OpenAI, proprietary

# o1-mini

> o1-mini by OpenAI, released September 2024. Ranked #235 of 354 with a Noometry Index of 34.0. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/o1-mini
- Last updated: 2026-10-10
- Title: o1-mini Benchmarks, Price & Rank (October 2026) | Noometry

o1-mini by OpenAI ranks 235th of 354 ranked models on the Noometry Index as of October 2026, with a score of 34.0. Its strongest category is agentic & tool use, where it ranks 118th.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #235 of 354
- **Index score:** 34.0
- **Evidence:** Confirmed 39 results
- **Provider:** [OpenAI](https://noometry.com/providers/openai)
- **Released:** September 12, 2024
- **Weights:** Proprietary
- **Reasoning:** Unknown
- **Context window:** —
- **Max output:** —
- **Input price:** Not listed
- **Output price:** Not listed
- **Blended price:** Not listed
- **Output speed:** Not measured
- **Value:** Not ranked
- **Knowledge cutoff:** Unknown

## Category scores

Each category score combines every public result we have in that category.

o1-mini category scores

1.  Coding 35.5
2.  Agentic & Tool Use 24.6
3.  Reasoning 8.8
4.  Math 35.4
5.  Knowledge 34.9
6.  Multilingual 43.6
7.  Instruction Following 66.7
8.  Long Context 40.1
9.  Writing & Preference 48.4
10.  020406080

o1-mini category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 35.5 | #224 | 4 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 24.6 | #118 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 8.8 | #346 | 6 |
| [Math](https://noometry.com/best/math) | 35.4 | #186 | 4 |
| [Knowledge](https://noometry.com/best/knowledge) | 34.9 | #192 | 3 |
| [Multilingual](https://noometry.com/best/multilingual) | 43.6 | #182 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 66.7 | #206 | 2 |
| [Long Context](https://noometry.com/best/long-context) | 40.1 | #161 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 48.4 | #202 | 5 |

## Strengths and weaknesses

Categories where o1-mini places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

o1-mini: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Long Context](https://noometry.com/best/long-context) | 40.1 | −0.8 | #161 of 296, top 55% |
| [Math](https://noometry.com/best/math) | 35.4 | −1.2 | #186 of 327, top 57% |
| [Knowledge](https://noometry.com/best/knowledge) | 34.9 | −2.5 | #192 of 314, top 62% |

### Weakest categories

o1-mini: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Reasoning](https://noometry.com/best/reasoning) | 8.8 | −14.8 | #346 of 350, top 99% |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 24.6 | −5.8 | #118 of 154, top 77% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 66.7 | −4.5 | #206 of 305, top 68% |

## Closest competitors

The models ranked just above and below o1-mini. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to o1-mini
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Claude 3.5 Sonnet](https://noometry.com/models/claude-3-5-sonnet) | #231 | 34.6 | — | — | [Compare](https://noometry.com/compare/claude-3-5-sonnet-vs-o1-mini) |
| [Qwen3 Coder Next](https://noometry.com/models/qwen3-coder-next) | #232 | 34.3 | $0.29 | — | [Compare](https://noometry.com/compare/o1-mini-vs-qwen3-coder-next) |
| [Devstral Small 2505](https://noometry.com/models/devstral-small) | #233 | 34.3 | $0.15 | 88 | [Compare](https://noometry.com/compare/devstral-small-vs-o1-mini) |
| [Qwen1.5-110B](https://noometry.com/models/qwen1-5-110b) | #234 | 34.2 | — | — | [Compare](https://noometry.com/compare/o1-mini-vs-qwen1-5-110b) |
| [Qwen3.5-9B](https://noometry.com/models/qwen3-5-9b) | #236 | 33.8 | $0.11 | — | [Compare](https://noometry.com/compare/o1-mini-vs-qwen3-5-9b) |
| [Codellama 70b Instruct](https://noometry.com/models/codellama-70b-instruct) | #237 | 33.7 | — | — | [Compare](https://noometry.com/compare/codellama-70b-instruct-vs-o1-mini) |
| [Qwen3 8B](https://noometry.com/models/qwen3-8b) | #238 | 33.7 | $0.31 | — | [Compare](https://noometry.com/compare/o1-mini-vs-qwen3-8b) |
| [Grok-2 (Dec 2024)](https://noometry.com/models/grok-2) | #239 | 33.7 | — | — | [Compare](https://noometry.com/compare/grok-2-vs-o1-mini) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

o1-mini Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Aider Polyglot](https://noometry.com/benchmarks/aider-polyglot) | 32.9% | #31 of 44, top 71% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 36.3% | #89 of 119, top 75% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Coding](https://noometry.com/benchmarks/livebench-coding) | 48% | #18 of 39, top 47% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1362 | #164 of 294, top 56% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [HumanEval+](https://noometry.com/benchmarks/humaneval-plus) | 89% | #2 of 45, top 5% | sept 2024 | [EvalPlus](https://evalplus.github.io/leaderboard.html) |  |
| [MBPP+](https://noometry.com/benchmarks/mbpp-plus) | 78.8% | #2 of 38, top 6% | sept 2024 | [EvalPlus](https://evalplus.github.io/leaderboard.html) |  |

### Agentic & Tool Use

o1-mini Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Cybench](https://noometry.com/benchmarks/cybench) | 10% | #17 of 21, top 81% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

o1-mini Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 0.8% | #70 of 83, top 85% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SimpleBench](https://noometry.com/benchmarks/simplebench) | 18.1% | #74 of 77, top 97% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 14% | #72 of 83, top 87% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 14% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Reasoning](https://noometry.com/benchmarks/livebench-reasoning) | 72.3% | #9 of 39, top 24% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1333 | #173 of 297, top 59% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LiveBench Data Analysis](https://noometry.com/benchmarks/livebench-data-analysis) | 57.9% | #15 of 39, top 39% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 135.82 | #123 of 213, top 58% |  | [Epoch AI](https://epoch.ai/eci) | 2024-09-12 |
| [LiveBench](https://noometry.com/benchmarks/livebench) | 57.8% | #14 of 39, top 36% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

o1-mini Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 46.9% | #114 of 173, top 66% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-03-06 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 44.7% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-03-06 |
| [LiveBench Math](https://noometry.com/benchmarks/livebench-math) | 62% | #12 of 39, top 31% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1358 | #161 of 285, top 57% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [MATH Level 5](https://noometry.com/benchmarks/math-level-5) | 89.2% | #16 of 79, top 21% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-02-13 |
| [MATH Level 5](https://noometry.com/benchmarks/math-level-5) | 84.3% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-01-27 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 1.4% |  | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-03-06 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 1.7% | #57 of 68, top 84% | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-03-06 |

### Knowledge

o1-mini Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 62.4% | #112 of 186, top 61% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-02-13 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 59.5% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-01-27 |
| [Confabulations](https://noometry.com/benchmarks/confabulations) (lower is better) | 18.6% | #30 of 51, top 59% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/confabulations) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1316 | #171 of 273, top 63% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multilingual

o1-mini Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1289 | #182 of 297, top 62% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1314 | #184 of 285, top 65% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1293 | #164 of 223, top 74% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1278 | #161 of 231, top 70% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1245 | #141 of 211, top 67% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1223 | #153 of 213, top 72% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1283 | #190 of 283, top 68% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1303 | #160 of 226, top 71% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

o1-mini Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LiveBench Instruction Following](https://noometry.com/benchmarks/livebench-if) | 65.4% | #23 of 39, top 59% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1304 | #175 of 298, top 59% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

o1-mini Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1320 | #172 of 291, top 60% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

o1-mini Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1317 | #182 of 297, top 62% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1244 | #211 of 295, top 72% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Short-Story Creative Writing](https://noometry.com/benchmarks/lech-mazur-writing) | 64.9% | #34 of 39, top 88% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1314 | #179 of 295, top 61% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LiveBench Language](https://noometry.com/benchmarks/livebench-language) | 40.9% | #18 of 39, top 47% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |

## Compare o1-mini

-   [o1-mini vs Qwen1.5-110B](https://noometry.com/compare/o1-mini-vs-qwen1-5-110b)
-   [o1-mini vs Qwen3.5-9B](https://noometry.com/compare/o1-mini-vs-qwen3-5-9b)
-   [o1-mini vs Devstral Small 2505](https://noometry.com/compare/devstral-small-vs-o1-mini)
-   [o1-mini vs Codellama 70b Instruct](https://noometry.com/compare/codellama-70b-instruct-vs-o1-mini)
-   [o1-mini vs Qwen3 Coder Next](https://noometry.com/compare/o1-mini-vs-qwen3-coder-next)
-   [o1-mini vs Qwen3 8B](https://noometry.com/compare/o1-mini-vs-qwen3-8b)
-   [o1-mini vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-o1-mini)
-   [o1-mini vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-o1-mini)
-   [o1-mini vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-o1-mini)
-   [o1-mini vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-o1-mini)
-   [o1-mini vs Qwen3.8 Max](https://noometry.com/compare/o1-mini-vs-qwen3-8-max)
-   [o1-mini vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-o1-mini)
-   [o1-mini vs Muse Spark 1.3](https://noometry.com/compare/muse-spark-1-3-vs-o1-mini)
-   [o1-mini vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-o1-mini)

## Other OpenAI models

-   [GPT-6 Astra](https://noometry.com/models/gpt-6-astra)70.8
-   [GPT-6.1 Sol](https://noometry.com/models/gpt-6-1-sol)65.6
-   [GPT-5.6 Sol](https://noometry.com/models/gpt-5-6-sol)65.0
-   [GPT-5.5 Pro](https://noometry.com/models/gpt-5-5-pro)64.3
-   [GPT-5.5](https://noometry.com/models/gpt-5-5)63.4
-   [GPT-6 Sol](https://noometry.com/models/gpt-6-sol)61.8
-   [GPT-5.4](https://noometry.com/models/gpt-5-4)59.4
-   [GPT-5.6 Terra](https://noometry.com/models/gpt-5-6-terra)59.2

## Frequently asked questions

### How good is o1-mini?

o1-mini by OpenAI ranks 235th of 354 ranked models on the Noometry Index as of October 2026, with a score of 34.0. Its strongest category is agentic & tool use, where it ranks 118th.

### Is o1-mini open source?

No. o1-mini is proprietary and available only through OpenAI's API and partner platforms.

### What are o1-mini's strengths and weaknesses?

Relative to other ranked models, o1-mini places best in long context, math, knowledge and lowest in reasoning, agentic & tool use, instruction following.

### What is o1-mini best at?

Its best category is agentic & tool use, where it ranks 118th on Noometry.

### Cite this page

Noometry. (2026). o1-mini benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/o1-mini

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/o1-mini.md).