Mlx Python Packages

einops

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

mlx-lm

Run LLMs with MLX

mlx

MLX: An array framework for Apple silicon

mlx-metal

MLX: An array framework for Apple silicon

mlx-vlm

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

mlx-audio

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.

mlx-whisper

Examples in the MLX framework

transformerlab

The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.

rapid-mlx

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.

mflux

MLX native implementations of state-of-the-art generative image models

vmlx

vMLX - JANGTQ Uber Compressed MLX Models - L2 Disk Cache (survives restart) + L1 Paged (super fast ttft) + Hybrid SSM Scheduler + Cont Batching + etc!

mlx-cpu

MLX: An array framework for Apple silicon

llmfit

Hundreds of models & providers. One command to find what runs on your hardware.

mlx-openai-server

A high-performance API server that provides OpenAI-compatible endpoints for MLX models. Developed using Python and powered by the FastAPI framework, it provides an efficient, scalable, and user-friendly solution for running MLX-based vision and language models locally with an OpenAI-compatible interface.

mtplx

2.24x decode TPS increase On Qwen 3.6 27B @ temp 0.6 | Native MTP Speculative Decoding On Apple Silicon With No External Drafter.

transformerlab-cli

The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.

jang

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

mlx-cuda-13

MLX: An array framework for Apple silicon

mlx-tune

Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.

llm-autotune

Zero-config local LLM optimization for Ollama, LM Studio, and Apple Silicon MLX. Reduces TTFT by 40%, wall time for local agents by 46%, and RAM usage by 3x.

mlx-cuda-12

MLX: An array framework for Apple silicon

f5-tts-mlx

Implementation of F5-TTS in MLX

vocos-mlx

Implementation of 'Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis', in MLX

benchloop-cli

Local-first CLI for benchmarking LLMs on real hardware — quality, speed, reliability, and a real multi-turn agent loop.