EmbeddingGemma 2: an open, lightweight multimodal embedding model

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Oct 06, 2026

EmbeddingGemma 2 is the most capable model for on-device multimodal embeddings, natively mapping combinations of text, images, audio, and video into a unified embedding space.


Sahil Dua

Research Engineer, Google DeepMind

Henrique Schechter Vera

Research Engineer, Google DeepMind


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This content is generated by Google AI. Generative AI is experimental

We introduced EmbeddingGemma last year to provide a lightweight option for high-quality text embeddings, to help your apps organize, search, and connect information directly on consumer hardware. The developer community’s response blew past our expectations. With more than 20 million downloads, builders have used it to power smarter on-device search tools and privacy-first retrieval augmented generation (RAG) pipelines.

Today, we’re launching EmbeddingGemma 2,expanding beyond text to unify code, images, video, and audio in a shared embedding space. Built on the Gemma 4 architecture and released under a commercially permissive Apache 2.0...

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