XLA

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/openxla/xla/blob/main/LICENSE recorded 2026-08-18

  LICENSE file is the verbatim Apache-2.0 text

• https://api.github.com/repos/openxla/xla recorded 2026-08-18

  Repo metadata - license spdx_id Apache-2.0, private false, archived false, default branch main - for openxla/xla.

• https://github.com/openxla/xla/blob/main/README.md recorded 2026-08-18

  README describes an ML compiler for GPUs, CPUs and ML accelerators that takes models from PyTorch, TensorFlow and JAX and optimizes them for execution across hardware platforms, with no paid tier, enterprise edition or license-key-gated build beside it.

4,477 GitHub stars, which lands in the 1K-10K stars band of the stars scale, level 2. XLA ships inside the frameworks that embed it rather than as its own package, so no download channel measures it and the stars scale is the instrument of last resort. Its real reach is that of PyTorch, TensorFlow and JAX, which the stars figure does not capture; a stars-derived band may not claim above 3 and this one does not.

• https://api.github.com/repos/openxla/xla recorded 2026-08-18

  Repo metadata - stargazers_count = 4,477 - for openxla/xla.

Banded on the category feature matrix as retargetable end-to-end compiler. Placed level with 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/openxla/xla/blob/main/README.md recorded 2026-08-18

  README still documents an ML compiler for GPUs, CPUs and ML accelerators that takes models from PyTorch, TensorFlow and JAX and optimizes them for execution across hardware platforms.