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Models / OpenAI

OpenAI / MODEL EVIDENCE

OpenAI o1-preview

4 benchmarks · 8 observations · 4 sources

Scores at a glance

4 benchmarks · large dot: OpenAI o1-preview; small dots: closest models where reported

ScienceAgentBench ↗23.9%
3.623.9

OpenAI o1-preview · ScienceAgentBench · Task success · Without expert knowledge ↗

3 more reported results

27.1% · OpenAI o1-preview · ScienceAgentBench · Task success · Without expert knowledge · ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery ↗

18.3% · OpenAI o1-preview · ScienceAgentBench · Task success · With expert knowledge · ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery ↗

27.8% · OpenAI o1-preview · ScienceAgentBench · Task success · With expert knowledge · ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery ↗

Omni-MATH ↗52.55%
14.2460.54

OpenAI o1-preview · Omni-MATH · Overall accuracy · official leaderboard ↗

FACTS Grounding ↗61.7%
61.783.6

OpenAI o1-preview · FACTS Grounding · Final factuality score · judge average · eligibility-filtered evaluation ↗

Closest models by score

Similar positions on shared benchmark leaderboards. Smaller gaps are closer.

46.2 percentile-point gap

3 of 4 shared benchmark comparisons

How similarity is measured

Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.

Filter comparisons to this model →

Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

  1. ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery — published result table ↗

    Ziru Chen, Shijie Chen, Yuting Ning, Qianheng Zhang, Boshi Wang, Botao Yu et al. · 2024

    All 20 authors

    Ziru Chen, Shijie Chen, Yuting Ning, Qianheng Zhang, Boshi Wang, Botao Yu, Yifei Li, Zeyi Liao, Chen Wei, Zitong Lu, Vishal Dey, Mingyi Xue, Frazier N. Baker, Benjamin Burns, Daniel Adu-Ampratwum, Xuhui Huang, Xia Ning, Song Gao, Yu Su, Huan Sun

  2. Commit0: Library Generation from Scratch — published result table ↗

    Zhao, Wenting, Jiang, Nan, Lee, Celine, Chiu, Justin T, Cardie, Claire, Gallé, Matthias et al. · 2024

    All 7 authors

    Zhao, Wenting, Jiang, Nan, Lee, Celine, Chiu, Justin T, Cardie, Claire, Gallé, Matthias, Rush, Alexander M

  3. The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input — published result table ↗

    Alon Jacovi, Andrew Wang, Chris Alberti, Connie Tao, Jon Lipovetz, Kate Olszewska et al. · 2025

    All 26 authors

    Alon Jacovi, Andrew Wang, Chris Alberti, Connie Tao, Jon Lipovetz, Kate Olszewska, Lukas Haas, Michelle Liu, Nate Keating, Adam Bloniarz, Carl Saroufim, Corey Fry, Dror Marcus, Doron Kukliansky, Gaurav Singh Tomar, James Swirhun, Jinwei Xing, Lily Wang, Madhu Gurumurthy, Michael Aaron, Moran Ambar, Rachana Fellinger, Rui Wang, Zizhao Zhang, Sasha Goldshtein, Dipanjan Das

  4. Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models — published result table ↗

    Gao, Bofei, Song, Feifan, Yang, Zhe, Cai, Zefan, Miao, Yibo, Dong, Qingxiu et al. · 2024

    All 20 authors

    Gao, Bofei, Song, Feifan, Yang, Zhe, Cai, Zefan, Miao, Yibo, Dong, Qingxiu, Li, Lei, Ma, Chenghao, Chen, Liang, Xu, Runxin, Tang, Zhengyang, Wang, Benyou, Zan, Daoguang, Quan, Shanghaoran, Zhang, Ge, Sha, Lei, Zhang, Yichang, Ren, Xuancheng, Liu, Tianyu, Chang, Baobao

Names used in source tables

OpenAI o1-preview