84.1%
MMLU-Pro (AA run)
Models / OpenAI
OpenAI o · Released 2024-09-12
OpenAI's September 2024 reasoning model. AIME 2024 83.3% with cons@64 sampling. Predecessor to o3 and GPT-5 reasoning tiers.
Legacy reasoning tier — prefer o3 or GPT-5.5 for new math and code work.
74average across 6 tested families
Where OpenAI o1 places on each public benchmark source that publishes a row. Rank counts every model with a latest row in the same test — not a universal quality score.
| Benchmark | Family | Rank | Score | Source | Date |
|---|---|---|---|---|---|
| MATH | Math | #2/ 20 | 97 | Artificial Analysis | 2026-07-21 |
| LiveCodeBench | Coding | #8/ 13 | 68 | Artificial Analysis | 2026-07-21 |
| MMLU-Pro | Knowledge | #8/ 21 | 84 | Artificial Analysis | 2026-07-21 |
| AIME | Math | #12/ 19 | 83 | OpenAI: Learning to Reason | 2024-09-12 |
| τ³-Bench Banking | Agentic | #14/ 64 | 63 | Artificial Analysis | 2026-07-21 |
| IFBench | Reasoning | #34/ 57 | 70 | Artificial Analysis | 2026-07-21 |
| AA-LCR | Long context | #46/ 64 | 59 | Artificial Analysis | 2026-07-21 |
| Artificial Analysis Intelligence Index | Reasoning | #53/ 67 | 23 | Artificial Analysis | 2026-07-21 |
| SciCode | Coding | #56/ 65 | 36 | Artificial Analysis | 2026-07-21 |
| Humanity's Last Exam | Reasoning | #57/ 65 | 8 | Artificial Analysis | 2026-07-21 |
| GPQA Diamond | Reasoning | #58/ 69 | 75 | Artificial Analysis | 2026-07-21 |
| Terminal-Bench | Agentic | #63/ 69 | 13 | Artificial Analysis | 2026-07-21 |
| AA output speed | Performance | #69/ 69 | Artificial Analysis | 2026-07-21 | |
| AA time to first token | Performance | #69/ 69 | Artificial Analysis | 2026-07-21 |
The three highest-scoring carded models in each capability family. Where OpenAI o1 shows up, it's highlighted.
Benchmark rows added to the public ledger for OpenAI o1 in the last 120 days. Older rows live in the full table below.
| Benchmark | Family | Score | Source | Days ago |
|---|---|---|---|---|
| AA-LCR | Long context | 59.33% | Artificial Analysis | 2 |
| AA output speed | Performance | 0 t/s | Artificial Analysis | 2 |
| AA time to first token | Performance | 0.00s | Artificial Analysis | 2 |
| Artificial Analysis Intelligence Index | Reasoning | 23.4% | Artificial Analysis | 2 |
| GPQA Diamond | Reasoning | 74.7% | Artificial Analysis | 2 |
| Humanity's Last Exam | Reasoning | 7.7% | Artificial Analysis | 2 |
| IFBench | Reasoning | 70.34% | Artificial Analysis | 2 |
| LiveCodeBench | Coding | 67.9% | Artificial Analysis | 2 |
| MATH | Math | 97% | Artificial Analysis | 2 |
| MMLU-Pro | Knowledge | 84.1% | Artificial Analysis | 2 |
| SciCode | Coding | 35.8% | Artificial Analysis | 2 |
| τ³-Bench Banking | Agentic | 62.57% | Artificial Analysis | 2 |
| Terminal-Bench | Agentic | 12.88% | Artificial Analysis | 2 |
A high composite that hides a weak family is a trap. These bars surface the families where this model hasn't been publicly tested, and where it leads.
Hover or tab any dot for name, score, and input price.
Every catalog benchmark for OpenAI o1. Scores link to the original source; gaps mean no public row exists yet.
14 of 32 catalog benchmarks have a sourced row for OpenAI o1.
84.1%
MMLU-Pro (AA run)
23.4%
AA Intelligence Index v4.1
74.7%
GPQA Diamond (AA run)
7.7%
HLE (AA run)
70.34%
IFBench (AA run)
67.9%
LiveCodeBench (AA run)
35.8%
SciCode (AA run)
12.88%
Terminal-Bench Hard (AA run)
62.57%
τ²-Bench Banking (AA run; maps to τ³ explainer)
59.33%
AA-LCR (AA run)
0 t/s
Median output tokens/s (1k prompt, default provider)
0.00s
Median time to first token (1k prompt, default provider)