Google drops EmbeddingGemma for private, on-device search
Google just launched EmbeddingGemma, a compact 308M parameter open embedding model tailored specifically for on-device AI. It allows developers to run semantic search and local RAG pipelines entirely offline, keeping sensitive data private while sharing a tokenizer with Gemma 3n to save memory. High-accuracy retrieval is finally fitting inside lightweight local hardware.