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4-bit GGUF Quality for MoE Models: Why Only 3B of 180B Params Fire, and How to Prove Parity

This story is from 2026-10-06. It is preserved in the archive; the latest stories are on the live feed.

TL;DR Mixture-of-Experts (MoE) models look enormous on disk, but only a small slice of the weights does work on any single token. A 180B-parameter MoE can activate roughly 3B parameters per forward pass. That sparsity is exactly why 4-bit GGUF quantization behaves so differently on MoE than on a de…

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  1. 2026-10-06 19:10 · DEV Community — AI
    4-bit GGUF Quality for MoE Models: Why Only 3B of 180B Params Fire, and How to Prove Parity

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