MLX on Mac with Apple silicon lets AI researchers and developers experiment locally with the latest models and methods in a private…
Exploring LLMs with MLX and the Neural Accelerators in the M5 GPU
Mac with Apple silicon is increasingly popular among AI developers and researchers interested in using their Mac to experiment with the…
oMLX — LLM inference, optimized for your Mac
Native macOS inference server built on MLX with paged SSD KV caching for Apple Silicon.
Run LLMs locally on your Mac · mlx-optiq
Quantize, fine-tune and serve LLMs locally on Apple Silicon. MLX-native, no PyTorch, no cloud. On PyPI.
M5 Ultra Mac Studio Review: The Dream Mac for Local AI Agents
For the past few days, I’ve been testing the (currently) top-of-the-line M5 Ultra Mac Studio with 256 GB of RAM. I’ll cut to the chase: the M5 Ultra Mac Studio is a dream machine for local AI agents. This computer makes it possible to run personal assistants powered by local models with great performance and
mzau/broke-cluster
A Poor Man's Apple Silicon LLM Cluster — tuned for MLX, scalable without shame.
Locally AI - Run AI models locally on your iPhone, iPad, and Mac.
Run Llama, Gemma, Qwen, DeepSeek, and more on your iPhone, iPad, and Mac. Optimized for Apple Silicon. Offline. Private.
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
ModelScope on Twitter / X
🤯 400 Token/S on a MacBook? Yes, you read that right!Shaohong Chen just fine-tuned the Qwen3-0.6B LLM in under 2 minutes using Apple's MLX framework. This is how you turn your MacBook into a serious LLM development rig. A step-by-step guide and performance metrics inside! 🧵… pic.twitter.com/31Cmycy8Mh— ModelScope (@ModelScope2022) October 13, 2025
The Potential of M6 and M5 Ultra for Local AI on macOS
Earlier today, Apple unveiled the new generation of Mac mini and Mac Studio, featuring the latest entries in the Apple silicon family of chips: the M6, available in the Mac mini, and the M5 Ultra, exclusive to the Mac Studio. You can read more details about the announcement and related specs in John’s overview. As
Alex Cheema on Twitter / X
It’s kind of crazy but the shitstorm of supply chain issues has created a new best-in-class local AI deployment: M5 Max MacBook clusters.- The memory unit economics are great - each MacBook has 128GB @ 614GB/s for $5k- M5 Max added tensor cores (Apple Neural Accelerators) with… https://t.co/f8STQ0tLZs pic.twitter.com/FLm3oOnyEl— Alex Cheema (@alexocheema) May 14, 2026
jundot/omlx
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar
Your Laptop Isn’t Ready for LLMs. That’s About to Change
The quest to run large AI models locally on an individual's machine are driving the biggest change in laptop architecture in decades.
Mount Thor — AI Execution Environments on Apple Hardware
Managed macOS environments for AI workloads that require native desktop access, persistent state, or model inference on Apple silicon.
omlx/docs/experimental/dflash_mlx_integration.md at main · jundot/omlx
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar - jundot/omlx
Running local models on an M4 with 24GB memory | jola.dev
Experiments with getting usable outputs out of local models on a standard Macbook
