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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

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

MME Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

Show columns

1DEDeepSeek VL2DeepSeek22.5%100.0%3CAug 11, 2026
2DEDeepSeek VL2 SmallDeepSeek21.2%50.0%3CAug 11, 2026
3DEDeepSeek VL2 TinyDeepSeek19.1%0.0%3CAug 11, 2026

MME Score Distribution

A closer view of the leading scores on this benchmark.

MME

MME Highlights

The leading models and scores on this benchmark.

Rank #1DeepSeek VL222.5%Rank #2DeepSeek VL2 Small21.2%Rank #3DeepSeek VL2 Tiny19.1%

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.

Rankings

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