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// Search & vector stores

EmbeddingGemma 2

Google DeepMind's 0.74B multimodal embedding model: text (incl. code), images, video and audio in one 768-d space; 100+ languages, 8K context, Matryoshka truncation to 128/256/512; text-only loads just 270M, built for on-device RAG and semantic search

Open source Maintained For agents

Official site ↗ Compare

IN ONE PARAGRAPH

EmbeddingGemma 2 is google DeepMind's 0.74B multimodal embedding model: text (incl. code), images, video and audio in one 768-d space; 100+ languages, 8K context, Matryoshka truncation to 128/256/512; text-only loads just 270M, built for on-device RAG and semantic search.

Good for: Developers who want their agent (Claude Code, Codex, Cursor…) to search & vector stores.

Not for: people who don’t want to install and run tools themselves.

01How to start

  1. 1Read the official README / docs for requirements and permissions.
  2. 2Install it as the official guide describes.
  3. 3Tell your agent the command exists (e.g. in AGENTS.md / CLAUDE.md) so it knows when to call it.

02Alternatives & comparison

Compare side by side →
elasticsearch Free and Open Source, Distributed, RESTful Search Engine ★ 78k redis For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine. ★ 77k milvus Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search ★ 46k qdrant Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/ ★ 35k chroma Search infrastructure for AI ★ 30k

03Related

Versions, why it is listed, for AI to read

For AI agents

Data updated: AI software & hot ranks · Software profiles & needs(UTC+8)