o4-mini
A customer fine-tuned deployment of OpenAI's o4-mini.
text + image + file → text · made by OpenAI
$1.1→$4.4per Mtok in / out
OpenAI · 6 sellers
Sold by 20 ways
| Seller | Lane | Rate |
|---|---|---|
| Microsoft Azure AI cloud | batch | $0.6per Mtok in$2.42per Mtok outraw.githubusercontent.com · read 2026-10-31 |
| Microsoft Azure AI cloud | standard | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedmodels.dev · read 2026-10-31 |
| Microsoft Azure AI 0 ways | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cached | |
| Microsoft Azure AI cloudnot on the seller's list today | fine-tuned | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedprices.azure.com · read 2026-08-25 |
| OpenAI api | standard | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cacheddevelopers.openai.com · read 2026-08-24 |
| Requesty 2 ways | $0.49per Mtok in$1.98per Mtok out$0.12per Mtok cached | |
| Requesty aggregatornot on the seller's list today | openai flex | $0.49per Mtok in$1.98per Mtok out$0.12per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | azure westus3 | $0.99per Mtok in$3.96per Mtok out$0.25per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | openai low | $0.99per Mtok in$3.96per Mtok out$0.25per 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$0.25per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | azure francecentral | $1.09per Mtok in$4.36per Mtok out$0.27per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | azure swedencentral | $1.09per Mtok in$4.36per Mtok out$0.27per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregator | azure | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedrouter.requesty.ai · read 2026-10-10 |
| Requesty aggregator | openai | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedrouter.requesty.ai · read 2026-10-09 |
| Requesty aggregatornot on the seller's list today | openai-responses | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedrouter.requesty.ai · read 2026-08-28 |
| Nous Research 2 ways | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cached | |
| Nous Research aggregator | batch | $0.55per Mtok in$2.2per Mtok out$0.14per Mtok cachedinference-api.nousresearch.com · read 2026-09-12 |
| Nous Research aggregator | standard | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedinference-api.nousresearch.com · read 2026-09-12 |
| OpenRouter 2 ways | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cached | |
| OpenRouter aggregator | batch | $0.55per Mtok in$2.2per Mtok out$0.14per Mtok cachedopenrouter.ai · read 2026-08-24 |
| OpenRouter aggregator | standard | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedopenrouter.ai · read 2026-08-24 |
| 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 |
| RedPill 0 ways | $1.1per Mtok in$4.4per Mtok out | |
| RedPill aggregatornot on the seller's list today | standard | $1.1per Mtok in$4.4per Mtok outapi.redpill.ai · read 2026-09-20 |
| Vercel AI Gateway aggregator | standard | $1.1per Mtok in$4.4per Mtok out$0.28per Mtok cachedai-gateway.vercel.sh · read 2026-08-25 |
Measured 43 standings
| Place | Board | Metric | Score |
|---|---|---|---|
| 3rdof 15 | Cad eval — Epoch AI | Overall pass (%) (medium) | 0.62 |
| 4thof 108 | Math level 5 — Epoch AI | mean_score (high) | 97.829 |
| 6thof 18 | Algotune — Epoch AI | Score (high) | 1.72 |
| 8thof 11 | Gdpval — Epoch AI | Win Rate (%) (high) | 0.253 |
| 8thof 38 | Vpct — Epoch AI | Correct (medium) | 0.575 |
| 16thof 46 | Enigma eval — Epoch AI | Accuracy (high) | 9.21 |
| 18thof 72 | Aider polyglot — Epoch AI | Percent correct (high) | 72 |
| 18thof 49 | Metr time horizons — Epoch AI | average_score (medium) | 0.639 |
| 20thof 42 | Fictionlivebench — Epoch AI | 120k token score (medium) | 0.625 |
| 26thof 56 | Humanity's Last Exam (Epoch AI replication) | Accuracy (high) | 18.08 |
| 32ndof 92 | Forecastbench — Epoch AI | Overall score | 64.2 |
| 33rdof 72 | Frontiermath tier 4 — Epoch AI | mean_score (high) | 6.25 |
| 33rdof 49 | Lech mazur writing — Epoch AI | Mean score (medium) | 7.5 |
| 34thof 101 | FrontierMath (Tiers 1-3) | mean_score (high) | 24.828 |
| 38thof 42 | Gso — Epoch AI | Score OPT@1 (high) | 0.036 |
| 66thof 173 | Weirdml — Epoch AI | Accuracy (high) | 52.56 |
| 69thof 78 | Frontiermath tier 4 v2 — Epoch AI | mean_score (high) | 4.878 |
| 69thof 122 | Frontiermath tiers 1 3 v2 — Epoch AI | mean_score (high) | 36.14 |
| 74thof 132 | Ale bench — Epoch AI | Performance (high) | 826.17 |
| 74thof 102 | Simplebench — Epoch AI | Score (AVG@5) (high) | 0.387 |
| 80thof 93 | Simpleqa verified — Epoch AI | mean_score (low) | 19.6 |
| 86thof 154 | Chess puzzles — Epoch AI | mean_score (medium) | 22 |
| 90thof 165 | LMArena · Vision | Score (Elo) | 1201 |
| 101stof 111 | Vectara Hallucination Leaderboard | Hallucination Rate | 18.6 |
| 118thof 306 | OTIS Mock AIME 2024-2025 | mean_score (high) | 81.667 |
| 133rdof 142 | Mystery game puzzles — Epoch AI | mean_score (high) | 5 |
| 137thof 326 | GPQA Diamond | mean_score (high) | 79.609 |
| 141stof 154 | Design Arena · dataviz (models) | Elo | 991 |
| 143rdof 157 | Design Arena · uicomponent (models) | Elo | 978 |
| 144thof 235 | Dtbench — Epoch AI | Accuracy (high) | 77.6 |
| 145thof 162 | Design Arena · gamedev (models) | Elo | 1003 |
| 146thof 150 | Design Arena · 3d (models) | Elo | 851 |
| 149thof 197 | Lmca — Epoch AI | Score (high) | 26.5 |
| 153rdof 163 | Design Arena · codecategories (models) | Elo | 974 |
| 155thof 169 | Design Arena · website (models) | Elo | 985 |
| 158thof 273 | ARC-AGI-1 (Public Eval) | Score (%) (high) | 68.03 |
| 166thof 282 | ARC-AGI-2 (Public Eval) | Score (%) (high) | 7.52 |
| 172ndof 414 | LMArena · Text | Score (Elo) | 1391 |
| 173rdof 298 | ARC-AGI-1 (Semi-Private) | Score (%) (high) | 58.67 |
| 183rdof 260 | Critpt — Epoch AI | Accuracy (high) | 0.6 |
| 184thof 309 | Arc agi — Epoch AI | Score (high) | 58.67 |
| 187thof 298 | ARC-AGI-2 (Semi-Private) | Score (%) (high) | 6.11 |
| 188thof 290 | Arc agi 2 — Epoch AI | Score (high) | 6.11 |
About
o4-mini — a text model from OpenAI, sold by 6 companies from $1.1 in and $4.4 out per million tokens, placed 4th of 108 on Math level 5 — Epoch AI.
It takes text, images and files and returns text, with a context window of 200,000 tokens. It was published in June 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 and agents. Six companies sell it. The cheapest is $1.1 in and $4.4 out per million tokens at Microsoft Azure AI. Beside the standard rate there are batch and separately routed lanes. It has been measured on 43 boards, and stands best at 4th of 108 on Math level 5 — Epoch AI.
Every current figure
- Maker
- OpenAI
- Register
- model
- Takes
- text + image + file
- Returns
- text
- Context
- 200,000 tokens
- Longest answer
- 100,000 tokens
- Published
- June 2024
- Knowledge to
- May 2024
- Licence
- not read
- Sellers
- 6
- Price
- $1.1 in and $4.4 out per million tokens — Microsoft Azure AI
- Boards
- 43
- Best place
- 4th of 108 — Math level 5 — Epoch AI
Known as 18 names
o4-mini (2025-04-16)o4-mini-2025-04-16 (FC)o4-mini (medium)O4-Mini (Low)GUIRepair + o4-mini (2025-04-16)o4-mini 0416o4-mini-ftopenai/o4-miniopenai/o4-mini:batchazure/o4-mini@eastus2azure/o4-mini@francecentralazure/o4-mini@swedencentralazure/o4-mini@westus3openai-responses/o4-miniopenai/o4-mini:flexopenai/o4-mini:lowopenai/o4-mini:mediumOpenAI: o4 Mini (batch)