multimodal benchmark
MMBench-V1.1
Version 1.1 of MMBench, an improved bilingual benchmark for assessing multi-modal capabilities of vision-language models through multiple-choice questions in both English and Chinese, providing systematic evaluation across diverse vision-language tasks.
Updated Aug 11, 2026
Models18
Model coverage18
MetricScore
EvidenceB
MMBench-V1.1 Ranking
Higher score ranks better on this benchmark.
MMBench-V1.1 Score Distribution
A closer view of the leading scores on this benchmark.
MMBench-V1.1 Highlights
The leading models and scores on this benchmark.
What is MMBench-V1.1?
What MMBench-V1.1 measures and how its scores work.
Version 1.1 of MMBench, an improved bilingual benchmark for assessing multi-modal capabilities of vision-language models through multiple-choice questions in both English and Chinese, providing systematic evaluation across diverse vision-language tasks.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MMBench-V1.1
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- mmbench-v1.1|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MMBench-V1.1.
Which model scores highest on MMBench-V1.1?
Qwen3.5-122B-A10B is currently ranked first with 92.8%.
What does MMBench-V1.1 measure?
Version 1.1 of MMBench, an improved bilingual benchmark for assessing multi-modal capabilities of vision-language models through multiple-choice questions in both English and Chinese, providing systematic evaluation across diverse vision-language tasks.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
18 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.