Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs

Researchers conducted the first systematic study on post-training quantization for diffusion large language models (dLLMs), identifying activation outliers as a key challenge for compression. The study evaluated state-of-the-art quantization methods across multiple dimensions to provide insights for efficient dLLM deployment on edge devices.