GPT-5 nano
GPT-5 nano is a high throughput model that excels at simple instruction or classification tasks.
text + image + file → text · made by OpenAI
$0.05→$0.4per Mtok in / out
OpenAI · 13 sellers
Sold by 25 ways
| Seller | Lane | Rate |
|---|---|---|
| Microsoft Azure AI cloud | batch | $0.028per Mtok in$0.22per Mtok out$0.0025per Mtok cachedraw.githubusercontent.com · read 2026-10-31 |
| Databricks cloud | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cached$0.05per Mtok cache writemodels.dev · read 2026-10-31 |
| DigitalOcean cloud | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedmodels.dev · read 2026-10-31 |
| Microsoft Azure AI cloud | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedmodels.dev · read 2026-10-31 |
| OpenAI api | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cacheddevelopers.openai.com · read 2026-08-24 |
| Oracle Cloud Infrastructure cloud | standard | $0.05per Mtok in$0.4per Mtok outraw.githubusercontent.com · read 2026-10-31 |
| Snowflake Cortex cloud | standard | $0.15per Mtok in$0.6per Mtok outraw.githubusercontent.com · read 2026-10-31 |
| Requesty 2 ways | $0.022per Mtok in$0.18per Mtok out$0.0022per Mtok cached | |
| Requesty aggregatornot on the seller's list today | openai flex | $0.022per Mtok in$0.18per Mtok out$0.0022per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregator | openai | $0.025per Mtok in$0.2per Mtok out$0.0025per Mtok cachedrouter.requesty.ai · read 2026-10-09 |
| Requesty aggregatornot on the seller's list today | azure eastus2 | $0.045per Mtok in$0.36per Mtok out$0.0045per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | azure francecentral | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregatornot on the seller's list today | azure swedencentral | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedrouter.requesty.ai · read 2026-08-25 |
| Requesty aggregator | azure | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedrouter.requesty.ai · read 2026-10-09 |
| Requesty aggregatornot on the seller's list today | openai-responses | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedrouter.requesty.ai · read 2026-08-28 |
| Nous Research 2 ways | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cached | |
| Nous Research aggregator | batch | $0.025per Mtok in$0.2per Mtok out$0.0025per Mtok cachedinference-api.nousresearch.com · read 2026-09-12 |
| Nous Research aggregator | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedinference-api.nousresearch.com · read 2026-09-12 |
| OpenRouter 5 ways | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cached | |
| OpenRouter aggregator | batch | $0.025per Mtok in$0.2per Mtok out$0.0025per Mtok cachedopenrouter.ai · read 2026-08-24 |
| OpenRouter aggregator | openai/flex | $0.025per Mtok in$0.2per Mtok out$0.0025per Mtok cachedopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedopenrouter.ai · read 2026-08-24 |
| OpenRouter aggregator | azure | $0.05per Mtok in$0.4per Mtok out$0.01per Mtok cachedopenrouter.ai · read 2026-08-25 |
| OpenRouter aggregator | azure/swedencentral | $0.055per Mtok in$0.44per Mtok out$0.011per Mtok cachedopenrouter.ai · read 2026-08-25 |
| ElectronHub aggregator | standard | $0.05per Mtok in$0.4per Mtok outapi.electronhub.ai · read 2026-10-31 |
| Inference.net aggregator | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedapi.inference.net · read 2026-10-31 |
| RedPill aggregator | standard | $0.05per Mtok in$0.4per Mtok outapi.redpill.ai · read 2026-09-20 |
| Vercel AI Gateway aggregator | standard | $0.05per Mtok in$0.4per Mtok out$0.005per Mtok cachedai-gateway.vercel.sh · read 2026-08-25 |
Measured 34 standings
| Place | Board | Metric | Score |
|---|---|---|---|
| 14thof 108 | Math level 5 — Epoch AI | mean_score (medium) | 95.242 |
| 26thof 38 | Vpct — Epoch AI | Correct (high) | 0.372 |
| 41stof 42 | Fictionlivebench — Epoch AI | 120k token score (medium) | 0.219 |
| 56thof 72 | Frontiermath tier 4 — Epoch AI | mean_score (medium) | 2.083 |
| 60thof 101 | FrontierMath (Tiers 1-3) | mean_score (high) | 8.276 |
| 66thof 111 | Vectara Hallucination Leaderboard | Hallucination Rate | 10.5 |
| 67thof 84 | Proofbench — Epoch AI | Accuracy (high) | 12 |
| 73rdof 78 | Frontiermath tier 4 v2 — Epoch AI | mean_score (high) | 2.439 |
| 82ndof 92 | Forecastbench — Epoch AI | Overall score | 59 |
| 87thof 154 | Chess puzzles — Epoch AI | mean_score (high) | 22 |
| 89thof 132 | Ale bench — Epoch AI | Performance (high) | 718.67 |
| 90thof 93 | Simpleqa verified — Epoch AI | mean_score (high) | 11.7 |
| 93rdof 122 | Frontiermath tiers 1 3 v2 — Epoch AI | mean_score (high) | 20 |
| 116thof 142 | Mystery game puzzles — Epoch AI | mean_score (medium) | 9 |
| 118thof 165 | LMArena · Vision | Score (Elo) (high) | 1146 |
| 119thof 306 | OTIS Mock AIME 2024-2025 | mean_score (high) | 81.111 |
| 125thof 173 | Weirdml — Epoch AI | Accuracy (high) | 38.06 |
| 132ndof 154 | Design Arena · dataviz (models) | Elo | 1056 |
| 132ndof 157 | Design Arena · uicomponent (models) | Elo | 1061 |
| 135thof 163 | Design Arena · codecategories (models) | Elo | 1082 |
| 136thof 150 | Design Arena · 3d (models) | Elo | 963 |
| 136thof 169 | Design Arena · website (models) | Elo | 1101 |
| 138thof 162 | Design Arena · gamedev (models) | Elo | 1043 |
| 169thof 202 | Terminalbench — Epoch AI | Accuracy mean | 0.218 |
| 181stof 235 | Dtbench — Epoch AI | Accuracy (high) | 62.67 |
| 189thof 326 | GPQA Diamond | mean_score (high) | 69.444 |
| 189thof 197 | Lmca — Epoch AI | Score (high) | 7.93 |
| 220thof 290 | Arc agi 2 — Epoch AI | Score (high) | 2.61 |
| 222ndof 298 | ARC-AGI-2 (Semi-Private) | Score (%) (high) | 2.61 |
| 234thof 414 | LMArena · Text | Score (Elo) (high) | 1337 |
| 235thof 273 | ARC-AGI-1 (Public Eval) | Score (%) (high) | 29.67 |
| 238thof 282 | ARC-AGI-2 (Public Eval) | Score (%) (high) | 0.3 |
| 255thof 298 | ARC-AGI-1 (Semi-Private) | Score (%) (medium) | 20.71 |
| 266thof 309 | Arc agi — Epoch AI | Score (medium) | 20.71 |
About
GPT-5 nano — a text model from OpenAI, sold by 13 companies from $0.05 in and $0.4 out per million tokens, placed 14th of 108 on Math level 5 — Epoch AI.
It takes text, images and files and returns text, with a context window of 400,000 tokens. It was published in 2025, 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. Thirteen companies sell it. The cheapest is $0.05 in and $0.4 out per million tokens at Databricks. Beside the standard rate there are batch, separately routed, regional and flex lanes. It has been measured on 34 boards, and stands best at 14th of 108 on Math level 5 — Epoch AI.
Every current figure
- Maker
- OpenAI
- Register
- model
- Takes
- text + image + file
- Returns
- text
- Context
- 400,000 tokens
- Published
- 2025
- Knowledge to
- May 2024
- Licence
- not read
- Sellers
- 13
- Price
- $0.05 in and $0.4 out per million tokens — Databricks
- Boards
- 34
- Best place
- 14th of 108 — Math level 5 — Epoch AI
Known as 13 names
GPT-5-nano-2025-08-07 (FC)GPT 5 Nanoopenai/gpt-5-nanoopenai/gpt-5-nano:batchgpt-5-nanoazure/gpt-5-nanoazure/gpt-5-nano@eastus2azure/gpt-5-nano@francecentralazure/gpt-5-nano@swedencentralopenai-responses/gpt-5-nanoopenai/gpt-5-nano:flexopenai/gpt-5-nano-batchOpenAI: GPT-5 Nano (batch)