OpenAI
availableShows if the model has enough results for an index.o1
o1 is a reasoning model from OpenAI. 22 benchmarks count toward its score, in 7 categories.
IndexOverall score out of 100.45.4 ±3.9
CoverageShare of the index weight with results.95%
SpeedOutput tokens per second.16/s
Input / 1MUS dollars per 1M input tokens.$15
Output / 1MUS dollars per 1M output tokens.$60
ContextMaximum tokens in one request.200K
EloLMArena rating and rank.1366 (#177)
The index is a score out of 100. The ± range shows how much it can change.
27,807 votes. Elo shows what people prefer. It does not change the score.
CapabilitiesScore per category, out of 100.
Out of 100Results
22 counted| BenchmarkThe test name. | CategoryThe capability that the test measures. | ResultThe score from the publisher. | IndexThis result as a score out of 100. | RunThe settings of the run. | DateDate of the result. | Published byThe source of the result. |
|---|---|---|---|---|---|---|
| MATH level 5 | Math | 94.7% | 45.2 | high effort | — | Epoch AI |
| Instruction-Following Eval | Instruction | 92.2% | 49.9 | — | — | Jeffrey Zhou et al. |
| Massive Multitask Language Understanding | Knowledge | 91.8% | — | — | — | Dan Hendrycks et al. |
| MATH 500 | Math | 90.4% | 42.8 | — | 9 Jan 2026 | Vals AI |
| MGSM | Multilingual | 89.3% | — | — | 9 Jan 2026 | Vals AI |
| MMLU Pro | Knowledge | 83.5% | 52.1 | — | 1 Sept 2026 | Vals AI |
| MMMU Pro | Multimodal | 77.4% | 53.3 | — | 1 Sept 2026 | Vals AI |
| GPQA diamond | Knowledge | 76.8% | 49.1 | high effort | — | Epoch AI |
| Graduate-Level Google-Proof Q&A | Knowledge | 75.7% | 48.1 | — | — | David Rein et al. |
| Artificial Analysis GPQA Diamond | Knowledge | 74.7% | 45.1 | — | — | Artificial Analysis |
| OTIS Mock AIME 2024-2025 | Math | 73.3% | 52.6 | high effort | — | Epoch AI |
| GPQA Diamond | Knowledge | 73.2% | 45.9 | — | 1 Sept 2026 | Vals AI |
| AIME | Math | 71.5% | 47.0 | — | 16 Apr 2026 | Vals AI |
| Artificial Analysis IFBench | Instruction | 70.3% | 60.4 | — | — | Artificial Analysis |
| Artificial Analysis Long Context Reasoning | Reasoning | 65.0% | 53.2 | — | — | Artificial Analysis |
| τ²-Bench Tool-Agent-User Evaluation | Agentic | 62.6% | 43.7 | — | — | Victor Barres et al. |
| LiveCodeBench | Coding | 50.3% | 30.0 | — | 1 Sept 2026 | Vals AI |
| SimpleQA Verified | Knowledge | 41.1% | 59.6 | high effort | — | Epoch AI |
| Artificial Analysis Coding Index | Coding | 39.7% | 47.0 | — | — | Artificial Analysis |
| Artificial Analysis Omniscience Accuracy | Knowledge | 34.5% | 56.5 | — | — | Artificial Analysis |
| Artificial Analysis Intelligence Index | Knowledge | 15.2% | 41.4 | — | — | Artificial Analysis |
| Chess Puzzles | Reasoning | 15.0% | 42.9 | high effort | — | Epoch AI |
| FrontierMath-Tiers-1-3-v2-Private | Math | 14.7% | 39.7 | high effort | — | Epoch AI |
| FrontierMath-2025-02-28-Private | Math | 9.3% | 39.3 | high effort | — | Epoch AI |
| Artificial Analysis Humanity's Last Exam | Knowledge | 7.0% | 32.2 | — | — | Artificial Analysis |
| Critical Physics Tasks | Reasoning | 0.3% | 39.0 | — | — | Artificial Analysis |
22 benchmarks count, from 24 of 26 results. A grey row does not count. Too few models took that benchmark.