OmniDocBench
Can the model extract and reason over information in images or documents?
Vision5 ranked models5 reported values1 reportsHigher is better
Top rankings
One row per model, using its best reported score across effort settings.
| Rank | Model | Best score | Best reported setting |
|---|---|---|---|
| 1 | Kimi K3Moonshot AI | 91.1% | max effortMoonshot AI report1 value · 1 reportJul 17, 2026 · source |
| 2 | Claude Fable 5Anthropic | 89.8% | max effortMoonshot AI report1 value · 1 reportJul 17, 2026 · source |
| 3 | GPT-5.5OpenAI | 89.4% | xhigh effortMoonshot AI report1 value · 1 reportJul 17, 2026 · source |
| 4 | Claude Opus 4.8Anthropic | 87.9% | max effortMoonshot AI report1 value · 1 reportJul 17, 2026 · source |
| 5 | GPT-5.6 SolOpenAI | 85.8% | max effortMoonshot AI report1 value · 1 reportJul 17, 2026 · source |
Effort curve
Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.
No cost-linked effort sweep for this version.
Definition and comparison boundarypublic methodology
Can the model extract and reason over information in images or documents?
Visual perception and multimodal reasoning under the reported protocol. Higher is better. The value is the percentage reported in this lab's table.
Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.
Method / source