Re:Show HN: Run 500B+ Parameter LLMs Locally on a Mac Mini
by ryanholtdev on Monday March 09, 2026 @11:19AM
(#47310237)
Running a Mac Mini M4 as a home server for a bunch of automation scripts right now. The mmap-based layer streaming is the part I'm most curious about -- how does latency look when you're streaming layers from disk mid-inference? I'd expect throughput to degrade sharply once you exceed unified memory, but maybe the Top-K sparsity masks enough of the weight accesses that it's not as bad as sequential streaming would be. What's the actual tokens/sec at 140B scale on the base Mac Mini config?
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Re:Show HN: Run 500B+ Parameter LLMs Locally on a Mac Mini
by anentropic on Monday March 09, 2026 @12:17PM
(#47311065)
Yeah...
https://github.com/opengraviton/graviton?tab=readme-ov-file#...
the benchmarks don't show any results for using these larger-than-memory models, only the size difference
it all smells quite sloppy