Compressing LLMs to Less Than 1 Bit Per Parameter
LotfiSanae · x · 2026-07-14
Resharing a study on compressing billion-parameter scale LLMs: the authors propose requential coding, claiming it can compress weights to less than 1 bit per parameter.
This work also attempts to explain a broader question: why models haven't hit a "generalization wall" as their scale continues to increase. The original thread is attached, authored by Shikai Qiu et al.
Related event: New Research Compresses LLMs to Sub-1-Bit Per Parameter(3 posts)→
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