Stable Diffusion XL on Mac with Advanced Core ML Quantization

Faster Stable Diffusion with Core ML on iPhone, iPad, and Mac

Swift 🧨Diffusers - Fast Stable Diffusion for Mac

Using Stable Diffusion with Core ML on Apple Silicon

🧨 Accelerating Stable Diffusion XL Inference with JAX on Cloud TPU v5e

Accelerating Stable Diffusion Inference on Intel CPUs

Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

Quanto: a PyTorch quantization backend for Optimum

Exploring Quantization Backends in Diffusers

Memory-efficient Diffusion Transformers with Quanto and Diffusers

Quartet II: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation

arXiv:2601. 22813v2 Announce Type: replace Abstract: The NVFP4 lower-precision format, supported in hardware by NVIDIA Blackwell GPUs, promises to allow, for the first time, end-to-end fully-quantized pre-training of massive models such as LLMs.

KroQuant: Kronecker-Structured Block Transforms for Efficient Post-Training Quantization of Diffusion Transformers

arXiv:2607. 21446v1 Announce Type: new Abstract: Post-training quantization (PTQ) of diffusion transformers (DiTs) to W4A4 severely degrades output quality, because activations entering each linear layer contain outliers that 4-bit formats cannot represent.

Using LoRA for Efficient Stable Diffusion Fine-Tuning