GPT-5 Nano (batch)
OpenAI · released Aug 7, 2025
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
Specification
- Context window
- 400K
- Max output
- 128K
- Knowledge cutoff
- May 31, 2024
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 1
- Moderated
- Yes
Intelligence
20.1
60th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
—
Median across providers
Latency
—
Time to first token
Cost per task
$0.02
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- AIME 202583.7%
- LiveCodeBench78.9%
- MMLU-Pro78.0%
- GPQA Diamond67.6%
- IFBench67.6%
- AA-LCR (long context)43.7%
- SciCode36.6%
- τ²-bench (Telecom)36.5%
- Terminal-Bench Hard12.1%
- Humanity's Last Exam9.5%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| AIME 2025 | 83.7% |
| LiveCodeBench | 78.9% |
| MMLU-Pro | 78.0% |
| GPQA Diamond | 67.6% |
| IFBench | 67.6% |
| AA-LCR (long context) | 43.7% |
| SciCode | 36.6% |
| τ²-bench (Telecom) | 36.5% |
| Terminal-Bench Hard | 12.1% |
| Humanity's Last Exam | 9.5% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- R1DeepSeek20.4
- North Mini Code (free)Cohere20.2
- GPT-5 Nano (batch)OpenAI20.1
- GPT-5 NanoOpenAI20.1
- GLM 4.5Z.ai19.7
- Kimi K2 0711Moonshot AI19.7
- GPT-4.1OpenAI19.6
- o3 MiniOpenAI19.2
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| R1 | 20.4 |
| North Mini Code (free) | 20.2 |
| GPT-5 Nano (batch) | 20.1 |
| GPT-5 Nano | 20.1 |
| GLM 4.5 | 19.7 |
| Kimi K2 0711 | 19.7 |
| GPT-4.1 | 19.6 |
| o3 Mini | 19.2 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.025
- Output / 1M tokens
- $0.2
- Cached input / 1M
- $0.003
- Blended 3:1
- $0.069
One task, estimated
$0.02
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.
Arena
Head-to-head generation quality
Elo from pairwise judgements, broken out by the kind of thing the model was asked to build.
- Overall Elo
- 1,124
- Win rate
- 48.9%
- Strongest at
- Websites
- Tournaments
- 5,413
Elo by category
Dot position on a 1,000–1,125 scale · Elo has no meaningful zero
- 1,124
- 1,102
- 1,091
- 1,087
- 1,019
Agent categories (full-stack apps, mobile apps) are only scored for models tested in agent harnesses.
View as table
| Category | Elo | Win rate |
|---|---|---|
| Websites | 1124 | 48.9% |
| UI components | 1102 | 51.9% |
| Data visualisation | 1091 | 47.2% |
| Game development | 1087 | 46.6% |
| 3D scenes | 1019 | 36.1% |