arXiv Machine Learning August 11, 2026 By Michael Helcig, Eldar Kurtic, Dan Alistarh

Statistically-Lossless Quantization of Large Language Models

Read the original on arXiv Machine Learning →

arXiv:2605. 02404v2 Announce Type: replace Abstract: Model quantization has become essential for efficient large language model deployment, yet existing approaches present clear trade-offs: methods such as GPTQ and AWQ achieve practical compression but are lossy, while lossless techniques preserve fidelity but lack inference acceleration.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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