RyanCodrai/turbovec

Health v2 · maintenance only

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16441 stars · 1426 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

turbovec is a Rust vector index with Python bindings implementing Google's TurboQuant algorithm for 2-4 bit vector quantization with SIMD-accelerated nearest-neighbor search. It supports online ingest without a training phase, incremental crash-safe saves, and filtered search, claiming faster search than FAISS IndexPQFastScan.

Use cases

• search embeddings from millions of documents in limited RAM
• build a fully local air-gapped RAG stack
• quantize vectors to 2-4 bits without a training step
• run fast nearest-neighbor search with SIMD on ARM or x86
• incrementally persist a growing vector index
• filter search results by id allowlist without recall loss

When to choose

• you need memory-efficient vector search with heavy quantization
• you want a pure local, self-hosted alternative to FAISS or managed vector services
• your corpus grows continuously and you want online ingest without retraining
• you need fast filtered ANN search on AVX-512 or NEON hardware

When to avoid

• you need full float32 precision or exact nearest-neighbor search
• you require a distributed or managed vector database
• you need rich index types like HNSW graph search
• your hardware lacks SIMD support and scalar fallback speed is insufficient

Facets

library · maturity active

vector-database search-engine machine-learning rag machine-learning artificial-intelligence databases python rust cross-platform ann quantization simd embeddings nearest-neighbor faiss-alternative avx512 neon retrieval-augmented-generation search

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