Local AI Glossary
What is Embedding model?
Source: local-llm.net/glossary
A model specifically designed to produce embedding vectors from input text, as opposed to generative language models that produce text output. Embedding models are typically small (100M-500M parameters) and fast. They are used in RAG pipelines to convert both documents and queries into vectors for similarity search.
How Embedding model fits in the local AI stack
Embedding model is part of the broader local AI ecosystem. See the related guides, comparisons, and tools below to see how it applies in practice.
See also
- Full Local AI Glossary
- All learn topics
- What is Local AI?
- Quantization explained
- Hardware requirements
- How to choose a local LLM