Humming

license

Apache-2.0(OSI)

source

public

core-gated

ungated

Apache-2.0 license body confirmed. The repository is public and unarchived and builds the whole product, and the README describes no paid tier, enterprise edition or license-gated build beside it, so source is public and the core ungated.

• https://github.com/inclusionAI/humming/blob/main/LICENSE recorded 2026-09-02

  LICENSE body carries the verbatim Apache License 2.0 text under an Ant Group / inclusionAI copyright header.

• https://api.github.com/repos/inclusionAI/humming recorded 2026-09-02

  Repo metadata for humming's canonical repository - private false, archived false, fork false.

• https://github.com/inclusionAI/humming/blob/main/README.md recorded 2026-09-02

  README describes Humming as a high-performance, lightweight, JIT-compiled GEMM kernel library for quantized inference, supporting dense and MoE GEMM across a wide activation/weight type matrix, with no paid tier, enterprise edition or license-gated build beside the published source.

219 GitHub stars, which lands in the <1K stars band of the stars scale, level 1. Humming has no registry package and is built from source, so no download count exists and the stars scale applies.

• https://api.github.com/repos/inclusionAI/humming recorded 2026-09-02

  Repo metadata - stargazers_count = 219 - for inclusionAI/humming.

Banded on the category feature matrix as one optimization family, applied broadly - the breadth of dtype and hardware coverage puts it beside cutlass and onednn rather than a single-purpose kernel. Placed two bands below the apache-tvm anchor.

• https://github.com/inclusionAI/humming/blob/main/README.md recorded 2026-09-02

  README describes Humming as a high-performance, lightweight, JIT-compiled GEMM kernel library for quantized inference, supporting dense and MoE GEMM across a wide activation/weight type matrix, with no paid tier, enterprise edition or license-gated build beside the published source.