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#on-device-ai

EmbeddingGemma 2 operates on 191MB to 567MB of RAM with an 8K context window

Google detailed operational specifications for EmbeddingGemma 2, stating the 740M model uses between ~191MB and 567MB of active RAM, expands its context window to 8K, and processes up to 5.5 minutes of audio, 29 images, or 58 video frames per pass.

Google for Developers details offline execution and modular deployment for EmbeddingGemma 2

EmbeddingGemma 2 runs multimodal workloads entirely offline with zero server calls. The model features a modular design that lets developers drop unused vision or audio components to save memory, offers flexible dimension sizes that reduce local database storage by up to 6x, and pairs with Gemma 4 for efficient on-device RAG pipelines.