math benchmark
MMVet
MM-Vet is an evaluation benchmark that examines large multimodal models on complicated multimodal tasks requiring integrated capabilities. It assesses six core vision-language capabilities: recognition, knowledge, spatial awareness, language generation, OCR, and math through questions that require one or more of these capabilities.
Updated Aug 11, 2026
Models2
Model coverage2
MetricScore
EvidenceB
MMVet Ranking
Higher score ranks better on this benchmark.
| 1 | AC | 76.2% | 100.0% | 2 | C | |
| 2 | AC | 67.1% | 0.0% | 2 | C |
MMVet Score Distribution
A closer view of the leading scores on this benchmark.
MMVet Highlights
The leading models and scores on this benchmark.
What is MMVet?
What MMVet measures and how its scores work.
MM-Vet is an evaluation benchmark that examines large multimodal models on complicated multimodal tasks requiring integrated capabilities. It assesses six core vision-language capabilities: recognition, knowledge, spatial awareness, language generation, OCR, and math through questions that require one or more of these capabilities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MMVet
- Modality
- multimodal
- Primary category
- math
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mmvet|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MMVet.
Which model scores highest on MMVet?
Qwen2.5 VL 72B Instruct is currently ranked first with 76.2%.
What does MMVet measure?
MM-Vet is an evaluation benchmark that examines large multimodal models on complicated multimodal tasks requiring integrated capabilities. It assesses six core vision-language capabilities: recognition, knowledge, spatial awareness, language generation, OCR, and math through questions that require one or more of these capabilities.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
2 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.