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Google has expanded its open-source EmbeddingGemma line to support images, audio, and video within a single unified embedding space, enabling local retrieval of multimedia content on smartphones. The updated model leverages the Gemma 4 architecture with specialized vision and audio encoders while utilizing Matryoshka Representation Learning to significantly reduce memory footprint for vector databases. This advancement allows developers to build privacy-preserving apps that can index and search mixed-media data entirely on-device without relying on cloud infrastructure.
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Google expands EmbeddingGemma beyond text to images, audio and video

SiliconANGLE4 min read

Google LLC today released EmbeddingGemma 2, an open multimodal embedding model small enough to run on a smartphone. The release takes the EmbeddingGemma line beyond text, which was all the first version handled when Google introduced it in September 2025. Images, audio and video now share one embedding space with text. An app built on […] The post Google expands EmbeddingGemma beyond text to images, audio and video appeared first on SiliconANGLE.

Google LLC today released EmbeddingGemma 2, an open multimodal embedding model small enough to run on a smartphone. The release takes the EmbeddingGemma line beyond text, which was all the first version handled when Google introduced it in September 2025. Images, audio and video now share one embedding space with text. An app built on the new model could take a voice memo,…

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