o1-preview · GPQA diamond · Best score (across scorers) · % ↗
OpenAI / MODEL EVIDENCE
o1-preview
21 benchmarks · 29 observations · 19 sources · released 2024-09-12
Scores at a glance
21 benchmarks · large dot: o1-preview; small dots: closest models where reported
o1-preview · MATH level 5 · Best score (across scorers) · % ↗
o1-preview · OTIS Mock AIME 2024-2025 · Best score (across scorers) · % ↗
o1-preview · ARC-AGI · Score · % ↗
o1-preview · Cybench · Unguided % Solved · % ↗
o1-preview · SimpleBench · Score (AVG@5) · % ↗
o1-preview · WeirdML · Accuracy · % ↗
o1-preview · METR task performance & time horizons · Average task accuracy ↗
1 more reported result
20.32659 minutes · o1-preview · METR task performance & time horizons · 50% success task horizon · METR-Horizon-v1.1 · Epoch AI · METR Autonomy / Task-Horizon Suite · public result data ↗
o1-preview · General ECI · 26 October 2026 fit ↗
o1-preview · Aider coding benchmarks · Refactoring · percent correct ↗
o1-preview · ZebraLogic · Grid-level accuracy · complete puzzles ↗
o1-preview · PlanBench · Blocksworld ↗
3 more reported results
52.8% · o1-preview · PlanBench · Mystery Blocksworld · PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change ↗
37.3% · o1-preview · PlanBench · Randomized Mystery Blocksworld · PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change ↗
23.65% · o1-preview · PlanBench · Blocksworld Hard · PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change ↗
o1-preview · Omni-MATH · Rule-based accuracy · rule-based evaluation ↗
o1-preview · JudgeBench · Overall pairwise accuracy · Arena-Hard judge scaffold ↗
o1-preview · Putnam-AXIOM · Original · problem accuracy · original questions ↗
2 more reported results
43% · o1-preview · Putnam-AXIOM · Functional variation · accuracy · five-trial robustness comparison · Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs ↗
51% · o1-preview · Putnam-AXIOM · Matched original subset · accuracy · five-trial robustness comparison · Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs ↗
o1-preview† · CFBench (Chinese Complex Following) · Full set · Constraint satisfaction · full-set evaluation ↗
2 more reported results
63.4% · o1-preview† · CFBench (Chinese Complex Following) · Full set · Instruction satisfaction · full-set evaluation · CFBench: A Comprehensive Constraints-Following Benchmark for LLMs ↗
71.8% · o1-preview† · CFBench (Chinese Complex Following) · Full set · Priority satisfaction · full-set evaluation · CFBench: A Comprehensive Constraints-Following Benchmark for LLMs ↗
o1-preview · SimpleQA · Correct answers · OpenAI Simple Evals · archived July 2025 ↗
o1-preview · HumanEval · Pass@1 · OpenAI Simple Evals · archived July 2025 ↗
o1-preview · DROP (Discrete Reasoning Over Paragraphs) · F1 · three-shot · OpenAI Simple Evals · archived July 2025 ↗
o1 preview · HARP · Human Annotated Reasoning Problems · Short-answer overall accuracy · zero-shot chain of thought ↗
o1-preview · BioLP-Bench · rounded reported accuracy · Figure 1 caption · three-run means ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
3 of 3 shared benchmark comparisons
3 of 3 shared benchmark comparisons
3 of 3 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.
Sources
Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.
- Aider refactoring benchmark ↗
- ARC Prize - Leaderboard ↗
- CFBench: A Comprehensive Constraints-Following Benchmark for LLMs — published result table ↗
All 14 authors
Tao Zhang, Chenglin Zhu, Yanjun Shen, Wenjing Luo, Yan Zhang, Hao Liang, Tao Zhang, Fan Yang, Mingan Lin, Yujing Qiao, Weipeng Chen, Bin Cui, Wentao Zhang, Zenan Zhou
- JudgeBench: A Benchmark for Evaluating LLM-based Judges — published result table ↗
All 8 authors
Sijun Tan, Siyuan Zhuang, Kyle Montgomery, William Y. Tang, Alejandro Cuadron, Chenguang Wang, Raluca Ada Popa, Ion Stoica
- HARP: A challenging human-annotated math reasoning benchmark — published result table ↗
- ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning — published result table ↗
All 7 authors
Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark, Yejin Choi
- Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs — published result table ↗
All 8 authors
Gulati, Aryan, Miranda, Brando, Chen, Eric, Xia, Emily, Fronsdal, Kai, Dumont, Bruno, Obbad, Elyas, Koyejo, Sanmi
- Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models ↗
All 27 authors
Zhang, Andy K., Perry, Neil, Dulepet, Riya, Ji, Joey, Menders, Celeste, Lin, Justin W., Jones, Eliot, Hussein, Gashon, Liu, Samantha, Jasper, Donovan, Peetathawatchai, Pura, Glenn, Ari, Sivashankar, Vikram, Zamoshchin, Daniel, Glikbarg, Leo, Askaryar, Derek, Yang, Mike, Zhang, Teddy, Alluri, Rishi, Tran, Nathan, Sangpisit, Rinnara, Yiorkadjis, Polycarpos, Osele, Kenny, Raghupathi, Gautham, Boneh, Dan, Ho, Daniel E., Liang, Percy
- GPQA Diamond ↗
- MATH Level 5 ↗
- OTIS Mock AIME 2024-2025 ↗
- SimpleBench ↗
- AI benchmarks & capabilities ↗
- WeirdML ↗
- Measuring AI Ability to Complete Long Software Tasks ↗
- Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models — published result table ↗
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
- PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change — published result table ↗
- Simple Evals — model benchmark results ↗
- BioLP-bench: Measuring understanding of biological lab protocols by large language models ↗
Names used in source tables
o1 preview · o1-preview · o1-preview†