VQAv2
VQAv2 is a balanced Visual Question Answering dataset that addresses language bias by providing complementary images for each question, forcing models to rely on visual understanding rather than language priors. It contains approximately twice the number of image-question pairs compared to the original VQA dataset.
Pixtral Large from Mistral AI currently leads the VQAv2 leaderboard with a score of 0.809 across 3 evaluated AI models.
Pixtral Large leads with 80.9%, followed by Pixtral-12B at 78.6% and 
Llama 3.2 90B Instruct at 78.1%.
Progress Over Time
Interactive timeline showing model performance evolution on VQAv2
VQAv2 Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Mistral AI | 124B | — | — | ||
| 2 | Mistral AI | 12B | — | — | ||
| 3 | 90B | — | — |
FAQ
Common questions about VQAv2.
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