xavier · gflocal 🧑🏾💻 @XavierLocalAI
6'4" philosopher. I run models that need a datacenter, 2 x M5 Max Macs TB5 RDMA. Local AI for regulated industry. New experiment weekly Learn, views will change gflocal.netlify.app Henderson, NV Joined November 2017-
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xavier · gflocal 🧑🏾💻 retweeted
Meet Kimi K3
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@prathamgrv love is invention
xavier · gflocal 🧑🏾💻 retweeted
I deeply resent that AI has forced me to eliminate em dashes from my writing for fear of signaling slop
@BenjaminDEKR stream decks are perfect for this
this is running on a 16gb mac btw
how small can you make a world model? we built mira mini, the first reproduction of mira: • reproduced in a week from scratch • four players, one shared rocket league match, in the browser • distilled to 364m params, weights, code, full report: all open.
@MatthewBerman i think faster than i can type, typing too risky if i lose my train of thought
@0xSero @DegenApeDev grinding gwd just for some ram
@jun_song noooo my storage lands in 5 days!!! think we have 5 days ??
@jun_song Onward and Upward!
This it how it happens slowly then all at once!
The new engine for MLX is in its final stages of development. Just ran GLM-5.2 on a single MacBook (116GB) hitting 41.8 tok/s with a 256k context window. Quality loss is only around ~4%, which puts it right at the 3-4bit quality level. The tech behind this uses a newly
@cetusian agreed, I really like this take "most people benchmark the model and never the fabric"
You don't need all this!!! Don't get finessed
Data center-grade AI. Now on your desk. NVIDIA DGX Spark and DGX Station brings AI-factory-class compute directly into the enterprise—no rack, no cloud dependency. ✅ DGX Station packs 748GB of coherent memory and up to 20 petaflops of AI performance into a deskside system,
The change is happening, when those who said I was crazy start to see the light. You don't need a home lab you just need a book bag. That's the real next unlock.
So @theo published a YouTube video about local inference and its hard limits (you often can *not* run the fancy open weight models locally) and I agree with every word, but then with two M5 Max 128GB systems and RDMA I'm at 50 token/sec with DeepSeek v4 Flash Q5 even without
ooo more to test with exciting !
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