# G^2PTQ: Improving LLM Post-Training Quantization with Generalized Gradient Compensation > Source: > Published: 2026-09-29 10:30:58+00:00 Post-training quantization (PTQ) is a practical approach to reducing the memory and computational footprint of large language models (LLMs) without retraining. GPTQ-based methods have become the de facto standard, yet they suffer from two complementary limitations. Methods with local, layer-wise obj