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Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.

MLX: An array framework for Apple silicon

Native LLM inference server for Apple Silicon. OpenAI + Anthropic API compatible. No Python. Zig backend, Swift frontend macOS app with chat, music, voice, video generation.

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) on the same weights.

Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.

The native UI for Apple Containers and (o)MLX sandboxes, written in swift as a replacement for docker desktop

A modular Swift SDK for audio processing with MLX on Apple Silicon

LLMs and VLMs with MLX Swift

Examples using MLX Swift

A native macOS AI chat app powered by MLX. 100% local inference on Apple Silicon, no cloud required. Built with ShipSwift.

Unofficial Rust bindings to Apple's mlx framework

MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.

Apple MLX native implementations of state-of-the-art generative image & video models

MLX Backend for Nx

Local dictation and meeting notes with Whisper or the OpenAI API. Custom Whisper models, MCP history access, and shared engines over LAN/Tailscale. Optional Parakeet/Nemotron (Windows x64, Linux x86_64), Qwen3-ASR/Moonshine (Windows x64), and Parakeet CPU/experimental MLX (Apple Silicon).

A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.

Run LLMs with MLX

An implementation of the Nvidia's Parakeet models for Apple Silicon using MLX.

Train Large Language Models on MLX.

Local-first healthcare AI: clinical NER & HIPAA PII de-identification that runs 100% on-device. 2,200+ medical models, 21 languages, Apple MLX + Python, no cloud, no patient data leaving your network. Apache-2.0

Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.

AI speech toolkit for Apple Silicon — ASR, TTS, speech-to-speech, VAD, and diarization powered by MLX and CoreML

M-Courtyard: Local AI Model Fine-tuning Assistant for Apple Silicon. Zero-code, zero-cloud, privacy-first desktop app powered by Tauri + React + mlx-lm.

Qwen3-ASR speech recognition on Apple Silicon via MLX

vMLX - Use MLX models easily - JANGQ (GGUF for MLX) - Not dependant on mlx_vlm

Vocello: a private voice studio for Apple Silicon. Write a script, pick or describe a voice, and generate speech locally on your Mac and iPhone. Native Swift and MLX, no Python, no cloud. Mac app and command line out now, iPhone beta on TestFlight. (Formerly QwenVoice.)

MLX Studio - Easiest way to run LLM's on your Mac. All in one engine.

JANG — GGUF for MLX. YOU MUST USE JANG_Q RUNTIME. Adaptive Mixed-Precision Quantization + Runtime for Apple Silicon