Experiments with getting usable outputs out of local models on a standard Macbook
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
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
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
DHH on Twitter / X
Going to double down on the MacBook mission with Omarchy. We almost have perfect coverage for the vintage Intel era going from 2009-2020. There's a straight shot to get the M1 and M2 machines going too, even if it's a lot more work. But we'll do the work. We'll fix everything.— DHH (@dhh) August 22, 2026
Compiling Models to Megakernels
Fine-grained synchronization, deep pipelines, and zero kernel launch overheads, automatically.
Optimizing On-Device Inference for Apple Silicon
A custom local engine that improves prefill and decode throughput
mzau/broke-cluster
A Poor Man's Apple Silicon LLM Cluster — tuned for MLX, scalable without shame.
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…
First look at the DGX Spark
A local supercomputer between the size of a Mac mini and a Mac mini.
Build Bigger With Small Ai: Running Small Models Locally
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.
Benchmarks | EXO
Transparent benchmarks for LLMs tested on real hardware. Coming soon.
Ivan Fioravanti ᯅ on Twitter / X
"We are releasing Open Source implementations for CoreAILanguageModel and MLXLanguageModel for running a myriad of local models on the Apple Neural Engine or your Mac's GPU" 👀 From #WWDC26: What’s new in the Foundation Models framework video: https://t.co/1NtKWYhNRs pic.twitter.com/HVtBsr3tjL— Ivan Fioravanti ᯅ (@ivanfioravanti) June 9, 2026
videlalvaro/ane-book
Production LLM inference on the Apple Neural Engine — a practitioner's guide, complete with converters, Swift runtimes, and validated model manifests