Gemini Embedding 2 Preview

• 🎯 Google's latest text embedding model for semantic search
• 🧠 Converts text into dense vector representations
• 🏢 From Google, part of the broader Gemini ecosystem
• 🔍 Powers retrieval, RAG, clustering, and similarity tasks
• 🌍 Preview release of the Gemini Embedding line

Google

Google is an American multinational technology corporation and one of the world's most valuable brands. A subsidiary of parent company Alphabet Inc., Google operates across search, cloud computing, consumer electronics, and artificial intelligence. Its…

Gemini Embedding 2 Preview is Google's current text-embedding model on the platform, designed to transform words, sentences, and documents into dense numerical vectors that capture semantic meaning. Unlike the generative Gemini models, it produces no prose or images — its job is to encode text so that similar concepts land close together in vector space, making it a foundational building block for search and retrieval systems rather than a chat or content tool.

Released in April 2026, it is the newest entry in Google's Gemini Embedding line and sits alongside a wide Gemini-family catalogue that includes generative text models like Gemini 3.5 Flash and Gemini 3.1 Pro Preview, the Nano Banana image models, and Veo video generators. Within that ecosystem, this model fills the specialized embedding niche that complements those generative systems.

It is best suited for retrieval-augmented generation pipelines, semantic search, document clustering, deduplication, recommendation, and classification workloads — anywhere you need to measure how closely two pieces of text relate. Pair it with a generative Gemini model to build grounded, knowledge-aware applications.