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Tuesday, 6 October 2026
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EmbeddingGemma 2

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  1. 6 Oct 2026
    Google ships EmbeddingGemma 2, an open multimodal embedding model for RAG
    ParameterBeforeNow
    Base architectureNot specifiedGemma 4-based decoder
    ParametersNot specified270M (text/code) up to 740M (full multimodal)
    Embedding spaceNot specifiedShared 768-dimensional space across modalities
    Context windowNot specified8,192 tokens
    Dimension truncationNot specifiedMatryoshka Representation Learning, 768 down to 128 dimensions
    Code retrieval benchmark (MTEB Code)EmbeddingGemma 1 baseline+14% score vs EmbeddingGemma 1
    LicenseNot specifiedApache 2.0

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Google ships EmbeddingGemma 2, an open multimodal embedding model for RAG

Google has launched EmbeddingGemma 2, a Gemma 4-based embedding model released under Apache 2.0 that places text, code, images, video and audio in one shared 768-dimensional vector space. It's modular, so developers load only the encoders they need: 270M parameters for text and code alone, scaling up to 740M for every modality. Google reports a 14% jump over EmbeddingGemma 1 on the MTEB Code benchmark while keeping the earlier model's multilingual text accuracy.

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EmbeddingGemma 2 · TENESYS AI NEWS