Overview

Plain English

MLX: An array framework for Apple silicon.

Technical

MLX: An array framework for Apple silicon.

Technical scorecard

License MIT

Commercial use Yes

OpenAI-compatible API No

REST API No

Fine-tuning support No

Quantization support No

Docker available No

GUI / no-code available No

Telemetry None

Offline after setup Yes

Data & Privacy

After setup, this listing is marked as usable offline. Confirm network behavior against the upstream project before regulated deployment.

Not verified in this directory yet. Review the upstream docs for persistence, logs, and workspace storage.

Commercial use is marked as allowed or likely allowed by the listed license.

None

Last verified: May 17, 2026. Maintainer verification should be treated as directory guidance, not legal advice.

Setup & Installation

Medium

A developer can usually get this running with standard docs.

C++, Bare Metal

# Start with the official project documentation
# https://github.com/ml-explore/mlx

Hardware Requirements

RAM8 GB minimum / 16 GB recommended

Hardware tagsApple Silicon (Metal)

Model formatsNot specified

Primary languageC++

Works Well With

You might also evaluate

Ollama Get up and running with Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other mode... llama.cpp LLM inference in C/C++.... vLLM A high-throughput and memory-efficient inference and serving engine for LLMs.... LocalAI LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any...