MyCaptionAI
Introducing text-embedding-3-smallOpenAIReleased January 25, 2024

text-embedding-3-small

Highly efficient embedding model featuring Matryoshka dimension shortening for ultra-low storage and compute costs.

embeddingsProprietary API$0.02 / 1M tok (1536 dims)Context: 8.191K (8,191 tokens)
Official Model Card & DocsTry in AI Studio / PlaygroundGitHub Repository

Technical Specifications

Architecture Type
Dense Matryoshka Representation Transformer
Total Parameters
Compact Dense
Context Window
8.191K (8,191 tokens)
Max Output Tokens
1.536K (1,536 tokens)
Knowledge Cutoff
September 2021
Supported Modalities
text
License & Access
OpenAI Business Terms

Benchmark Evaluations

Mteb
62.3
Miracl
44

Deep Architectural Overview

text-embedding-3-small generates 1536-dimensional embeddings for vector search and RAG. Using Matryoshka Representation Learning, developers can shorten vectors to 512 dimensions without substantial loss of retrieval accuracy.

Strengths & Considerations

Core Strengths
  • Ultra-cheap $0.02 per 1M tokens
  • Matryoshka representation shortening down to 512 dims
  • Outperforms text-embedding-ada-002
Known Limitations
  • Complex multi-lingual search is better served by text-embedding-3-large

Token & API Pricing

Input Tokens (1M)$0.02
Output Tokens (1M)Contact
Pricing is verified directly against OpenAI's developer documentation and API rate sheets.

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