Banger report from Google.
This is a dev post classified by AGK Intelligence as AI dev tools (a tool drop), kept by the Dev Radar because it carries real work, not commentary.
Banger report from Google. They just released EmbeddingGemma 2, an open 744M multimodal embedding model. It beats specialist models and models 2 to 12 times larger across seven benchmark suites covering text, code, images, video, documents, and audio. Text, images, audio, video, and mixed inputs all go into one vector space. Each modality has its own encoder feeding into a shared backbone, so you can load only what you need. Text-only runs at 271M parameters, vision-language at 439M, and audio-language at 577M. It scores 61.36 on MTEB Multilingual v2 and 68.46 on MTEB English v2. The int4
Posted by DAIR.AI (136.1k followers) 2 days ago · 217 likes · 16.1k views · view the original post on X. Kept by the Dev Radar as AI dev tools. Tools mentioned: arXiv.org.
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