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multimodal benchmark

PerceptionTest Leaderboard

A novel multimodal video benchmark designed to evaluate perception and reasoning skills of pre-trained models across video, audio, and text modalities. Contains 11.6k real-world videos (average 23 seconds) filmed by participants worldwide, densely annotated with six types of labels. Focuses on skills (Memory, Abstraction, Physics, Semantics) and reasoning types (descriptive, explanatory, predictive, counterfactual). Shows significant performance gap between human baseline (91.4%) and state-of-the-art video QA models (46.2%).

Updated Aug 17, 2026

Models2
Model coverage2
MetricScore
EvidenceB

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PerceptionTest Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen2.5 VL 72B InstructAlibaba Cloud / Qwen TeamScore73.2%Percentile100.0%Participants2EvidenceCEvaluatedAug 17, 2026
Rank02ModelACQwen2.5 VL 7B InstructAlibaba Cloud / Qwen TeamScore70.5%Percentile0.0%Participants2EvidenceCEvaluatedAug 17, 2026

PerceptionTest Highlights

The leading models and scores on this benchmark.

Rank #1Qwen2.5 VL 72B Instruct73.2%Rank #2Qwen2.5 VL 7B Instruct70.5%

PerceptionTest Score Distribution

A closer view of the leading scores on this benchmark.

PerceptionTest

The Top AI Models for PerceptionTest

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

Ranking basisThis perceptiontest 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
    AC
    Qwen2.5 VL 72B InstructAlibaba Cloud / Qwen Team
    Score
    73.2%

    Strengths

    • Ranks #1 of 2 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures PerceptionTest, not total model capability
  2. 02
    AC
    Qwen2.5 VL 7B InstructAlibaba Cloud / Qwen Team
    Score
    70.5%
    Price
    $0.35 input / $1.1 output per 1M tokens

    Strengths

    • Ranks #2 of 2 compared models
    • 0th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures PerceptionTest, not total model capability

Selection summary

Best AI Models for PerceptionTest

Qwen2.5 VL 72B Instruct currently leads PerceptionTest with 73.2%. 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 #1Qwen2.5 VL 72B Instruct73.2%Benchmark rank #2Qwen2.5 VL 7B Instruct70.5% · $0.35 input / $1.1 output per 1M tokens

What is PerceptionTest?

What PerceptionTest measures and how its scores work.

A novel multimodal video benchmark designed to evaluate perception and reasoning skills of pre-trained models across video, audio, and text modalities. Contains 11.6k real-world videos (average 23 seconds) filmed by participants worldwide, densely annotated with six types of labels. Focuses on skills (Memory, Abstraction, Physics, Semantics) and reasoning types (descriptive, explanatory, predictive, counterfactual). Shows significant performance gap between human baseline (91.4%) and state-of-the-art video QA models (46.2%).

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
PerceptionTest
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
No
Evaluation key
perceptiontest|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about PerceptionTest.

Which model scores highest on PerceptionTest?

Qwen2.5 VL 72B Instruct is currently ranked first with 73.2%.

What does PerceptionTest measure?

A novel multimodal video benchmark designed to evaluate perception and reasoning skills of pre-trained models across video, audio, and text modalities. Contains 11.6k real-world videos (average 23 seconds) filmed by participants worldwide, densely annotated with six types of labels. Focuses on skills (Memory, Abstraction, Physics, Semantics) and reasoning types (descriptive, explanatory, predictive, counterfactual). Shows significant performance gap between human baseline (91.4%) and state-of-the-art video QA models (46.2%).

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.