multimodal benchmark
DocVQAtest Leaderboard
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 17, 2026
Models11
Model coverage11
MetricScore
EvidenceB
DocVQAtest Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score97.1% | Percentile100.0% | Participants11 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score96.9% | Percentile90.0% | Participants11 | EvidenceC | Evaluated |
| Rank03 | ModelAC | Score96.5% | Percentile80.0% | Participants11 | EvidenceC | Evaluated |
| Rank04 | ModelAC | Score96.5% | Percentile70.0% | Participants11 | EvidenceC | Evaluated |
| Rank05 | ModelAC | Score96.1% | Percentile60.0% | Participants11 | EvidenceC | Evaluated |
| Rank06 | ModelAC | Score96.1% | Percentile50.0% | Participants11 | EvidenceC | Evaluated |
| Rank07 | ModelAC | Score95.3% | Percentile40.0% | Participants11 | EvidenceC | Evaluated |
| Rank08 | ModelAC | Score95.3% | Percentile30.0% | Participants11 | EvidenceC | Evaluated |
| Rank09 | ModelAC | Score95.0% | Percentile20.0% | Participants11 | EvidenceC | Evaluated |
| Rank10 | ModelAC | Score95.0% | Percentile10.0% | Participants11 | EvidenceC | Evaluated |
| Rank11 | ModelAC | Score94.2% | Percentile0.0% | Participants11 | EvidenceC | Evaluated |
DocVQAtest Highlights
The leading models and scores on this benchmark.
DocVQAtest Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for DocVQAtest
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis docvqatest AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01ACQwen3 VL 235B A22B InstructAlibaba Cloud / Qwen Team
- Score
- 97.1%
Strengths
- Ranks #1 of 11 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures DocVQAtest, not total model capability
- 02ACQwen3 VL 32B InstructAlibaba Cloud / Qwen Team
- Score
- 96.9%
Strengths
- Ranks #2 of 11 compared models
- 90th percentile on this benchmark
- C evidence result
Considerations
- This result measures DocVQAtest, not total model capability
- 03ACQwen2-VL-72B-InstructAlibaba Cloud / Qwen Team
- Score
- 96.5%
Strengths
- Ranks #3 of 11 compared models
- 80th percentile on this benchmark
- C evidence result
Considerations
- This result measures DocVQAtest, not total model capability
- 04ACQwen3 VL 235B A22B ThinkingAlibaba Cloud / Qwen Team
- Score
- 96.5%
Strengths
- Ranks #4 of 11 compared models
- 70th percentile on this benchmark
- C evidence result
Considerations
- This result measures DocVQAtest, not total model capability
- 05ACQwen3 VL 32B ThinkingAlibaba Cloud / Qwen Team
- Score
- 96.1%
Strengths
- Ranks #5 of 11 compared models
- 60th percentile on this benchmark
- C evidence result
Considerations
- This result measures DocVQAtest, not total model capability
Selection summary
Best AI Models for DocVQAtest
Qwen3 VL 235B A22B Instruct currently leads DocVQAtest with 97.1%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
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.