mistral.rs
Eric Buehlermistral.rs is an LLM inference engine written in Rust, exposing OpenAI-compatible and Anthropic-compatible endpoints from one binary. It carries paged attention, prefix caching, ISQ and UQFF quantization and multimodal support. It is not affiliated with Mistral AI.
Openness
5 medium confidence- license
- MIT(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
The LICENSE body is the unmodified MIT text, copyright Eric Buehler. The repository is public, active and builds the engine itself, with no enterprise or paid tier in the root tree or README.
- https://api.github.com/repos/EricLBuehler/mistral.rs recorded 2026-08-31
Repo metadata for EricLBuehler/mistral.rs - archived false, 7,638 stars.
- https://raw.githubusercontent.com/EricLBuehler/mistral.rs/master/LICENSE recorded 2026-10-07
LICENSE body, read in full: the stock MIT text, Copyright (c) 2024 Eric Buehler, with no appended condition.
- https://raw.githubusercontent.com/EricLBuehler/mistral.rs/master/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.
Adoption
2 low confidencemistral.rs is distributed mainly as Rust source and prebuilt binaries, so GitHub stars are its adoption signal. A `mistralrs` package on PyPI does resolve to this repository, but its downloads measure a minority channel next to that primary distribution, so it is left undeclared and the star count should be read as a floor.
- https://api.github.com/repos/EricLBuehler/mistral.rs recorded 2026-08-31
Repo metadata - stargazers_count = 7,638 - for EricLBuehler/mistral.rs.
Capability
4 medium confidencemistral.rs sits one tier below vLLM. Its feature set closely overlaps vLLM's own, paged attention, prefix caching, quantization, but SGLang holds the same tier as vLLM on a published multi-node serving record that mistral.rs does not claim.
- https://raw.githubusercontent.com/EricLBuehler/mistral.rs/master/README.md recorded 2026-10-07
README, read for the engine's feature set: Paged attention, prefix caching, ISQ/UQFF quantization and multimodality in one engine, serving OpenAI-compatible and Anthropic-compatible endpoints.
Verified 2026-09-27