xLLM-AI

license

Apache-2.0(OSI)

source

public(the published repository is the engine)

core features withheld

no — no enterprise path in the repository root and no paid build of the engine in the README

xLLM's LICENSE is the stock Apache-2.0 text with no appended condition, and the public repository is the engine itself rather than a wrapper around closed code. Its root carries no enterprise or commercial directory, and the README describes no license-gated build, so nothing in the published source is held back.

• https://api.github.com/repos/xLLM-AI/xllm recorded 2026-08-31

  Repo metadata for xLLM-AI/xllm - archived false, 1,543 stars.

• https://raw.githubusercontent.com/xLLM-AI/xllm/main/LICENSE recorded 2026-10-07

  LICENSE body, read in full: the stock Apache-2.0 text with no appended condition.

• https://raw.githubusercontent.com/xLLM-AI/xllm/main/README.md recorded 2026-10-07

  README, read for a paid tier, an enterprise edition or a licence-gated build beside the published source, and for whether any component is stated to be private.

The xllm package on PyPI is a different, unrelated project (bobazooba/xllm, an LLM finetuning library), so no package artifact can be declared for this engine. GitHub stars are the only available signal instead.

• https://api.github.com/repos/xLLM-AI/xllm recorded 2026-08-31

  Repo metadata - stargazers_count = 1,543 - for xLLM-AI/xllm.

xLLM sits one tier below vLLM. It has the same decoupled service/engine serving shape, but targets Chinese AI accelerators rather than vLLM's broader multi-vendor hardware support, the same reasoning that places LMDeploy at the same tier.

• https://raw.githubusercontent.com/xLLM-AI/xllm/main/README.md recorded 2026-10-07

  README, read for the engine's feature set: Service-engine decoupled serving on Chinese accelerators, with the scheduling and availability layer separated from the computation layer.