在 Apple Silicon Mac 上本地运行 LLM 推理服务，提供比 Ollama 和 llama.cpp 更快的 OpenAI 兼容 API，同时原生支持工具调用和提示缓存。https://t.co/IXet9GW7x0Rapid-MLX 用 Apple 自家的 MLX 框架做推理，搭了个 FastAPI 服务跑 OpenAI 兼容 API。在 Apple Silicon 上比 Ollama 快 2-4 倍，靠… pic.twitter.com/d9QUbAWJSZ— Geek Lite (@QingQ77) May 3, 2026
Ollama is now powered by MLX on Apple Silicon in preview· Ollama Blog
Today, we're previewing the fastest way to run Ollama on Apple silicon, powered by MLX, Apple's machine learning framework.
Rohan Paul on Twitter / X
👨🔧 Github: Native, Apple Silicon–only local LLM server. Similar to Ollama, but built on Apple's MLX- OpenAI API compatible, - Ollama‑compatible- OpenAI‑style tools + tool_choice, with tool_calls parsing and streaming deltasgithub. com/dinoki-ai/osaurus pic.twitter.com/G0NbWnEJcQ— Rohan Paul (@rohanpaul_ai) September 3, 2025
apple-silicon-llm-bench/results/complete_results.html at main · AlexHiesch/apple-silicon-llm-bench
Systematic LLM inference benchmark for Apple Silicon: 8 backends, 7 models, 791 measurements - AlexHiesch/apple-silicon-llm-bench
Seth Godin on the State of Apple’s Software
Link to: http://sethgodin.typepad.com/seths_blog/2016/10/hardware-is-sexy-but-its-software-that-matters.html
Silicon Jungle on Twitter / X
i’m glad they’re doing what they’re doing.but they have one thing wrong.this should be happening at the OS level, not the browser. https://t.co/GiSLenJ0bg— Silicon Jungle (@JungleSilicon) December 2, 2024
mzau/broke-cluster
A Poor Man's Apple Silicon LLM Cluster — tuned for MLX, scalable without shame.
Cua on Twitter / X
1/ Today, as part of our broader research into Apple Silicon virtualization, we're releasing a process-scoped Metal capability layer for macOS VMs. On one M1 Ultra, prompt / generation:TinyLlama: 11.08× / 16.36×Gemma 4 12B: 7.20× / 14.54×Muse Glimmer 30B: 7.55× / 8.87× pic.twitter.com/6UwxgoDowT— Cua (@trycua) August 11, 2026
How Apple Can Own I/O to Own the Universe
Plus! The Great Inflation; Two-Way API Businesses; Zoom and Cities; From ETrade to eToro; Hardware-as-a-Service
delftopenhardware/awesome-open-hardware
🛠Helpful items for making open source hardware projects.
Part 4: Brief history of Apple ML Stack
By Mirai Labs, frontier on-device AI lab. Building the models, inference runtime, and quantization stack from the device constraint up.
Protected by its moat, Apple has time to get AI right
Best of all, the hardware it sells today will run whatever Apple comes up with.
用Macbook微调Qwen3！手把手教你用微调给Qwen起一个新名字
Column: Apple takes its eye off the ball: Why Apple fans are really coming to hate Apple software
There always have been two great virtues in Apple's policy of keeping the development of hardware and core software in-house: their seamless integration with each other and their quality.
