Google has launched Gemini Embedding 2, its first natively multimodal embedding model, now available in Public Preview via the Gemini API and Vertex AI. This model can map text, images, video, audio, and documents (up to 6 pages) into a single embedding space, facilitating multimodal retrieval and classification and enhancing AI applications like Retrieval-Augmented Generation (RAG) and semantic search.
Gemini Embedding 2 gives streaming and media teams a single embedding layer for text, images, video, audio, and short documents instead of separate pipelines for each format. Google positions it for multimodal retrieval, RAG, semantic search, sentiment analysis, and clustering, and says it already supports tools like LangChain, LlamaIndex, Haystack, Weaviate, QDrant, ChromaDB, and Vertex AI Vector Search. The clearest near-term signal to watch is whether developers adopt the preview through Gemini API and Vertex AI, and whether the benchmark claims translate into production search and retrieval gains like Paramount Skydance’s 85.3% Recall@1.
Add StreamingMeme as a preferred source on Google to see more of our streaming news at the top of your Search results.
Add as preferred source