Tsinghua PACMAN Lab

license

Apache-2.0(OSI

source

public

core features withheld

no — paid professional services offered by email are support beside the published engine, not a withheld component

The LICENSE body is the unmodified Apache-2.0 text, apart from the appendix copyright line naming Qingcheng.AI. The repository is public and active and is the engine itself; the README's paid professional-services offer is support sold beside it, not a gate on the core.

• https://api.github.com/repos/thu-pacman/chitu recorded 2026-09-01

  Repo metadata for thu-pacman/chitu - archived false, license Apache-2.0, 2,997 stars, default branch public-main, pushed 2026-09-01.

• https://raw.githubusercontent.com/thu-pacman/chitu/public-main/LICENSE recorded 2026-10-07

  LICENSE body, read in full and diffed against the canonical Apache-2.0 text: identical except the appendix copyright line reads "Copyright Qingcheng.AI". No appended terms.

• https://raw.githubusercontent.com/thu-pacman/chitu/public-main/README.md recorded 2026-10-07

  README (Chinese), read for a paid tier (professional services by email only - no gated build): "生产级大模型推理引擎" (production-grade LLM inference engine); milestones - DeepSeek-R1 671B single-GPU via CPU+GPU heterogeneous inference, FP4-to-FP8/BF16 online conversion, Ascend 910B native support, Moore Threads adaptation, chitu.run single-file multi-node launcher; licence section states Apache-2.0 with SPDX-marked third-party snippets under LICENSES/ and submodules under third_party/.

Chitu is distributed through the repository and its release executables rather than a package registry, leaving GitHub stars as the only adoption signal. The README credits production deployments at China Telecom and other Chinese enterprises, which a star count is likely to understate.

• https://api.github.com/repos/thu-pacman/chitu recorded 2026-09-01

  Repo metadata - stargazers_count = 2,997 - for thu-pacman/chitu.

Chitu is a production inference engine distinguished by broad support for Chinese accelerator hardware: five vendors plus pure CPU, along with prefill-decode separated cluster serving. Its feature set is comparable to xLLM, RTP-LLM and FastDeploy, while vLLM and SGLang remain ahead on community-wide throughput.

• https://raw.githubusercontent.com/thu-pacman/chitu/public-main/README.md recorded 2026-10-07

  Milestones and positioning: v0.6.0 chitu.run single-file multi-node/multi-instance/PD- separation launcher; v0.5.x cluster performance and Moore Threads support; v0.4.0 Ascend/NVIDIA/Muxi/Hygon adaptation serving DeepSeek/Qwen/GLM/Kimi; v0.2.2 single-GPU DeepSeek-R1 671B via CPU+GPU heterogeneous inference; v0.3.0 FP4-to-FP8/BF16 kernels.