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text-embedding-3-small

text-embedding-3-small

  • 0.02/M Input Tokens
  • 0 Output Tokens

text-embedding-3-small is OpenAI’s cost-effective text embedding model, serving as the lightweight version in the text-embedding-3 series. This model maintains good performance while offering a more economical pricing option.

Key Features

  • Cost-Effective: Approximately 1/6 the price of text-embedding-3-large
  • Multilingual Support: Supports embeddings for 100+ languages
  • Context Length: Handles up to 8192 tokens of input
  • Embedding Dimension: Fixed 1536-dimensional embedding vectors

Performance

  • Outperforms the older text-embedding-ada-002 on most tasks
  • Slightly lower performance than text-embedding-3-large, but sufficient for most applications

Use Cases

  1. Text Similarity Matching
  2. Information Retrieval
  3. Text Classification
  4. Small-scale RAG Applications
  5. Personal Projects or Budget-conscious Commercial Applications

Pricing

  • Input: $0.00002 / 1K tokens
  • Output: Free

Usage Recommendations

  • Ideal for projects with limited budgets requiring quality embeddings
  • Recommended for testing and development
  • Consider upgrading to text-embedding-3-large if highest embedding quality is required

text-embedding-3-small offers an excellent balance between performance and cost, making it particularly suitable for startups and budget-sensitive applications.

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