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#embeddinggemma-2

Google DeepMind's EmbeddingGemma 2 is now available on Ollama

Ollama has added support for Google DeepMind's EmbeddingGemma 2, allowing developers to run the multimodal on-device embedding model locally.

Google DeepMind releases 740M EmbeddingGemma 2 under Apache 2.0 license

EmbeddingGemma 2 features 740 million parameters and is published under an Apache 2.0 license, providing multimodal search and local retrieval-augmented generation capabilities on device.

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.

Google DeepMind introduces EmbeddingGemma 2 for on-device multimodal embeddings

Google DeepMind has introduced EmbeddingGemma 2, its first natively multimodal open model for on-device embeddings that unifies text, code, images, audio, and video in a shared space.