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multimodal benchmark

MME Leaderboard

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 17, 2026

Models4
Model coverage4
MetricScore
EvidenceB

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  • About
  • FAQ

MME Ranking

Higher score ranks better on this benchmark.

4 rows
Columns

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Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelLALFM2.5-VL-3BLiquid AIScore73.1%Percentile100.0%Participants4EvidenceCEvaluatedAug 17, 2026
Rank02ModelDEDeepSeek VL2DeepSeekScore22.5%Percentile66.7%Participants4EvidenceCEvaluatedAug 17, 2026
Rank03ModelDEDeepSeek VL2 SmallDeepSeekScore21.2%Percentile33.3%Participants4EvidenceCEvaluatedAug 17, 2026
Rank04ModelDEDeepSeek VL2 TinyDeepSeekScore19.1%Percentile0.0%Participants4EvidenceCEvaluatedAug 17, 2026

MME Highlights

The leading models and scores on this benchmark.

Rank #1LFM2.5-VL-3B73.1%Rank #2DeepSeek VL222.5%Rank #3DeepSeek VL2 Small21.2%Rank #4DeepSeek VL2 Tiny19.1%

MME Score Distribution

A closer view of the leading scores on this benchmark.

MME

The Top AI Models for MME

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

Ranking basisThis mme 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.

  1. 01
    LA
    LFM2.5-VL-3BLiquid AI
    Score
    73.1%

    Strengths

    • Ranks #1 of 4 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MME, not total model capability
  2. 02
    DE
    DeepSeek VL2DeepSeek
    Score
    22.5%
    Speed
    Up to 22 tok/s via Replicate

    Strengths

    • Ranks #2 of 4 compared models
    • 67th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MME, not total model capability
  3. 03
    DE
    DeepSeek VL2 SmallDeepSeek
    Score
    21.2%
    Speed
    Up to 22 tok/s via Replicate

    Strengths

    • Ranks #3 of 4 compared models
    • 33th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MME, not total model capability
  4. 04
    DE
    DeepSeek VL2 TinyDeepSeek
    Score
    19.1%
    Speed
    Up to 22 tok/s via Replicate

    Strengths

    • Ranks #4 of 4 compared models
    • 0th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures MME, not total model capability

Selection summary

Best AI Models for MME

LFM2.5-VL-3B currently leads MME with 73.1%. 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.

Benchmark rank #1LFM2.5-VL-3B73.1%Benchmark rank #2DeepSeek VL222.5% · Up to 22 tok/s via ReplicateBenchmark rank #3DeepSeek VL2 Small21.2% · Up to 22 tok/s via Replicate

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?

LFM2.5-VL-3B is currently ranked first with 73.1%.

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?

4 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.