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multimodal benchmark

DocVQAtest Leaderboard

DocVQAtest is a Visual Question Answering benchmark based on 12,000+ document images and 50,000 questions.

Updated Sep 5, 2026

Models11
Model coverage11
MetricScore
EvidenceB

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DocVQAtest Ranking

Higher score ranks better on this benchmark.

11 rows
Columns

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Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen3 VL 235B A22B InstructAlibaba Cloud / Qwen TeamScore97.10%Percentile100.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank02ModelACQwen3 VL 32B InstructAlibaba Cloud / Qwen TeamScore96.90%Percentile90.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank03ModelACQwen2-VL-72B-InstructAlibaba Cloud / Qwen TeamScore96.50%Percentile80.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank04ModelACQwen3 VL 235B A22B ThinkingAlibaba Cloud / Qwen TeamScore96.50%Percentile70.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank05ModelACQwen3 VL 8B InstructAlibaba Cloud / Qwen TeamScore96.10%Percentile60.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank06ModelACQwen3 VL 32B ThinkingAlibaba Cloud / Qwen TeamScore96.10%Percentile50.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank07ModelACQwen3 VL 4B InstructAlibaba Cloud / Qwen TeamScore95.30%Percentile40.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank08ModelACQwen3 VL 8B ThinkingAlibaba Cloud / Qwen TeamScore95.30%Percentile30.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank09ModelACQwen3 VL 30B A3B InstructAlibaba Cloud / Qwen TeamScore95.00%Percentile20.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank10ModelACQwen3 VL 30B A3B ThinkingAlibaba Cloud / Qwen TeamScore95.00%Percentile10.00%Participants11EvidenceCEvaluatedSep 8, 2026
Rank11ModelACQwen3 VL 4B ThinkingAlibaba Cloud / Qwen TeamScore94.20%Percentile0.00%Participants11EvidenceCEvaluatedSep 8, 2026

DocVQAtest Highlights

The leading models and scores on this benchmark.

DocVQAtest Score Distribution

A closer view of the leading scores on this benchmark.

DocVQAtest

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.

What is DocVQAtest?

What DocVQAtest measures and how its scores work.

DocVQAtest is a multimodal benchmark for answering questions about document images, including letters, memos, notes, and reports from the UCSF Industry Documents Library.

It measures performance in understanding document structure and content to answer questions, reported as Score in ratio units.

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
No
Evaluation key
overall

LLM Stats. 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 97.10%.

What are the top three models on DocVQAtest?

The current leaders are Qwen3 VL 235B A22B Instruct (97.10%), Qwen3 VL 32B Instruct (96.90%), and Qwen2-VL-72B-Instruct (96.50%).

Which DocVQAtest model has the lowest official input price?

No matched official input price is currently available.

Which models are fastest among DocVQAtest results?

The fastest matched records are Qwen3 VL 4B Thinking (8.77 tok/s via DeepInfra).

Does the highest score result prove overall model quality?

No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.

What does DocVQAtest measure?

It measures performance in understanding document structure and content to answer questions, reported as Score in ratio units.

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?

No. This benchmark is shown for reference but does not contribute to the overall score.

Rank #1Qwen3 VL 235B A22B Instruct97.10%
Rank #2Qwen3 VL 32B Instruct96.90%
Rank #3Qwen2-VL-72B-Instruct96.50%
Rank #4Qwen3 VL 235B A22B Thinking96.50%

Ranking basisThis docvqatest AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    AC
    Qwen3 VL 235B A22B InstructAlibaba Cloud / Qwen Team
    Score
    97.10%

    Strengths

    • Ranks #1 of 11 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures DocVQAtest, not total model capability
  2. 02
    AC
    Qwen3 VL 32B InstructAlibaba Cloud / Qwen Team
    Score
    96.90%

    Strengths

    • Ranks #2 of 11 compared models
    • 90th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures DocVQAtest, not total model capability
  3. 03
    AC
    Alibaba Cloud / Qwen Team
    Score
    96.50%

    Strengths

    • Ranks #3 of 11 compared models
    • 80th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures DocVQAtest, not total model capability
  4. 04
    AC
    Alibaba Cloud / Qwen Team
    Score
    96.50%

    Strengths

    • Ranks #4 of 11 compared models
    • 70th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures DocVQAtest, not total model capability
  5. 05
    AC
    Alibaba Cloud / Qwen Team
    Score
    96.10%

    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 97.10%. 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.

Qwen2-VL-72B-Instruct
Qwen3 VL 235B A22B Thinking
Qwen3 VL 8B Instruct
Benchmark rank #1Qwen3 VL 235B A22B Instruct97.10%
Benchmark rank #2Qwen3 VL 32B Instruct96.90%
Benchmark rank #3Qwen2-VL-72B-Instruct96.50%