[First] Gemini Embedding model is now generally available

Gemini Embedding is now generally available. It ranks #1 on the MTEB leaderboard and is ready for at-scale production use.

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First Gemini Embedding model is here 🚀

Start building

The new Gemini Embedding model is now live in the Gemini API. Start building better Retrieval-Augmented Generation (RAG), classification, and search today.   It's our most powerful and versatile text embedding model ever, achieving top-ranking scores on the Massive Text Embedding Benchmark (MTEB) leaderboard, and is priced at $0.15 USD per million tokens. Gemini Embedding supports 100+ languages and has a controllable embedding size.   You can generate text embeddings by using the embed_content method:

from google import genai client = genai.Client() result = client.models.embed_content(     model="gemini-embedding-001",     contents="What is the meaning of life?" ) print(result.embeddings)

New to embeddings? Check out this embedding crash course.

Happy coding, The Google AI Studio team

Building with multimodal AI Discover how Gemini's multimodal understanding is unlocking a new class of vision-powered apps and context-aware software with insights from Gemini's multimodal product lead, Ani Baddepudi.   Watch the video

Did you know? You can get significantly higher request limits and flexible pay-as-you-go pricing with a paid tier. Explore paid tier

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