MMEB-V2
Not in model cards
Multimodal embedding models are scored on 78 tasks over images, videos and visual documents. V2 adds visual document retrieval, video retrieval, temporal grounding, video classification and video QA.
Released with VLM2Vec-V2, accepted to TMLR 2026. Google's EmbeddingGemma 2 card reports its Image, VisDoc and Video splits.
Made by University of Waterloo (TIGER-Lab) + Salesforce Research Released May 2025 General visual questions All tasks public
- Level
- Everyday Most adults, without training
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Short answer A number, word or short string matched to a key.
No scores here yet
We have no scores for MMEB-V2 yet.
No lab model card reports it yet
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.
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