Rapid-MLX

Quick Start (60 seconds)

1. Install — pick one path (run only one of these):

One-liner — detects your RAM, picks a starter model (recommended):

curl -fsSL https://rapidmlx.com/install.sh | bash

or Homebrew — prebuilt bottle straight from homebrew-core:

brew install rapid-mlx

Both land the same rapid-mlx CLI. The curl installer additionally installs Python 3.10+ if missing, creates an isolated venv at ~/.rapid-mlx/, symlinks the rapid-mlx CLI into ~/.local/bin/, and prints a serve command sized to your Mac (8–23 GB → qwen3.5-4b-4bit; 24–47 GB → gpt-oss-20b-mxfp4-q8; 48–95 GB → qwen3.6-35b-8bit; 96 GB+ → gpt-oss-120b-mxfp4-q8).

Install security. install.sh is served over HTTPS (HSTS-preload) from rapidmlx.com and is a byte-identical mirror of install.sh at the release commit — read it before running if you like. If you want a cryptographically verified installer rather than trusting the website pipe, don't curl | bash the URL above: instead download the release's install.sh asset, verify it against the cosign-signed SHA256SUMS.txt shipped alongside it, and run that verified copy — full recipe in SECURITY.md. PyPI artifacts additionally carry Sigstore attestations (PEP 740). Two more low-trust paths:

• Pin to a commit hash — curl -fsSL https://raw.githubusercontent.com/raullenchai/Rapid-MLX/<commit>/install.sh -o install.sh && shasum -a 256 install.sh && bash install.sh
• Skip the shell script entirely — use Homebrew, uv, or pip below.

See Alternative install methods for the non-curl paths.

2. Chat with a model right now:

rapid-mlx chat

Defaults to qwen3.5-4b-4bit. First run downloads the weights (~2.5 GB) with a progress bar and drops you into a REPL. Type /help for slash commands, /exit to quit.

3. Or serve it for use from other apps:

rapid-mlx serve qwen3.5-4b-4bit

Starts an OpenAI-compatible HTTP server bound to http://localhost:8000. Point any OpenAI SDK / client (Cursor, Aider, LangChain, OpenCode, PydanticAI, your own scripts) at http://localhost:8000/v1; Claude Code / Anthropic SDK uses http://localhost:8000 (the Anthropic messages route lives at /v1/messages under the same host).

curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"default","messages":[{"role":"user","content":"Say hello"}]}'

from openai import OpenAI
client = OpenAI(base_url="http://localhost:8000/v1", api_key="not-needed")
print(client.chat.completions.create(
    model="default",
    messages=[{"role": "user", "content": "Say hello"}],
).choices[0].message.content)

4. Or wire up your coding agent — one command:

rapid-mlx launch claude-code

With a server running (step 3), this patches Claude Code's local config (~/.config/claude/settings.json) to route at http://localhost:8000 — no manual env vars, no editing JSON by hand. You get a fully local Claude Code: $0 per token, nothing leaves your Mac. Swap in cursor, cline, or continue-dev for the other IDE clients, or run rapid-mlx launch list to see what's detected on this machine.

Vision / audio / video / diffusion models? Base install is text-only (~460 MB). Vision, audio (TTS, STT, voice cloning), video generation, embeddings, and DFlash speculative decoding ship as opt-in extras. → Optional extras

Not into the terminal? Rapid-MLX Desktop bundles the same engine inside a one-click Mac app.

Alternative install methods

The two paths above cover most users — reach for these only if you already manage Python yourself.

brew install rapid-mlx