DocVQA
DocVQA (Document Visual Question Answering) tests AI models on their ability to understand and answer questions about document images including invoices, letters, reports, forms, and tables. Models must perform optical character recognition, layout understanding, and reasoning over document structure to extract specific information. It is a critical benchmark for enterprise document processing and automation applications.
Metrics
ANLS score (Average Normalized Levenshtein Similarity, 0-1)
Created By
Minesh Mathew et al. (CVC Barcelona)
Paper
View paper →Website
Visit website →Top Model Scores
| Rank | Model | Score | Date |
|---|---|---|---|
| 1 | GPT-5.2 | 0.952 | 2026-03 |
| 2 | Gemini 3 Ultra | 0.948 | 2026-01 |
| 3 | Claude Opus 4.6 | 0.941 | 2026-02 |
| 4 | Grok 4 | 0.923 | 2026-02 |
| 5 | Llama 4 405B | 0.908 | 2026-01 |
Related Vision Benchmarks
VQAv2
Visual Question Answering v2 is a large-scale benchmark for visual question answering containing over 1 million questions about images from COCO. It tests the ability to answer open-ended questions that require understanding image content.
Top: Gemini 3 Ultra — 88.9%
ChartQA
ChartQA tests the ability of models to answer questions about charts and visualizations, requiring both visual understanding of chart elements and reasoning about the underlying data.
Top: GPT-5.2 — 90.1%
RealWorldQA
RealWorldQA evaluates vision-language models on practical, real-world visual understanding tasks including spatial reasoning about real photographs, reading text in images, understanding scenes, and answering practical questions.
Top: Gemini 3 Ultra — 79.6%
WildVision-Bench
WildVision-Bench evaluates multimodal AI models on challenging real-world vision-language tasks collected from actual user interactions in the wild. Unlike curated academic datasets, WildVision captures the diversity and difficulty of how people naturally interact with vision-language models, including complex scene understanding, multi-image reasoning, and nuanced visual questions that require world knowledge and common sense.
Top: GPT-5.2 — 78.4%