How 8-bit quantization shrinks an LLM to a quarter of its size — and why a single outlier weight can quietly ruin it
I've been reading about LLM quantization for a while, and almost every explanation I found stopped at the same sentence: "it makes the model smaller." Fine. But how ? And what do you give up? So I wrote my notes down, got stuck on a few things, and built a small playground to help me visualize this…
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- 2026-10-11 07:50 · DEV Community — Machine Learning
How 8-bit quantization shrinks an LLM to a quarter of its size — and why a single outlier weight can quietly ruin it