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multimodal benchmark

WorldVQA

WorldVQA is a benchmark designed to evaluate atomic vision-centric world knowledge. It assesses models' ability to understand and reason about visual elements representing real-world knowledge.

Updated Aug 11, 2026

Models5
Model coverage5
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

WorldVQA Ranking

Higher score ranks better on this benchmark.

5 rows
Columns

Show columns

01ACQwen3.7-PlusAlibaba Cloud / Qwen Team61.1%100.0%5CAug 11, 2026
02BYSeed 2.1 ProByteDance53.0%75.0%5CAug 11, 2026
03MAKimi K3Moonshot AI51.0%50.0%5CAug 11, 2026
04BYSeed 2.1 TurboByteDance48.6%25.0%5CAug 11, 2026
05MAKimi K2.5Moonshot AI46.3%0.0%5CAug 11, 2026

WorldVQA Score Distribution

A closer view of the leading scores on this benchmark.

WorldVQA

WorldVQA Highlights

The leading models and scores on this benchmark.

Rank #1Qwen3.7-Plus61.1%Rank #2Seed 2.1 Pro53.0%Rank #3Kimi K351.0%Rank #4Seed 2.1 Turbo48.6%

What is WorldVQA?

What WorldVQA measures and how its scores work.

WorldVQA is a benchmark designed to evaluate atomic vision-centric world knowledge. It assesses models' ability to understand and reason about visual elements representing real-world knowledge.

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

Family
WorldVQA
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
worldvqa|llm-stats-current

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

FAQ

Common questions about WorldVQA.

Which model scores highest on WorldVQA?

Qwen3.7-Plus is currently ranked first with 61.1%.

What does WorldVQA measure?

WorldVQA is a benchmark designed to evaluate atomic vision-centric world knowledge. It assesses models' ability to understand and reason about visual elements representing real-world knowledge.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

5 model results are currently shown.

Does this benchmark affect the overall score?

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