EmbeddingGemma 2: An open, lightweight multimodal embedding model

EmbeddingGemma 2 is an open, lightweight multimodal embedding model that significantly improves code performance by 9.92 points in MTEB Code, from 68.76 to 78.68, while maintaining strong multilingual text performance. This makes it ideal for local codebase indexing, semantic code search, and coding agent retrieval. It also sets a new quality-per-parameter standard for sub-1B models across image, video, documents, and audio, outperforming some specialist models more than twice its size.