Hacker News·4 min read·hard

Lossless model compression experiment: GLM-5.2 in 25% less memory

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Lossless model compression experiment: GLM-5.2 in 25% less memory
AI Summary

Researchers have successfully compressed the GLM-5.2 large language model by approximately 25-30% using a technique called K15 charged-format accounting. This method replaces standard 9-bit sign-and-exponent symbols with 4-bit codes, maintaining bit-for-bit accuracy while significantly reducing memory requirements.

A full GLM-5.2 scan found 30.168% K15 charged-format accounting. A separate byte-split representation was decoded bit-for-bit across all 59,509 BF16 tensors at 24.967% reduction. Those are distinct evidence classes.

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