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
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
Nvidia invests $5 billion into Intel to jointly develop PC and data center chips
Intel will help build x86 chips with Nvidia RTX GPU chiplets
Is the Day of the Data Center About to Be Over?
Marco Arment's Setup as the Canary in the Coal Mine—or, Rather, as the 50 Mac Mini Server Farm Vastly More Efficient than the NVIDIA-Powered Cloud-Bound Hyperscalers...
oMLX — LLM inference, optimized for your Mac
Native macOS inference server built on MLX with paged SSD KV caching for Apple Silicon.
Chris Lattner on Twitter / X
Please don’t tell anyone: we aren’t just open sourcing all the models. We are doing the unspeakable: open sourcing all the gpu kernels too. Making them run on multivendor consumer hardware, and opening the door to folks who can beat our work.Plz keep it quiet, ok? 😉— Chris Lattner (@clattner_llvm) March 24, 2026
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
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
Alex Cheema on Twitter / X
4 x M5 Max MacBooks clustered with RDMA:512GB @ 2456GB/s, $20k, 560W, quiet.Find me a better deal, that I can buy today. https://t.co/pWZsHnv0Kl— Alex Cheema (@alexocheema) May 13, 2026
SF Compute: Commoditizing Compute to solve the GPU Bubble forever
Selling GPUs to avoid bankruptcy, empowering researchers with short term clusters, and why CoreWeave is maybe a real estate business
Scott Jenson: Are we really going to use the same Desktop UX forever?
Scott Jenson: Are we really going to use the same Desktop UX forever?
Scott Jenson: Are we really going to use the same Desktop UX forever?
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…
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
mzau/broke-cluster
A Poor Man's Apple Silicon LLM Cluster — tuned for MLX, scalable without shame.
so that new Mac Studio and M5 Ultra have me thinking about 2030 now the wildcard on the $1200ish 2030 Mac Mini is RAM. who knows what the future holds for RAM but the trajectory is clear: a reasonably priced home computer is going to have absolutely sicko inference power within a few years now…
