Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google’s TurboQuant Algorithm
Vector search underpins most retrieval-augmented era (RAG) pipelines. At scale, it will get costly. Storing 10 million doc embeddings in float32 consumes 31 GB of RAM. For dev groups operating native or on-premise inference, that quantity creates actual constraints. A new open-source library known as turbovec addresses this instantly. It is a vector index written…
