google-ai-edge/ai-edge-quantizer

LLM model quantization (compression) toolkit with HW acceleration support for Nvidia, AMD, Intel GPU and Intel/AMD/Apple CPU via HF, vLLM, and SGLang.

A pytorch quantization backend for optimum

PTQ-Level Efficiency, QAT-Level Accuracy|训练后量化的效率，量化感知训练的精度

Adaptive Precision for EXpert Models: MoE-aware mixed-precision quantization

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

Model Compression Toolkit (MCT) is an open source project for neural network model optimization under efficient, constrained hardware. This project provides researchers, developers, and engineers advanced quantization and compression tools for deploying state-of-the-art neural networks.

Support PyTorch model conversion with LiteRT.

Produce your own Dynamic 3.0 Quants and achieve optimum accuracy & SOTA quantization performance! Input a target size and the toolchain will create a GGUF recipe tuned to your hardware within seconds — flexible model sizing and lowest achievable perplexity/kld for GGUF enthusiasts seeking precise and automated dynamic quant production.