For the first time in five generations of Apple Silicon, these chips are not a single piece of silicon. The newly announced M5 Pro and M5 Max use what Apple calls Fusion Architecture. This is a big…
Apple introduces M6 and M5 Ultra for a big leap in performance and AI compute
Apple debuted M6 in the new Mac mini and M5 Ultra in the new Mac Studio, providing an extraordinary leap in performance and AI capabilities.
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
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…
Every Apple M Chip Explained – M1, M2, M3, M4, M5
Apple Vision Pro
Featuring the new powerful M5 chip and comfortable Dual Knit Band, Apple Vision Pro seamlessly blends digital content with your physical space.
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.
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.
Geek Lite on Twitter / X
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
Megakernel: Matching Apple Silicon Efficiency at 2x the Throughput on a RTX 3090
The first megakernel for hybrid DeltaNet/Attention LLMs. 413 tok/s at 1.87 tok/J on a 2020 RTX 3090, matching M5 Max efficiency at 1.8x throughput.
mzau/broke-cluster
A Poor Man's Apple Silicon LLM Cluster — tuned for MLX, scalable without shame.
clandestine.eth 🦇🔊 on Twitter / X
Heterogeneous acceleration on Apple Silicon achieved.ANE + GPU running in parallel.Mirror SD with DFlash, ported to MLX — targeting ANE + GPU simultaneously.The M-series was designed for this. We just hadn't unlocked it yet. pic.twitter.com/raSH0CMN4V— clandestine.eth 🦇🔊 (@0xClandestine) April 15, 2026
Alex Cheema on Twitter / X
A new approach to efficient large scale distributed training on Apple Silicon.Most AI research today is focused on traditional GPUs. These GPUs have a LOT of FLOPS but not much memory. They have a low memory:flops ratio. Apple Silicon has a lot more memory available for the GPU… https://t.co/FsNFnsvphJ pic.twitter.com/LFE1gtAm33— Alex Cheema (@alexocheema) July 11, 2025
0xSero on Twitter / X
I told y’all this is the move. Heterogenous hardware is the way forward. Large cheap pools of mixed memory + specialized accelerators (Nvidia GPUs, DGX Spark, Cerebras wafers) The next year will be dominated by solutions that split the stack. - 3000$ for a used Mac Studio… https://t.co/zMlScSnJ0X— 0xSero (@0xSero) April 1, 2026