multimodal benchmark
MME
A comprehensive evaluation benchmark for Multimodal Large Language Models measuring both perception and cognition abilities across 14 subtasks. Features manually designed instruction-answer pairs to avoid data leakage and provides systematic quantitative assessment of MLLM capabilities.
Updated Aug 11, 2026
Models3
Model coverage3
MetricScore
EvidenceB
MME Ranking
Higher score ranks better on this benchmark.
| 01 | DE | 22.5% | 100.0% | 3 | C | |
| 02 | DE | 21.2% | 50.0% | 3 | C | |
| 03 | DE | 19.1% | 0.0% | 3 | C |
MME Score Distribution
A closer view of the leading scores on this benchmark.
MME Highlights
The leading models and scores on this benchmark.
What is MME?
What MME measures and how its scores work.
A comprehensive evaluation benchmark for Multimodal Large Language Models measuring both perception and cognition abilities across 14 subtasks. Features manually designed instruction-answer pairs to avoid data leakage and provides systematic quantitative assessment of MLLM capabilities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MME
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- mme|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MME.
Which model scores highest on MME?
DeepSeek VL2 is currently ranked first with 22.5%.
What does MME measure?
A comprehensive evaluation benchmark for Multimodal Large Language Models measuring both perception and cognition abilities across 14 subtasks. Features manually designed instruction-answer pairs to avoid data leakage and provides systematic quantitative assessment of MLLM capabilities.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
3 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.