Concepts & capability filters
representation
Embedding
An embedding maps text into a dense vector so semantic similarity becomes distance — the backbone of RAG and semantic search.
- Category
- representation
- Difficulty
- Not classified
- Aliases
- None tracked
- Last reviewed
- 2026-07-02
Key facts
- Choosing an embedding model is a separate decision from your generation model: weigh retrieval quality on your domain, vector dimensionality (which drives storage and query cost), max input length, and per-token or per-request price across providers.