Models Published:
EmbeddingGemma 2: a 740M multimodal embedding model for local search and RAG
Google DeepMind released EmbeddingGemma 2 on October 6, an Apache 2.0 embedding model that maps text, code, images, audio and video into one 768-dimensional space. Text-only use needs just the 270M-parameter text part, while the vision and audio encoders load only when needed, for 740M parameters in total. Vectors can be shortened to 512, 256 or 128 dimensions to save storage, and the context window is 8K tokens. Google lists Ollama, LM Studio, llama.cpp, MLX and vLLM among the supported runtimes.
Why it matters locally
It is small enough to run beside your chat model on almost any machine, so a fully local RAG setup can search photos, recordings and documents with one model instead of a cloud embedding API.
Source
Read the official source: Google blog: EmbeddingGemma 2 ↗Summaries are written by OnPrem World from the official source. We link to the original and never republish it.
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