OpenAI, proprietary

# o3-mini

> o3-mini by OpenAI, released December 2024. Ranked #212 of 354 with a Noometry Index of 36.7. API: $1.10 in / $4.40 out per M tokens. 200K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/o3-mini
- Last updated: 2026-10-10
- Title: o3-mini Benchmarks, Price & Rank (October 2026) | Noometry

o3-mini by OpenAI ranks 212th of 354 ranked models on the Noometry Index as of October 2026, with a score of 36.7. Its strongest category is instruction following, where it ranks 72nd. API pricing starts at $1.10 per million input tokens and $4.40 per million output tokens, with a 200K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #212 of 354
- **Index score:** 36.7
- **Evidence:** Confirmed 51 results
- **Provider:** [OpenAI](https://noometry.com/providers/openai)
- **Released:** December 20, 2024
- **Weights:** Proprietary
- **Reasoning:** Yes
- **Context window:** 200K
- **Max output:** 100K
- **Input price:** $1.10 / M
- **Output price:** $4.40 / M
- **Blended price:** $1.93 / M
- **Output speed:** Not measured
- **Value:** #152 of 219
- **Knowledge cutoff:** May 2024
- **Input:** text

## Category scores

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

o3-mini category scores

1.  Coding 40.8
2.  Agentic & Tool Use 29.6
3.  Reasoning 16.3
4.  Math 28.1
5.  Knowledge 38.3
6.  Multilingual 45.7
7.  Instruction Following 75.1
8.  Long Context 33.8
9.  Writing & Preference 50.3
10.  020406080

o3-mini category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 40.8 | #132 | 7 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 29.6 | #84 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 16.3 | #305 | 11 |
| [Math](https://noometry.com/best/math) | 28.1 | #244 | 6 |
| [Knowledge](https://noometry.com/best/knowledge) | 38.3 | #146 | 4 |
| [Multilingual](https://noometry.com/best/multilingual) | 45.7 | #164 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 75.1 | #72 | 2 |
| [Long Context](https://noometry.com/best/long-context) | 33.8 | #256 | 2 |
| [Writing & Preference](https://noometry.com/best/writing) | 50.3 | #182 | 5 |

## Strengths and weaknesses

Categories where o3-mini places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

o3-mini: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Instruction Following](https://noometry.com/best/instruction-following) | 75.1 | +3.8 | #72 of 305, top 24% |
| [Coding](https://noometry.com/best/coding) | 40.8 | +2.1 | #132 of 340, top 39% |
| [Knowledge](https://noometry.com/best/knowledge) | 38.3 | +1.0 | #146 of 314, top 47% |

### Weakest categories

o3-mini: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Reasoning](https://noometry.com/best/reasoning) | 16.3 | −7.3 | #305 of 350, top 88% |
| [Long Context](https://noometry.com/best/long-context) | 33.8 | −7.1 | #256 of 296, top 87% |
| [Math](https://noometry.com/best/math) | 28.1 | −8.5 | #244 of 327, top 75% |

## Closest competitors

The models ranked just above and below o3-mini. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to o3-mini
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [GPT-4.5](https://noometry.com/models/gpt-4-5) | #208 | 37.2 | — | — | [Compare](https://noometry.com/compare/gpt-4-5-vs-o3-mini) |
| [Yi-Lightning](https://noometry.com/models/yi-lightning) | #209 | 37.1 | — | — | [Compare](https://noometry.com/compare/o3-mini-vs-yi-lightning) |
| [Qwen Plus](https://noometry.com/models/qwen-plus) | #210 | 37.1 | $0.60 | 37 | [Compare](https://noometry.com/compare/o3-mini-vs-qwen-plus) |
| [Gemini 2.5 Flash-Lite](https://noometry.com/models/gemini-2-5-flash-lite) | #211 | 37.0 | $0.18 | 172 | [Compare](https://noometry.com/compare/gemini-2-5-flash-lite-vs-o3-mini) |
| [Llama 3.1 Nemotron Ultra 253b v1](https://noometry.com/models/llama-3-1-nemotron-ultra-253b-v1) | #213 | 36.7 | — | — | [Compare](https://noometry.com/compare/llama-3-1-nemotron-ultra-253b-v1-vs-o3-mini) |
| [Granite 4.0 H Small](https://noometry.com/models/ibm-granite-h-small) | #214 | 36.5 | — | — | [Compare](https://noometry.com/compare/ibm-granite-h-small-vs-o3-mini) |
| [Command A](https://noometry.com/models/command-a) | #215 | 36.5 | $4.38 | 28 | [Compare](https://noometry.com/compare/command-a-vs-o3-mini) |
| [Grok Build 0.1](https://noometry.com/models/grok-build-0-1) | #216 | 36.4 | $1.25 | — | [Compare](https://noometry.com/compare/grok-build-0-1-vs-o3-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

o3-mini Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Aider Polyglot](https://noometry.com/benchmarks/aider-polyglot) | 60.4% | #13 of 44, top 30% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Aider Polyglot](https://noometry.com/benchmarks/aider-polyglot) | 53.8% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 39.8% | #82 of 121, top 68% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GSO](https://noometry.com/benchmarks/gso-bench) | 1.3% | #30 of 31, top 97% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GSO](https://noometry.com/benchmarks/gso-bench) | 1.3% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 43.7% | #64 of 119, top 54% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Coding](https://noometry.com/benchmarks/livebench-coding) | 82.7% | #2 of 39, top 6% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Coding](https://noometry.com/benchmarks/livebench-coding) | 61.5% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Coding](https://noometry.com/benchmarks/livebench-coding) | 65.4% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1378 | #153 of 294, top 53% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [CadEval](https://noometry.com/benchmarks/cadeval) | 54% | #6 of 14, top 43% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

o3-mini Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Cybench](https://noometry.com/benchmarks/cybench) | 22.5% | #10 of 21, top 48% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

o3-mini Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 3% | #63 of 83, top 76% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 0% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 2.1% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SimpleBench](https://noometry.com/benchmarks/simplebench) | 22.8% | #69 of 77, top 90% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 34.5% | #63 of 83, top 76% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 14.5% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 22.3% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 0.3% | #96 of 134, top 72% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 17% | #66 of 129, top 52% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-12-08 |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 6% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-15 |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 9% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [LiveBench Reasoning](https://noometry.com/benchmarks/livebench-reasoning) | 89.6% | #4 of 39, top 11% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Reasoning](https://noometry.com/benchmarks/livebench-reasoning) | 69.8% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Reasoning](https://noometry.com/benchmarks/livebench-reasoning) | 86.3% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1366 | #149 of 297, top 51% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 7% | #68 of 74, top 92% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 68.8% | #95 of 151, top 63% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Data Analysis](https://noometry.com/benchmarks/livebench-data-analysis) | 70.6% | #4 of 39, top 11% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Data Analysis](https://noometry.com/benchmarks/livebench-data-analysis) | 62% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Data Analysis](https://noometry.com/benchmarks/livebench-data-analysis) | 66.6% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 19% | #94 of 125, top 76% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 140.34 | #107 of 213, top 51% |  | [Epoch AI](https://epoch.ai/eci) | 2025-01-31 |
| [ForecastBench](https://noometry.com/benchmarks/forecastbench) | 59.6 | #37 of 72, top 52% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench](https://noometry.com/benchmarks/livebench) | 75.9% | #4 of 39, top 11% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench](https://noometry.com/benchmarks/livebench) | 62.5% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench](https://noometry.com/benchmarks/livebench) | 70% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

o3-mini Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 18.6% | #72 of 81, top 89% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-11 |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 3.9% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 10.5% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 0% | #63 of 63, top 100% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-11 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 76.9% | #84 of 173, top 49% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-02-27 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 44.4% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-20 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 63.9% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-02-25 |
| [LiveBench Math](https://noometry.com/benchmarks/livebench-math) | 77.3% | #7 of 39, top 18% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Math](https://noometry.com/benchmarks/livebench-math) | 63.1% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Math](https://noometry.com/benchmarks/livebench-math) | 72.4% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1396 | #132 of 285, top 47% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [MATH Level 5](https://noometry.com/benchmarks/math-level-5) | 96.5% | #8 of 79, top 11% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-02-13 |
| [MATH Level 5](https://noometry.com/benchmarks/math-level-5) | 95.2% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-01-31 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 12.4% | #36 of 68, top 53% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-11-16 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 8.1% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-03-06 |
| [FrontierMath Tier 4 (v1)](https://noometry.com/benchmarks/frontiermath-tier-4-v1) | 4.2% | #34 of 55, top 62% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-07-01 |

### Knowledge

o3-mini Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 77% | #86 of 186, top 47% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2025-02-13 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 68.2% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-20 |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 74.3% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2025-01-31 |
| [SimpleQA Verified](https://noometry.com/benchmarks/simpleqa-verified) | 15.3% | #69 of 77, top 90% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-31 |
| [Confabulations](https://noometry.com/benchmarks/confabulations) (lower is better) | 17.9% | #28 of 51, top 55% | medium reasoning | [Lech Mazur benchmarks](https://github.com/lechmazur/confabulations) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1364 | #145 of 273, top 54% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multilingual

o3-mini Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1319 | #164 of 297, top 56% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1379 | #152 of 285, top 54% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1334 | #150 of 223, top 68% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1303 | #149 of 231, top 65% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1286 | #129 of 211, top 62% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1314 | #121 of 213, top 57% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1304 | #175 of 283, top 62% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1321 | #154 of 226, top 69% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

o3-mini Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LiveBench Instruction Following](https://noometry.com/benchmarks/livebench-if) | 84.4% | #3 of 39, top 8% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Instruction Following](https://noometry.com/benchmarks/livebench-if) | 80.1% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Instruction Following](https://noometry.com/benchmarks/livebench-if) | 83.2% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1337 | #151 of 298, top 51% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

o3-mini Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Fiction.LiveBench](https://noometry.com/benchmarks/fiction-livebench) | 50% | #35 of 47, top 75% | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1343 | #157 of 291, top 54% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

o3-mini Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1337 | #168 of 297, top 57% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1286 | #181 of 295, top 62% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Short-Story Creative Writing](https://noometry.com/benchmarks/lech-mazur-writing) | 61.7% | #38 of 39, top 98% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Short-Story Creative Writing](https://noometry.com/benchmarks/lech-mazur-writing) | 61.5% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1320 | #175 of 295, top 60% | high | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LiveBench Language](https://noometry.com/benchmarks/livebench-language) | 50.7% | #10 of 39, top 26% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Language](https://noometry.com/benchmarks/livebench-language) | 38.3% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LiveBench Language](https://noometry.com/benchmarks/livebench-language) | 46.3% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |

## API pricing by provider

o3-mini API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [azure](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models) | $1.10 | $4.40 | $0.55 | 2026-10-10 |
| [openai](https://platform.openai.com/docs/models) | $1.10 | $4.40 | $0.55 | 2026-10-10 |
| [openrouter](https://openrouter.ai/openai/o3-mini) | $1.10 | $4.40 | $0.55 | 2026-10-10 |

[All OpenAI API prices →](https://noometry.com/llm-pricing/openai) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare o3-mini

-   [o3-mini vs o1-mini](https://noometry.com/compare/o1-mini-vs-o3-mini)
-   [o3-mini vs Gemini 2.5 Flash-Lite](https://noometry.com/compare/gemini-2-5-flash-lite-vs-o3-mini)
-   [o3-mini vs Llama 3.1 Nemotron Ultra 253b v1](https://noometry.com/compare/llama-3-1-nemotron-ultra-253b-v1-vs-o3-mini)
-   [o3-mini vs Qwen Plus](https://noometry.com/compare/o3-mini-vs-qwen-plus)
-   [o3-mini vs Granite 4.0 H Small](https://noometry.com/compare/ibm-granite-h-small-vs-o3-mini)
-   [o3-mini vs Yi-Lightning](https://noometry.com/compare/o3-mini-vs-yi-lightning)
-   [o3-mini vs Command A](https://noometry.com/compare/command-a-vs-o3-mini)
-   [o3-mini vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-o3-mini)
-   [o3-mini vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-o3-mini)
-   [o3-mini vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-o3-mini)
-   [o3-mini vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-o3-mini)
-   [o3-mini vs Qwen3.8 Max](https://noometry.com/compare/o3-mini-vs-qwen3-8-max)
-   [o3-mini vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-o3-mini)
-   [o3-mini vs Muse Spark 1.3](https://noometry.com/compare/muse-spark-1-3-vs-o3-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 o3-mini?

o3-mini by OpenAI ranks 212th of 354 ranked models on the Noometry Index as of October 2026, with a score of 36.7. Its strongest category is instruction following, where it ranks 72nd. API pricing starts at $1.10 per million input tokens and $4.40 per million output tokens, with a 200K-token context window.

### How much does o3-mini cost?

o3-mini costs $1.10 per million input tokens and $4.40 per million output tokens on OpenAI's own API, with cached input at $0.55.

### What is o3-mini's context window?

o3-mini accepts up to 200K tokens of input and can write up to 100K tokens in one response.

### Is o3-mini open source?

No. o3-mini is proprietary and available only through OpenAI's API and partner platforms.

### What are o3-mini's strengths and weaknesses?

Relative to other ranked models, o3-mini places best in instruction following, coding, knowledge and lowest in reasoning, long context, math.

### What is o3-mini best at?

Its best category is instruction following, where it ranks 72nd on Noometry.

### Cite this page

Noometry. (2026). o3-mini benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/o3-mini

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/o3-mini.md).