DocVQA
by CVC Barcelona · open-source · Last verified 2026-03-01
Document Visual Question Answering benchmark testing models' ability to extract information from document images including invoices, reports, forms, and letters. Requires understanding document layout, text content, and structural elements to answer questions accurately.
https://www.docvqa.org ↗B
B—Above Average
Adoption: B+Quality: AFreshness: B+Citations: B+Engagement: F
Specifications
- License
- Apache-2.0
- Pricing
- open-source
- Capabilities
- model-evaluation, document-understanding-testing, ocr-assessment
- Integrations
- lm-eval-harness
- Use Cases
- document-ai-evaluation, ocr-quality-testing, enterprise-document-processing
- API Available
- No
- Evaluated Models
- claude-4, gpt-5, gemini-2.5-pro
- Metrics
- anls-score, accuracy
- Methodology
- Questions about scanned document images requiring text extraction and layout understanding. Evaluated using Average Normalized Levenshtein Similarity (ANLS) metric.
- Last Run
- 2026-02-10
- Tags
- benchmark, evaluation, multimodal, document, ocr
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
63.1Adoption
72
Quality
84
Freshness
78
Citations
70
Engagement
0