multimodal benchmark
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
Higher score ranks better on this benchmark.
| 01 | AC | 61.1% | 100.0% | 5 | C | |
| 02 | BY | 53.0% | 75.0% | 5 | C | |
| 03 | MA | 51.0% | 50.0% | 5 | C | |
| 04 | BY | 48.6% | 25.0% | 5 | C | |
| 05 | MA | 46.3% | 0.0% | 5 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
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.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about WorldVQA.
Qwen3.7-Plus is currently ranked first with 61.1%.
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.
Yes. Higher values rank better for this benchmark.
5 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.