.4.21

2026.4.20

2026.4.19

2026.4.18

2026.4.17

2026.4.16

2026.4.15

2026.4.14

2026.4.13

2026.4.12

2026.4.11

2026.4.10

2026.4.9

2026.4.8

2026.4.7

2026.4.6

2026.4.5

2026.4.4

2026.4.3

2026.4.2

2026.4.1

2026.3.31

2026.3.30

2026.3.29

2026.3.28

2026.3.27

2026.3.26

2026.3.25

2026.3.24

2026.3.23

2026.3.22

2026.3.21

2026.3.20

2026.3.19

2026.3.18

2026.3.17

2026.3.16

2026.3.15

2026.3.14

2026.3.13

2026.3.12

2026.3.11

2026.3.10

2026.3.9

2026.3.8

2026.3.7

2026.3.6

2026.3.5

2026.3.4

2026.3.3

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page