What is Gemini Embeddings?
Gemini Embeddings are SOTA on MTEB (the embedding leaderboard) and are now generally available for production use. If you are doing RAG, you should try Gemini Embeddings!
Problem
Developers and data scientists previously relied on older embedding models that offered lower accuracy and struggled with efficient production deployment, leading to suboptimal performance in retrieval-augmented generation (RAG) applications.
Solution
A developer tool (API) that provides state-of-the-art (SOTA) embeddings built on Gemini, enabling users to integrate high-performance embeddings into production-grade applications for tasks like RAG. Example: Embed text for semantic search using Google's infrastructure.
Customers
Machine learning engineers, data scientists, and developers building AI-driven applications requiring advanced NLP capabilities, particularly those focused on RAG or semantic search.
Unique Features
Ranked #1 on the MTEB leaderboard for embeddings, production scalability via Google Cloud, and direct integration with Gemini's AI capabilities.
User Comments
Top-tier accuracy for semantic search
Seamless production deployment
Reliable performance at scale
Essential for RAG workflows
Superior to older embedding models
Traction
Ranked #1 on MTEB, generally available via Vertex AI, part of Google's AI ecosystem with millions of enterprise developers.
Market Size
The global NLP market is projected to reach $161 billion by 2029 (MarketsandMarkets, 2024), driven by demand for advanced AI embeddings.
