multimodal benchmark
DocVQAtest
DocVQA is a Visual Question Answering benchmark on document images containing 50,000 questions defined on 12,000+ document images. The benchmark focuses on understanding document structure and content to answer questions about various document types including letters, memos, notes, and reports from the UCSF Industry Documents Library.
Updated Aug 11, 2026
Models11
Model coverage11
MetricScore
EvidenceB
DocVQAtest Ranking
Higher score ranks better on this benchmark.
| 01 | AC | 97.1% | 100.0% | 11 | C | |
| 02 | AC | 96.9% | 90.0% | 11 | C | |
| 03 | AC | 96.5% | 80.0% | 11 | C | |
| 04 | AC | 96.5% | 70.0% | 11 | C | |
| 05 | AC | 96.1% | 60.0% | 11 | C | |
| 06 | AC | 96.1% | 50.0% | 11 | C | |
| 07 | AC | 95.3% | 40.0% | 11 | C | |
| 08 | AC | 95.3% | 30.0% | 11 | C | |
| 09 | AC | 95.0% | 20.0% | 11 | C | |
| 10 | AC | 95.0% | 10.0% | 11 | C | |
| 11 | AC | 94.2% | 0.0% | 11 | C |
DocVQAtest Score Distribution
A closer view of the leading scores on this benchmark.
DocVQAtest Highlights
The leading models and scores on this benchmark.
What is DocVQAtest?
What DocVQAtest measures and how its scores work.
DocVQA is a Visual Question Answering benchmark on document images containing 50,000 questions defined on 12,000+ document images. The benchmark focuses on understanding document structure and content to answer questions about various document types including letters, memos, notes, and reports from the UCSF Industry Documents Library.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- DocVQAtest
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- docvqatest|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about DocVQAtest.
Which model scores highest on DocVQAtest?
Qwen3 VL 235B A22B Instruct is currently ranked first with 97.1%.
What does DocVQAtest measure?
DocVQA is a Visual Question Answering benchmark on document images containing 50,000 questions defined on 12,000+ document images. The benchmark focuses on understanding document structure and content to answer questions about various document types including letters, memos, notes, and reports from the UCSF Industry Documents Library.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
11 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.