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First Gemini Embedding model is here 🚀 |
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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: |
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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)
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| The Google AI Studio team |
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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 |
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| You can get significantly higher request limits and flexible pay-as-you-go pricing with a paid tier. | |
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| This email was sent to anshari.kurniawan@gmail.com because you signed up to receive emails about Google AI. If you do not wish to receive these emails, please unsubscribe. |
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