AI/ML●●Solid
TurboQuant for vector search – 2-4 bit compression
Data-oblivious quantization beats Product Quantization on online updates.
Big BrainNiche Gem
justsomeguy1996
8962mo ago
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GitHub Repository
TurboQuant WASM SIMD vector compression — 3 bits/dim with fast dot product. Requires relaxed SIMD (Chrome 114+, Firefox 128+, Safari 18+, Node 20+)
316 starsZig
TurboQuant-WASM – Google's vector quantization in the browser
by teamchong·Apr 4, 2026·165 points·7 comments
AI Analysis
●●●BangerWizardryZero to One
Google's ICLR 2026 quantization paper running client-side with SIMD-accelerated dot products.
Strengths
- •Enables client-side vector search without server roundtrips — genuinely new capability
- •Relaxed SIMD with @mulAdd maps to f32x4.relaxed_madd for hardware acceleration
- •npm package with TypeScript API and golden-value tests matching Zig reference
Weaknesses
- •Requires Chrome 114+, Firefox 128+, Safari 18+ — excludes older browser users
- •Research paper is ICLR 2026 — algorithm still emerging, less battle-tested
Category
Target Audience
Frontend developers building client-side vector search or ML features
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Faiss · ScaNN · usearch
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