Turbovec – Google's TurboQuant for vector search in Rust
Turbovec is a new Rust-based vector index library that utilizes Google's TurboQuant algorithm to provide high-performance, memory-efficient vector search. It is designed for developers building RAG applications who need to manage large datasets with limited memory and low latency.
Why it matters
Efficient vector search is a critical component for scaling AI applications and Retrieval-Augmented Generation (RAG) systems in resource-constrained environments.
A 10 million document corpus takes 31 GB of RAM as float32. turbovec fits it in 4 GB - and searches it faster than FAISS.
turbovec is a Rust vector index with Python bindings, built on Google Research's TurboQuant algorithm — a data-oblivious quantizer with near-optimal distortion and no separate training phase.
Building RAG where privacy, memory, or latency matters? You're in the right place.
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