Dataset · Hugging Face

VLM2Vec/MMEB-V3

Name: MMEB-V3
Creator: VLM2Vec
License: mit
Keywords: task_categories:feature-extraction, task_categories:image-to-text, task_categories:text-to-image, license:mit, modality:text, modality:image, modality:video, modality:audio, arxiv:2604.23321, arxiv:2507.04590, arxiv:2410.05160, region:us, multimodal-embedding, retrieval, benchmark

MMEB-V3: Measuring the Performance Gaps of Omni-Modality Embedding Models 🌐 Website | GitHub | 🏆 Leaderboard | 📖 MMEB-V3 Paper | 📖 MMEB-V2 Paper | 📖 MMEB-V1 Paper | 🤗 Models Introduction MMEB-V3 is a comprehensive benchmark for evaluating omni-modality embedding models across text, image, video, audio, visual-document, and agent-centric retrieval scenarios. Building upon MMEB-V1 and MMEB-V2, MMEB-V3 adds 111 new tasks, resulting in 190 evaluation tasks in… See the full description on the dataset page: https://huggingface.co/datasets/VLM2Vec/MMEB-V3.

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Author / organization	VLM2Vec
License (as declared)	mit
Downloads	2.7K (as reported by Hugging Face)
Likes	8
Created	19 March 2026
Last updated at source	6 August 2026

multimodal-embeddingretrievalbenchmarktextimagevideoaudiovisual-documentagent

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