product
Data quality: Editorially ReviewedFree
Retrieval & data layer
Vector Databases
Software & technology
Workflow orchestration
Self-hosted / on-premises
Retrieval & semantic search
Faiss
Vector Databases
Overview
Faiss is an open-source library by Meta for efficient similarity search and clustering of dense vectors. It provides algorithms for searching sets of vectors of any size, including those that may not fit in RAM. Faiss supports multiple index types, GPU acceleration, and is widely used as a building block in vector search pipelines.
- Pricing model
- Free
- Deployment
- Self-hosted / on-premises
- Regions served
- Global
- Categories
- Free, Retrieval & data layer, Vector Databases, Software & technology, Workflow orchestration, Self-hosted / on-premises, Retrieval & semantic search
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Workflow orchestration
Deployment options
Self-hosted / on-premises
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- faiss.ai
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
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Anyone can suggest a correction — you don't need an account. An editor checks every suggestion against the sources before the record changes.