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FAISS

Vector Databases & Memory
Open Source AI
AI Research
Meta AI Research

High-performance similarity search library from Meta AI. CPU and GPU implementations. Multiple index types optimized for different scale/speed trade-offs. Used by Meta for production search at billion-vector scale. Open-source with active development.

Why Use FAISS

Industry-proven at massive scale - powers Facebook search and recommendations. Fastest pure similarity search available. Multiple index types let you optimize for your exact use case. GPU support for extreme performance. Free and open-source. Best for research, experiments, and custom deployments where you need maximum control.

Use Cases for Builders
Practical ways to use FAISS in your workflow
  • Research and experiment with vector similarity algorithms
  • Build custom agent memory systems with specific performance needs
  • Implement high-throughput recommendation engines
  • Create specialized embeddings search for academic research
  • Deploy on-device vector search for edge AI applications
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