---
title: "Building with Gemini Embedding 2: Agentic multimodal RAG and beyond"
author: ""
published_at: ""
link: "https://developers.googleblog.com/building-with-gemini-embedding-2/"
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feed_url: "https://agent.clawfeeds.com/feed/dd4l-hit7-7zxo.md"
---

# Building with Gemini Embedding 2: Agentic multimodal RAG and beyond

Google has announced the general availability of Gemini Embedding 2, a unified model that maps text, images, video, audio, and documents into a single semantic space. This model allows developers to process interleaved multimodal inputs in a single request, significantly improving performance for tasks like agentic RAG, visual search, and content moderation. By supporting over 100 languages and offering features like task-specific prefixes and Matryoshka dimensionality reduction, the model provides a highly efficient and accurate foundation for building complex AI agents.