title: README
emoji: 🐆
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Run it on your Mac
Rapid-MLX is a local OpenAI- and Anthropic-compatible inference server for Apple Silicon.
curl -fsSL https://rapidmlx.com/install.sh | bash
rapid-mlx serve ling-3.0-tiny-4bit
curl -s http://localhost:8000/v1/chat/completions -H 'Content-Type: application/json' -d '{"model":"default","messages":[{"role":"user","content":"Say hello"}]}'
Use it from OpenCode / Claude Code / Codex: rapid-mlx agents <name> --setup · Agent setup
Download the Desktop app · The example needs at least 8 GB unified memory; leave extra headroom for long contexts.
Rapid-MLX
Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents.
Up to 4× faster than Apple's MLX (mlx-lm), 1.5× on a typical task — same model, same weights. Qwen3.5-9B 4-bit on a Mac mini M4 Pro, greedy decoding, Rapid-MLX 0.15.6 vs mlx-lm 0.32.0 at defaults, measured 2026-10-04. Per-task results, method and raw data: rapidmlx.com/compare/mlx-lm
curl -fsSL https://rapidmlx.com/install.sh | bash
rapid-mlx serve qwen3.5-9b-4bit # OpenAI-compatible API on http://127.0.0.1:8000/v1
Any MLX model on the Hub runs the same way: rapid-mlx serve <org/repo> (bring your own model).
- Website and docs: rapidmlx.com
- Source: github.com/raullenchai/Rapid-MLX
- Which model fits your Mac: community leaderboard