text-embedding-3-small

text-embedding-3-small is OpenAI's small embedding model released in January 2024 — designed as a high-performance, low-cost vector embedding option for production applications. The model produces 1536-dimensional vectors by default (configurable down to 256 or 512 dimensions using OpenAI's dimension reduction feature) and was priced at $0.02 per million tokens at launch, dramatically cheaper than its predecessor text-embedding-ada-002. Performance on MTEB (Massive Text Embedding Benchmark) significantly exceeded ada-002 at a fraction of the cost. The model supports up to 8K tokens of input, making it suitable for chunked-document workflows in RAG systems. Real-world deployments span semantic search, retrieval-augmented generation, recommendation systems, content classification, clustering, and anomaly detection. The model became one of the most widely-used commercial embedding APIs for production. AI governance, AI compliance, and AI risk management programs document embedding-model versions in retrieval-system inventories — supporting responsible AI through embedding-pipeline transparency across enterprise AI semantic search deployments worldwide.

Centralpoint Routes Embeddings Across Providers: Oxcyon's Centralpoint AI Governance Platform calls text-embedding-3-small alongside Cohere, Voyage, BGE, and other embedding models — keeping vector content on-prem. Centralpoint meters every embedding call and embeds RAG chatbots into your portals via a single JavaScript line.


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