o3-mini
o3-mini is OpenAI's most recent small reasoning model, providing high intelligence at the same cost and latency targets of o1-mini.
text → text · made by OpenAI
Sold by 14 ways
| Seller | Lane | Rate |
|---|---|---|
| Microsoft Azure AI cloud | batch | $0.6per Mtok in$2.42per Mtok outraw.githubusercontent.com · read 2026-10-31 |
| DigitalOcean cloud | standard | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cachedmodels.dev · read 2026-10-31 |
| Microsoft Azure AI cloud | standard | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cachedmodels.dev · read 2026-10-31 |
| OpenAI api | standard | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cacheddevelopers.openai.com · read 2026-08-24 |
| Nous Research 2 ways | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cached | |
| Nous Research aggregator | batch | $0.55per Mtok in$2.2per Mtok out$0.28per Mtok cachedinference-api.nousresearch.com · read 2026-09-12 |
| Nous Research aggregator | standard | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cachedinference-api.nousresearch.com · read 2026-09-12 |
| OpenRouter 2 ways | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cached | |
| OpenRouter aggregator | batch | $0.55per Mtok in$2.2per Mtok out$0.28per Mtok cachedopenrouter.ai · read 2026-08-24 |
| OpenRouter aggregator | standard | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cachedopenrouter.ai · read 2026-08-24 |
| Requesty aggregatornot on the seller's list today | openai low | $0.99per Mtok in$3.96per Mtok out$0.49per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | openai medium | $0.99per Mtok in$3.96per Mtok out$0.49per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregator | openai | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cachedrouter.requesty.ai · read 2026-08-28 |
| Requesty aggregatornot on the seller's list today | openai-responses | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cachedrouter.requesty.ai · read 2026-08-28 |
| ElectronHub 0 ways | $1.1per Mtok in$4.4per Mtok out | |
| ElectronHub aggregatornot on the seller's list today | standard | $1.1per Mtok in$4.4per Mtok outapi.electronhub.ai · read 2026-10-18 |
| Vercel AI Gateway aggregator | standard | $1.1per Mtok in$4.4per Mtok out$0.55per Mtok cachedai-gateway.vercel.sh · read 2026-08-25 |
Measured 32 standings
| Place | Board | Metric | Score |
|---|---|---|---|
| 4thof 54 | Live bench — Epoch AI | Global average (high) | 75.88 |
| 6thof 15 | Cad eval — Epoch AI | Overall pass (%) (medium) | 0.54 |
| 10thof 108 | Math level 5 — Epoch AI | mean_score (high) | 96.488 |
| 11thof 22 | Cybench — Epoch AI | Unguided % Solved (medium) | 0.225 |
| 27thof 72 | Aider polyglot — Epoch AI | Percent correct (high) | 60.4 |
| 30thof 42 | Fictionlivebench — Epoch AI | 120k token score (medium) | 0.438 |
| 32ndof 69 | Aider polyglot coding leaderboard | Percent correct (medium) | 53.8 |
| 40thof 92 | Forecastbench — Epoch AI | Overall score | 63.8 |
| 40thof 42 | Gso — Epoch AI | Score OPT@1 (high) | 0.013 |
| 45thof 72 | Frontiermath tier 4 — Epoch AI | mean_score (high) | 4.167 |
| 47thof 49 | Lech mazur writing — Epoch AI | Mean score (high) | 6.17 |
| 52ndof 101 | FrontierMath (Tiers 1-3) | mean_score (high) | 12.414 |
| 78thof 78 | Frontiermath tier 4 v2 — Epoch AI | mean_score (high) | 0 |
| 84thof 93 | Simpleqa verified — Epoch AI | mean_score (high) | 15.3 |
| 92ndof 102 | Simplebench — Epoch AI | Score (AVG@5) (high) | 0.228 |
| 97thof 173 | Weirdml — Epoch AI | Accuracy (high) | 43.7 |
| 98thof 122 | Frontiermath tiers 1 3 v2 — Epoch AI | mean_score (high) | 18.596 |
| 110thof 154 | Chess puzzles — Epoch AI | mean_score (high) | 15 |
| 126thof 142 | Mystery game puzzles — Epoch AI | mean_score (high) | 7 |
| 132ndof 306 | OTIS Mock AIME 2024-2025 | mean_score (high) | 76.944 |
| 151stof 326 | GPQA Diamond | mean_score (high) | 77.02 |
| 162ndof 235 | Dtbench — Epoch AI | Accuracy (high) | 68.8 |
| 164thof 197 | Lmca — Epoch AI | Score (high) | 18.97 |
| 166thof 235 | Scicode — Epoch AI | Score (high) | 42.824 |
| 195thof 260 | Critpt — Epoch AI | Accuracy (high) | 0.286 |
| 205thof 273 | ARC-AGI-1 (Public Eval) | Score (%) (high) | 46.58 |
| 213thof 290 | Arc agi 2 — Epoch AI | Score (high) | 2.99 |
| 215thof 298 | ARC-AGI-2 (Semi-Private) | Score (%) (high) | 2.99 |
| 218thof 414 | LMArena · Text | Score (Elo) | 1348 |
| 220thof 298 | ARC-AGI-1 (Semi-Private) | Score (%) (high) | 34.5 |
| 230thof 309 | Arc agi — Epoch AI | Score (high) | 34.5 |
| 254thof 282 | ARC-AGI-2 (Public Eval) | Score (%) (low) | 0 |
About
o3-mini — a text model from OpenAI, sold by 7 companies from $1.1 in and $4.4 out per million tokens, placed 4th of 54 on Live bench — Epoch AI.
It takes text and returns text, with a context window of 200,000 tokens. It was published in December 2024, trained on material up to May 2024. Its sellers say it can reason step by step and call a tool. The catalogue files it under reasoning, code and agents. Seven companies sell it. The cheapest is $1.1 in and $4.4 out per million tokens at DigitalOcean. Beside the standard rate there are batch and separately routed lanes. It has been measured on 32 boards, and stands best at 4th of 54 on Live bench — Epoch AI.
Every current figure
- Maker
- OpenAI
- Register
- model
- Takes
- text
- Returns
- text
- Context
- 200,000 tokens
- Longest answer
- 131,072 tokens
- Published
- December 2024
- Knowledge to
- May 2024
- Licence
- not read
- Sellers
- 7
- Price
- $1.1 in and $4.4 out per million tokens — DigitalOcean
- Boards
- 32
- Best place
- 4th of 54 — Live bench — Epoch AI
Known as 11 names
o3-mini (2025-01-31)O3-Mini-2025-01-31 (High)O3-Mini-2025-01-31 (Low)O3-Mini-2025-01-31 (Med)o3 mini 0131openai/o3-miniopenai/o3-mini:batchopenai-responses/o3-miniopenai/o3-mini:lowopenai/o3-mini:mediumOpenAI: o3 Mini (batch)