GPT-5
OpenAI · released Aug 7, 2025
GPT-5 is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy...
Specification
- Context window
- 400K
- Max output
- 128K
- Knowledge cutoff
- Sep 30, 2024
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 2
- Moderated
- Yes
- Uptime
- 100.0%
Intelligence
35.3
82th percentile
Coding
37.8
Coding Index
Agentic
26.5
Agentic Index
Output speed
79 t/s
Median across providers
Latency
5.3s
Time to first token
Cost per task
$0.86
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 202594.3%
- MMLU-Pro87.1%
- GPQA Diamond85.4%
- τ²-bench (Telecom)84.8%
- LiveCodeBench84.6%
- AA-LCR (long context)76.3%
- IFBench73.1%
- SciCode42.9%
- Terminal-Bench Hard32.6%
- Humanity's Last Exam28.5%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| AIME 2025 | 94.3% |
| MMLU-Pro | 87.1% |
| GPQA Diamond | 85.4% |
| τ²-bench (Telecom) | 84.8% |
| LiveCodeBench | 84.6% |
| AA-LCR (long context) | 76.3% |
| IFBench | 73.1% |
| SciCode | 42.9% |
| Terminal-Bench Hard | 32.6% |
| Humanity's Last Exam | 28.5% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Kimi K2.5Moonshot AI36.0
- Claude Opus 4.5Anthropic35.6
- GPT-5.1-CodexOpenAI35.6
- GPT-5OpenAI35.3
- GLM 5V TurboZ.ai35.3
- Qwen3.5-27BQwen34.6
- M2.5MiniMax34.5
- GLM 4.7Z.ai34.5
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Kimi K2.5 | 36.0 |
| Claude Opus 4.5 | 35.6 |
| GPT-5.1-Codex | 35.6 |
| GPT-5 | 35.3 |
| GLM 5V Turbo | 35.3 |
| Qwen3.5-27B | 34.6 |
| M2.5 | 34.5 |
| GLM 4.7 | 34.5 |
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
- $1.25
- Output / 1M tokens
- $10
- Cached input / 1M
- $0.125
- Blended 3:1
- $3.44
One task, estimated
$0.86
- 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).
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
- 1,262
- Win rate
- 62.9%
- Strongest at
- Data visualisation
- Tournaments
- 232
Elo by category
Dot position on a 1,100–1,275 scale · Elo has no meaningful zero
- 1,262
- 1,235
- 1,227
- 1,217
- 1,207
- 1,111
Agent categories (full-stack apps, mobile apps) are only scored for models tested in agent harnesses.
View as table
| Category | Elo | Win rate |
|---|---|---|
| Data visualisation | 1262 | 62.9% |
| SVG | 1235 | 64.1% |
| Game development | 1227 | 59.5% |
| UI components | 1217 | 58.2% |
| Websites | 1207 | 53.8% |
| 3D scenes | 1111 | 41.4% |