Rapid-MLX

Enrichment pending

The fastest local AI engine for Apple Silicon. 4.2x faster than Ollama, 0.08s cached TTFT, 100% tool calling. 17 tool parsers, prompt cache, reasoning separation, cloud routing. Drop-in OpenAI replace

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Python Apache-2.0Created Feb 25, 2026

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Maintenance: Very active (0d since push); As of today · Source: github_public_v1
Provenance: Not a fork · Personal account; As of today · Source: github_public_v1
Security (OSV): No lockfile; As of today · Source: none

Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.

Overview

Capability facts

CLI: CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 11, 2026
Languages: python
Source: github.language+pyproject.toml · Jul 11, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

LangChain integrationLangChain

Source: README excerpt (regex_v1, Jul 11, 2026)

bound to `http://localhost:8000`. Point any OpenAI SDK / client (Cursor, Aider, LangChain, OpenCode, PydanticAI, your own scripts) at **`http://localhost:8000/v1`**; Cla

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Python runtimePython

Source: README excerpt (regex_v1, Jul 11, 2026)

Installs Python 3.10+ if missing, creates an isolated venv at `~/.rapid-mlx/`, symlinks the `rapid-m

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Works with CursorCursor

Source: README excerpt (regex_v1, Jul 11, 2026)

le HTTP server bound to `http://localhost:8000`. Point any OpenAI SDK / client (Cursor, Aider, LangChain, OpenCode, PydanticAI, your own scripts) at **`http://localho

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README

Quick Start (60 seconds)

1. Install (one command, detects your RAM, picks a starter model):

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

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).

curl | bash security. install.sh is served over HTTPS (HSTS-preload) from rapidmlx.com and is a byte-identical mirror of install.sh at the current release commit — read it before running if you like. Two verified alternatives:

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)

Vision / audio / diffusion models? Base install is text-only (~460 MB). Vision, audio, 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 curl one-liner above wraps all of these — reach for these only if you already manage Python yourself.

Homebrew — Mac-native, tap + trust required on Homebrew 4.x

brew tap raullenchai/rapid-mlx
brew trust raullenchai/rapid-mlx
brew install rapid-mlx

Upgrade with brew upgrade rapid-mlx. If brew install stalls on Tapping homebrew/core, run brew tap homebrew/core --force once (one-time ~1.3 GB download) and retry.

uv — isolated tool install, auto-manages Python

uv tool install rapid-mlx@latest

Don't have uv yet? curl -LsSf https://astral.sh/uv/install.sh | sh. Upgrade with uv tool upgrade rapid-mlx.

pip — requires Python 3.10+ (macOS ships 3.9)

python3.12 -m pip install rapid-mlx

If pip install rapid-mlx says "no matching distribution", your Python is too old. brew install python@3.12 first. Upgrade with pip install -U rapid-mlx.

For image-input / VLM models (Qwen-VL, true multimodal), install the vision extra: pip install 'rapid-mlx[vision]' — see Optional extras.