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HuaweiNovember 14, 2025

SINQ

Open Source
Infrastructure
LLMs
ML

Explore SINQ

Visit the official website to learn more and get started

### TL;DR

SINQ (Sinkhorn-Normalized Quantization) is a novel, fast, and high-quality quantization method designed to make any Large Language Model (LLM) smaller while preserving accuracy. It offers a plug-and-play, model-agnostic technique that delivers state-of-the-art performance for LLMs without sacrificing accuracy.

Key Insights & Metrics

Pricing
Free
Cost structure
Version
1.0
Current release version
Hardware
NVIDIA GPU with CUDA support, 8GB RAM
Compute requirements
Category
Open Source
Licensing model
Region
Switzerland
Primary region

Key Features

  • Calibration-free quantization
  • Supports both symmetric and asymmetric quantization
  • NF4 support
  • Approximately twice as fast as HQQ
  • Higher model quality compared to alternatives

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