OPTQ: Accurate Quantization for Generative Pre-trained Transformers

Elias Frantar, Saleh Ashkboos, T. Hoefler, Dan Alistarh
2/12/2026

No confident code implementation found for this paper.

Semantic Scholar

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Cite this paper

@article{frantar2026optq,
  title  = {OPTQ: Accurate Quantization for Generative Pre-trained Transformers},
  author = {Elias Frantar and Saleh Ashkboos and T. Hoefler and Dan Alistarh},
  year   = {2026},
  url    = {https://api.semanticscholar.org/CorpusID:363668677c459ebc0ff494655f993a93a0251009},
  journal = {ICLR 2023 2023}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/363668677c459ebc0ff494655f993a93a0251009.svg)](https://codeofpaper.com/paper/363668677c459ebc0ff494655f993a93a0251009)

Discussion