multimodal benchmark
MTVQA Leaderboard
MTVQA (Multilingual Text-Centric Visual Question Answering) is the first benchmark featuring high-quality human expert annotations across 9 diverse languages, consisting of 6,778 question-answer pairs across 2,116 images. It addresses visual-textual misalignment problems in multilingual text-centric VQA.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
MTVQA Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score30.9% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
MTVQA Highlights
The leading models and scores on this benchmark.
The Top AI Models for MTVQA
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis mtvqa 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.
- 01ACQwen2-VL-72B-InstructAlibaba Cloud / Qwen Team
- Score
- 30.9%
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures MTVQA, not total model capability
Selection summary
Best AI Models for MTVQA
Qwen2-VL-72B-Instruct currently leads MTVQA with 30.9%. 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 MTVQA?
What MTVQA measures and how its scores work.
MTVQA (Multilingual Text-Centric Visual Question Answering) is the first benchmark featuring high-quality human expert annotations across 9 diverse languages, consisting of 6,778 question-answer pairs across 2,116 images. It addresses visual-textual misalignment problems in multilingual text-centric VQA.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MTVQA
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mtvqa|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MTVQA.
Which model scores highest on MTVQA?
Qwen2-VL-72B-Instruct is currently ranked first with 30.9%.
What does MTVQA measure?
MTVQA (Multilingual Text-Centric Visual Question Answering) is the first benchmark featuring high-quality human expert annotations across 9 diverse languages, consisting of 6,778 question-answer pairs across 2,116 images. It addresses visual-textual misalignment problems in multilingual text-centric VQA.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 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.