Arm Compute Library

license

MIT(OSI)

source

public

core-gated

ungated

MIT 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. GitHub reports no license because the repository follows the REUSE convention rather than carrying a root LICENSE file: REUSE.toml declares MIT throughout, LICENSES/MIT.txt holds the body, and Apache-2.0 and BSD-3-Clause texts sit beside it for vendored third-party code. All three are OSI, so the tier does not turn on which covers a given file.

• https://github.com/ARM-software/ComputeLibrary/blob/main/LICENSES/MIT.txt recorded 2026-08-18

  LICENSES/MIT.txt holds the verbatim MIT text. The repository carries no root LICENSE file - it follows the REUSE convention, with REUSE.toml declaring MIT for the tree and Apache-2.0 and BSD-3-Clause texts beside this one for vendored third-party code - which is why the API reports no license at all.

• https://api.github.com/repos/ARM-software/ComputeLibrary recorded 2026-08-18

  Repo metadata - license spdx_id None, private false, archived false, default branch main - for ARM-software/ComputeLibrary.

• https://github.com/ARM-software/ComputeLibrary/blob/main/README.md recorded 2026-08-18

  README describes a collection of low-level machine learning and computer vision functions optimized for Arm Cortex-A and Neoverse CPUs and Mali GPUs, distributed as source and as prebuilt binaries, with no paid tier, enterprise edition or license-key-gated build beside it.

3,181 GitHub stars, which lands in the 1K-10K stars band of the stars scale, level 2. Distributed as source and prebuilt binaries rather than through a package registry, so no download figure exists and the stars scale applies with its cap of 3.

• https://api.github.com/repos/ARM-software/ComputeLibrary recorded 2026-08-18

  Repo metadata - stargazers_count = 3,181 - for ARM-software/ComputeLibrary.

Banded on the category feature matrix as performance-critical kernel and operator library. Placed two bands below the apache-tvm anchor, on a matrix that bands on how much of the model-to-hardware transformation pipeline a product performs, over how many inputs and targets.

• https://github.com/ARM-software/ComputeLibrary/blob/main/README.md recorded 2026-08-18

  README still documents a collection of low-level machine learning and computer vision functions optimized for Arm Cortex-A and Neoverse CPUs and Mali GPUs, distributed as source and as prebuilt binaries.