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Software Library
Summary
turbovec is a high-performance Rust-based vector index with Python bindings that utilizes Google's TurboQuant algorithm for zero-training, data-oblivious quantization. It offers significant memory compression and faster search speeds than FAISS, making it ideal for privacy-focused, local RAG applications.
Highlights
- Extreme memory efficiency, reducing a 31 GB float32 corpus to just 4 GB.
- High-speed search performance via hand-written SIMD kernels (AVX-512 and NEON).
- Zero-training quantization that requires no codebook training or data-dependent calibration.
- Efficient filtered search using allowlists that prevents over-fetching and maintains recall.
- Supports stable external IDs and O(1) deletions via the IdMapIndex.
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Context
Audience
Machine Learning Engineers and Software Developers building high-performance, privacy-centric RAG applications
DomainMachine Learning
Formatopen source library
Accessopen source
Topics
Related
Retrieval Augmented GenerationVector DatabasesFAISSTurboQuantLangChainLlamaIndex