I'm building a semantic search feature for my app and need an embedding model recommendation

For a semantic search feature, a strong default recommendation is:

Recommended model: text-embedding-3-large

• Best quality for semantic retrieval and ranking
• Strong across many domains and query styles
• Good choice if search relevance matters most

If you want a cheaper/faster option: text-embedding-3-small

• Lower cost and latency
• Still quite capable for many apps
• Good if you have high query volume or a tighter budget

How to choose

• Use text-embedding-3-large if:

  • Search quality is a top priority
  • You have diverse content
  • You want the best recall/precision tradeoff

• Use text-embedding-3-small if:

  • You need lower cost
  • You’re prototyping
  • Your content is fairly straightforward

Practical tip

For semantic search, also make sure to:

• Chunk documents sensibly
• Store embeddings in a vector database
• Retrieve top-k candidates, then rerank if needed
• Embed queries with the same model as your documents

If you want, I can also recommend:

1. the best model for your budget,
2. a vector DB stack, or
3. an end-to-end semantic search architecture.