Krita AI Diffusion 1.53.0 Adds int4 Quantization, EU AI Act Compliance, and Semantic Segmentation Control
Krita AI Diffusion 1.53.0 is adding semantic segmentation control layers via the Anima regional controlnet and modernizing its backend with PyTorch 2.13 and CUDA 13. The update doubles down on hardware accessibility by introducing int4 and int8 quantization support, allowing artists to run larger diffusion models like Flux on GPUs with as little as 6 to 8 gigabytes of VRAM. For cloud users on Interstice.cloud, the release implements EU AI Act compliance through metadata tagging and invisible watermarking, though local runners remain entirely unaffected. Developers removed Nunchaku optimization and insightface to consolidate their quantization strategy, while community contributors also fixed long-standing timestamp and prompt import bugs across Windows, Linux, and macOS.
Krita AI Diffusion 1.53.0 Adds int4 Quantization, EU AI Act Compliance, and Semantic Segmentation Control
Krita AI Diffusion 1.53.0 introduces significant updates including semantic segmentation control layers, int4 and int8 quantization support, and compliance with the EU AI Act. The new segmentation model allows artists to define boundaries on their canvas, giving them better control over how different regions of an image respond to prompts. Backend improvements with PyTorch 2.13 and CUDA 13 enhance memory management and model compatibility, making high-end models accessible on lower VRAM GPUs. Although some features like Nunchaku support have been removed to streamline quantization strategies, the update overall enhances usability for artists and ensures compliance for cloud users without affecting local runners
