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Text Embedding 3 Small
OpenAI
cost effective
production ready
Overview
A cost-effective embedding model designed for efficient text representation and semantic search applications. It converts text into numerical vectors that capture semantic meaning, enabling similarity comparisons, clustering, and classification. This compact model balances performance and efficiency for production-level semantic search, recommendation systems, and content organization.
Key Strengths
Semantic search optimization
Efficient document retrieval
Text similarity calculations
Content clustering
Capabilities
Categories
Embedding
Specifications
Context Size
8,191 tokens
Pricing
Input$0.02 / 1M tokens
Output$0 / 1M tokens