GPT-4o ranks first on 9 of the 98 benchmarks it has scores on.
May 2024 snapshot Closed weights Flagship
Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| AlpacaEval 2.0 | 57.5% | #1 of 40 | Official leaderboard | |
| WildBench | 58.8 | #2 of 47 | Official leaderboard | |
| RepoQA | 90.6% | #2 of 22 | Official leaderboard | |
| MixEval | 87.9% | #4 of 34 | Official leaderboard | |
| MMBench-CN v1.1 | 82.5% | #28 of 178 | Official leaderboard | |
| MMLU | 88.7% | #21 of 127 | Model card | |
| MGSM | 90.5% | #11 of 52 | Model card | |
| ThaiExam | 63.3% | #6 of 24 | Official leaderboard | |
| SEAL Multilingual | 1,084 | #5 of 19 | Official leaderboard | |
| SEAL Precise Instruction Following | 85.3 | #6 of 18 | Official leaderboard | |
| MMLU-Pro | 72.5% | #80 of 212 | Official leaderboard | |
| DROP | 83.4% | #19 of 40 | Model card | |
| RewardBench | 83.3% | #23 of 48 | Official leaderboard | |
| LLM-AggreFact | 75.9% | #3 of 6 | Official leaderboard | |
| LMArena (Elo) | 1,346 | #180 of 333 | Official leaderboard | |
| SuperGPQA | 39.8% | #36 of 58 | Official leaderboard | |
| MMLU College Biology | 95% | #1 of 1 | Model card | |
| SuperCLUE-RAG | 66.7 | #1 of 1 | Official leaderboard |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| OlympicArena | 40.5% | #1 of 25 | Official leaderboard | |
| MathBench | 70.9% | #1 of 21 | Official leaderboard | |
| ForecastBench | 53.5 | #8 of 86 | Official leaderboard | |
| KOR-Bench | 58% | #4 of 33 | Official leaderboard | |
| OlympiadBench | 25.9% | #1 of 7 | Official leaderboard | |
| ZebraLogic | 28.2% | #13 of 46 | Official leaderboard | |
| MATH | 76.6% | #29 of 93 | Model card | |
| GSM1k | 94.8% | #6 of 15 | Official leaderboard | |
| Omni-MATH | 30.5% | #4 of 9 | Official leaderboard | |
| PutnamBench | 0.15% | #7 of 14 | Official leaderboard | |
| MATH Level 5 | 51% | #50 of 94 | Epoch AI | |
| GPQA Diamond | 48.9% | #151 of 219 | Epoch AI | |
| DTBench | 40.9% | #125 of 178 | Official leaderboard | |
| OTIS Mock AIME 2024-2025 | 6.25% | #167 of 202 | Epoch AI |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| BigCodeBench | 56.1% | #1 of 69 | Official leaderboard | |
| HumanEval | 90.2% | #12 of 95 | Model card | |
| MHPP | 51.4% | #3 of 23 | Official leaderboard | |
| Aider-Edit | 72.9% | #5 of 37 | Official leaderboard | |
| BigCodeBench-Hard | 27.1% | #31 of 96 | Official leaderboard | |
| SWE-bench Lite | 38% | #5 of 15 | Official leaderboard | |
| SEAL Coding | 1,036 | #11 of 26 | Official leaderboard | |
| StructEval | 76% | #12 of 28 | Official leaderboard | |
| SWE-bench | 18.8% | #4 of 9 | Official leaderboard | |
| OpenAI Research Engineer Interview: Coding | 95% | #4 of 7 | Model card | |
| SciCode | 1.50% | #11 of 18 | Official leaderboard | |
| METR Time Horizon | 10 min | #21 of 31 | Official leaderboard | |
| METR Time Horizon 1.1 | 7.0 min | #19 of 26 | Official leaderboard | |
| SWE-bench Verified | 38.4% | #45 of 60 | Official leaderboard | |
| TasteVal | 5.96× | #19 of 20 | Official leaderboard | |
| OpenAI Research Engineer Interview: Multiple Choice | 61% | #9 of 9 | Model card | |
| Agentic tasks (autonomous replication and adaptation) | 0% | #4 of 4 | Model card | |
| Select machine learning engineering tasks from METR | 0% | #1 of 1 | Model card |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MedQA | 89.4% | #1 of 4 | Model card | |
| MedHELM | 49.1 | #9 of 13 | Official leaderboard | |
| MedMCQA | 77% | #1 of 1 | Model card | |
| MedQA Mainland China | 84% | #1 of 1 | Model card | |
| MedQA Taiwan | 91% | #1 of 1 | Model card | |
| MedQA USMLE (5 options) | 86% | #1 of 1 | Model card | |
| MMLU Anatomy | 89% | #1 of 1 | Model card | |
| MMLU Clinical Knowledge | 92% | #1 of 1 | Model card | |
| MMLU College Medicine | 84% | #1 of 1 | Model card | |
| MMLU Medical Genetics | 96% | #1 of 1 | Model card | |
| MMLU Professional Medicine | 94% | #1 of 1 | Model card |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| A-Bench | 79.2% | #7 of 116 | Official leaderboard | |
| VCR (Visual Caption Restoration) | 51.8% | #3 of 42 | Official leaderboard | |
| LongVideoBench | 66.7% | #1 of 13 | Official leaderboard | |
| ScienceQA | 88.5% | #2 of 23 | Epoch AI | |
| MEGA-Bench | 54.2% | #2 of 22 | Official leaderboard | |
| Image2Struct | 80.7 | #2 of 18 | Official leaderboard | |
| Video-MME | 77.2% | #4 of 26 | Official leaderboard | |
| CharXiv | 47.1% | #12 of 77 | Official leaderboard | |
| AI2D | 94.2% | #7 of 44 | Model card | |
| CCBench (MMBench Chinese Culture) | 71.2% | #25 of 152 | Official leaderboard | |
| MTVQA-Test | 27.8% | #3 of 18 | Official leaderboard | |
| MMBench | 83.4% | #26 of 155 | Official leaderboard | |
| MMBench-EN v1.1 | 83.1% | #31 of 178 | Official leaderboard | |
| MMStar | 63.9% | #38 of 173 | Official leaderboard | |
| MMMU | 69.1% | #36 of 136 | Official leaderboard | |
| VHELM | 65.3 | #12 of 41 | Official leaderboard | |
| ActivityNet-QA | 61.9% | #3 of 8 | Model card | |
| EgoSchema | 72.2% | #5 of 12 | Model card | |
| MMMU-Pro | 51.9% | #24 of 57 | Official leaderboard | |
| ChartQA | 85.7% | #21 of 37 | Model card | |
| DocVQA | 92.8% | #21 of 33 | Model card | |
| Vision Arena | 1,162 | #93 of 136 | Official leaderboard | |
| MATH-Vision (MathVision) | 30.4% | #73 of 105 | Official leaderboard | |
| MathVista | 63.8% | #52 of 64 | Model card | |
| Drone-Bench | 14% | #19 of 19 | Official leaderboard | |
| LVBench | 30.8% | #9 of 9 | Official leaderboard |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| OR-Bench | 6.80% | #1 of 28 | Official leaderboard | |
| AgentDojo | 3.66% | #4 of 20 | Official leaderboard | |
| HELM Safety | 94.6 | #25 of 75 | Official leaderboard | |
| Situational Awareness Dataset (SAD) | 50.7% | #6 of 17 | Official leaderboard | |
| Anthropic Red Team | 99.1% | #32 of 75 | Official leaderboard | |
| SimpleSafetyTests | 98.5% | #42 of 75 | Official leaderboard | |
| Tacit Knowledge and Troubleshooting | 69% | #18 of 29 | Model card | |
| Cybench | 12.5% | #17 of 24 | Official leaderboard | |
| AIR-Bench 2024 | 52.8% | #62 of 82 | Official leaderboard | |
| Capture the Flag (Collegiate) | 0% | #11 of 13 | Model card | |
| Capture the Flag (Professional) | 1.00% | #21 of 21 | Model card | |
| Capture the Flag (High School) | 19% | #9 of 9 | Model card | |
| SEAL Adversarial Robustness | 67.0 | #8 of 8 | Official leaderboard | |
| Standard Refusal Evaluation | 93% | #8 of 8 | Model card | |
| Unauthorized voice generation | 100% | #1 of 1 | Model card | |
| Ungrounded inference and sensitive trait attribution | 84% | #1 of 1 | Model card | |
| Voice persuasion study on party preferences | 5.74% | #1 of 1 | Model card |
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| HELM Lite | 93.8 | #1 of 71 | Official leaderboard | |
| OpenVLM Leaderboard | 70.9 | #31 of 173 | Official leaderboard | |
| Conceptual Reasoning Index | 27.1 | #119 of 149 | Official leaderboard | |
| ACCoRD | 44.8 | #122 of 150 | Official leaderboard | |
| LMCA | 16.6% | #115 of 139 | Epoch AI |
OpenAI's models in color, against every other model on the Epoch Capabilities Index, by release date.
The benchmarks the lab chose to headline, with the scores it gave.
Every result in the longer documents the lab published with it. 34 of them aren't in the launch post.