ESLint

Extremely fast Python linter and formatter written in Rust

Ruff is a Python linter and code formatter written in Rust by Astral that runs 10-100x faster than existing tools like flake8, isort, and Black. It implements over 800 lint rules from dozens of popular plugins in a single binary, handles auto-fixing for most violations, and includes a built-in formatter compatible with Black. Adopted by FastAPI, Hugging Face, Pandas, and Apache Airflow, Ruff has over 38,000 GitHub stars and processes entire codebases in milliseconds.

Rust-powered JavaScript linter that is 50-100x faster than ESLint

Oxlint is an extremely fast JavaScript and TypeScript linter built as part of the OXC (Oxidation Compiler) toolchain written in Rust. It runs 50-100x faster than ESLint by parsing and analyzing code in a single optimized pass without requiring any plugins or configurations. Oxlint ships with 520+ built-in rules covering correctness, performance, and style checks, and is designed to run alongside ESLint during migration. Part of Evan You's VoidZero initiative, OXC has over 20,000 GitHub stars.

High-performance Rust JavaScript toolchain

Oxc is a high-performance collection of JavaScript and TypeScript tools written in Rust by the VoidZero team. It includes a parser, linter, formatter, transpiler, minifier, and module resolver that run 50x faster than their JS equivalents. Oxc powers Rolldown and integrates with Vite, forming the backbone of a unified Rust-based toolchain. With 20K+ GitHub stars and MIT license, it provides drop-in replacements for ESLint, Prettier, and Babel with dramatic speed gains.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.

Distributed inference orchestration above vLLM, SGLang and TensorRT-LLM

Open-source, datacenter-scale orchestration layer that coordinates vLLM, SGLang and TensorRT-LLM across nodes with disaggregated serving, KV-aware routing, multi-tier cache management and automatic scaling.

Open-source GPU control plane for scalable AI model serving

Open-source GPU cluster manager that configures vLLM, SGLang, TensorRT-LLM or custom engines, serves models through compatible APIs, and provisions SSH-accessible GPU instances across on-premises, Kubernetes and cloud environments.

Disaggregated KV cache storage and transfer for LLM serving

Open-source infrastructure for disaggregated LLM serving that pools KV caches across prefill and decode workers, with high-performance transfer, distributed storage and integrations for vLLM and SGLang.

Reusable KV cache infrastructure for scalable LLM inference

Open-source KV cache management layer that persists, offloads and reuses model key-value caches across requests and serving engines to reduce repeated prefill work and improve inference throughput.