Skip to main content

Unapologetically SM120-only CuTe DSL kernels for NVFP4 GEMM and MoE.

Project description

b12x is an SM120/SM121 CuTe DSL kernel library for (primarily) NVFP4 LLM inference.

It is intentionally narrow. This is not a generic CUDA kernel collection or a full model-serving stack. It does not intend to target any other GPU architectures, including SM100. It is a focused package for a small number of high-performance kernels plus the runtime glue needed to launch them cleanly from sglang/vllm.

Currently supported kernels:

  • NVFP4 fused MoE GEMM
  • NVFP4 dense GEMM
  • BF16/FP8 paged attention
  • Sparse MLA attention (for DSA/NSA only).
pip install b12x

Ask your friendly neighborhood AI agent for further information on how to use this library.

Project details


Download files

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

Source Distribution

b12x-0.9.0.tar.gz (353.9 kB view details)

Uploaded Source

Built Distribution

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

b12x-0.9.0-py3-none-any.whl (405.3 kB view details)

Uploaded Python 3

File details

Details for the file b12x-0.9.0.tar.gz.

File metadata

  • Download URL: b12x-0.9.0.tar.gz
  • Upload date:
  • Size: 353.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for b12x-0.9.0.tar.gz
Algorithm Hash digest
SHA256 eac7bfedb71c66a0fa6e9ce9fa5650a220e9f12ab61b3a0cbe60ce963cd31138
MD5 9d66be0ed798d65289231bff35f845f6
BLAKE2b-256 8bccf8badbda60ea3867749b5e503f673b0556618490f9f5e6895ffb06fc76f5

See more details on using hashes here.

File details

Details for the file b12x-0.9.0-py3-none-any.whl.

File metadata

  • Download URL: b12x-0.9.0-py3-none-any.whl
  • Upload date:
  • Size: 405.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for b12x-0.9.0-py3-none-any.whl
Algorithm Hash digest
SHA256 fe64f2c6c4492ddf1adb20dd92047216008ba34b49667063bd11c262bd14db0d
MD5 eb4fb3ec98973dd90cbcc405333db458
BLAKE2b-256 7e94987c113df9ddd7760a89e9980dd30c7466c84f3dd6bfd40e28c6232623fd

See more details on using hashes here.

Supported by

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