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Open Source LLMs

MLX

🇨🇳 中文 / 🇬🇧 English — 双语介绍
🇨🇳 中文

Apple 机器学习研究团队为 Apple silicon 写的数组计算框架:统一内存架构让 CPU 与 GPU 共用同一块内存,省掉来回拷贝;API 接近 NumPy,配 mlx-examples 有 LoRA 微调、Whisper、图像生成等可直接跑的样例,是 Mac 本地跑模型的主力栈。 ⭐ GitHub Stars: 29k+ 🔗 仓库: https://github.com/ml-explore/mlx

🇬🇧 English

An array framework from Apple machine learning research built for Apple silicon: the unified memory architecture lets CPU and GPU share one buffer instead of copying, and the API stays close to NumPy. mlx-examples ships runnable LoRA fine-tuning, Whisper and image generation samples, which makes it the default stack for running models locally on a Mac. ⭐ GitHub Stars: 29k+ 🔗 Repository: https://github.com/ml-explore/mlx

📋 Product Info

Category: Open Source LLMs
Listed on: 2026-10-20
Last verified: 2026-10-20
Official site: https://github.com/ml-explore/mlx
Open source: GitHub repository ↗
Tags: apple-silicon,machine-learning,array-framework,local-llm,open-source

🎯 Why This Tool

MLX belongs to the Open Source LLMs category on hedirbase. Tagged with: apple-silicon,machine-learning,array-framework,local-llm,open-source.

An array framework from Apple machine learning research built for Apple silicon: the unified memory architecture lets CPU and GPU share one buffer instead of copying, and the API stays close to NumPy.

✓ Manually reviewed ✅ Last verified: 2026-10-20 📁 Open source 🌐 Curated for independents
🌎 访问 MLX → 📦 GitHub