{"data":{"slug":"raullenchai-rapid-mlx","name":"Rapid-MLX","tagline":"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","github_url":"https://github.com/raullenchai/Rapid-MLX","owner":"raullenchai","repo":"Rapid-MLX","owner_avatar_url":"https://avatars.githubusercontent.com/u/989846?v=4","primary_language":"Python","stars":3250,"forks":382,"topics":["apple-silicon","claude-code","cursor","deepseek","fastapi","hacktoberfest","inference","llm","local-llm","m1","m2","m3","macos","mlx","ollama-alternative","openai-api","python","qwen","tool-calling"],"archived":false,"github_pushed_at":"2026-07-11T20:38:01+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/raullenchai-rapid-mlx","markdown_url":"https://www.graphcanon.com/tools/raullenchai-rapid-mlx.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/raullenchai-rapid-mlx","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=raullenchai-rapid-mlx","description":"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 replacement. Works with Claude Code, Cursor, Aider.","homepage_url":"https://pypi.org/project/rapid-mlx","license":"Apache-2.0","open_issues":23,"watchers":63,"ai_summary":null,"readme_excerpt":"## Quick Start (60 seconds)\n\n**1. Install** (one command, detects your RAM, picks a starter model):\n\n```bash\ncurl -fsSL https://rapidmlx.com/install.sh | bash\n```\n\nInstalls 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`).\n\n> **`curl | bash` security.** `install.sh` is served over HTTPS (HSTS-preload) from `rapidmlx.com` and is a byte-identical mirror of [`install.sh`](install.sh) at the current release commit — read it before running if you like. Two verified alternatives:\n> - **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`\n> - **Skip the shell script entirely** — use Homebrew, `uv`, or `pip` below.\n\nSee [Alternative install methods](#alternative-install-methods) for the non-curl paths.\n\n**2. Chat with a model right now:**\n\n```bash\nrapid-mlx chat\n```\n\nDefaults 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.\n\n**3. Or serve it for use from other apps:**\n\n```bash\nrapid-mlx serve qwen3.5-4b-4bit\n```\n\nStarts 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).\n\n```bash\ncurl http://localhost:8000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"default\",\"messages\":[{\"role\":\"user\",\"content\":\"Say hello\"}]}'\n```\n\n```python\nfrom openai import OpenAI\nclient = OpenAI(base_url=\"http://localhost:8000/v1\", api_key=\"not-needed\")\nprint(client.chat.completions.create(\n    model=\"default\",\n    messages=[{\"role\": \"user\", \"content\": \"Say hello\"}],\n).choices[0].message.content)\n```\n\n> **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](https://rapidmlx.com/docs/extras.html)\n\n> **Not into the terminal?** [**Rapid-MLX Desktop**](https://rapidmlx.com/desktop) bundles the same engine inside a one-click Mac app.\n\n---\n\n---\n\n## Alternative install methods\n\nThe curl one-liner above wraps all of these — reach for these only if you already manage Python yourself.\n\n<details>\n<summary><strong>Homebrew</strong> — Mac-native, tap + trust required on Homebrew 4.x</summary>\n\n```bash\nbrew tap raullenchai/rapid-mlx\nbrew trust raullenchai/rapid-mlx\nbrew install rapid-mlx\n```\n\nUpgrade 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.\n\n</details>\n\n<details>\n<summary><strong>uv</strong> — isolated tool install, auto-manages Python</summary>\n\n```bash\nuv tool install rapid-mlx@latest\n```\n\nDon't have uv yet? `curl -LsSf https://astral.sh/uv/install.sh | sh`. Upgrade with `uv tool upgrade rapid-mlx`.\n\n</details>\n\n<details>\n<summary><strong>pip</strong> — requires Python 3.10+ (macOS ships 3.9)</summary>\n\n```bash\npython3.12 -m pip install rapid-mlx\n```\n\nIf `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`.\n\nFor image-input / VLM models (Qwen-VL, true multimodal), install the vision extra: `pip install 'rapid-mlx[vision]'` — see [Optional extras](https://rapidmlx.com/docs/extras.html).\n\n</details>\n\n---\n\n---\n\n## License\n\nApache 2.0 — see [LICENSE](LICENSE).","github_created_at":"2026-02-25T00:41:44+00:00","created_at":"2026-07-11T23:11:40.298387+00:00","updated_at":"2026-07-12T04:16:43.308053+00:00","categories":[{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"}],"tags":[{"slug":"deepseek","name":"deepseek"},{"slug":"llm","name":"llm"},{"slug":"hacktoberfest","name":"hacktoberfest"},{"slug":"fastapi","name":"fastapi"},{"slug":"apple-silicon","name":"apple-silicon"},{"slug":"claude-code","name":"claude-code"},{"slug":"cursor","name":"cursor"},{"slug":"inference","name":"inference"}],"trust":{"provenance":{"is_fork":false,"github_id":1166182351,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:11:41.624Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":30,"days_since_push":0,"last_release_at":"2026-07-11T20:38:01Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:11:42.083Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T23:11:41.397Z"},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-07-11T23:11:41.397Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-07-11T23:11:41.397Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T23:11:41.397Z"}}}}