Highlights: 768x768 native models (v1.x maxed out at 512x512) a built-in 4x upscaler: "Combined with our text-to-image models, Stable Diffusion 2.0 can now ge

Highlights: 768x768 native models (v1.x maxed out at 512x512) a built-in 4x upscaler: "Combined with our text-to-image models, Stable Diffusion 2.0 can now generate images with resolutions of 2048x2048–or even higher." Depth-to-Image Diffusion Model: "infers the depth of an input image, and then generates new images using both the text and depth information." Depth-to-Image can offer all sorts of new creative applications, delivering transformations that look radically different from the original but which still preserve the coherence and depth of that image (see the demo gif if you haven't looked) Better inpainting model Trained with a stronger NSFW filter on training data. For me the depth-to-image model is a huge highlight and something I wasn't expecting. The NSFW filter is a nothing (it's trivially easy to fine-tune the model on porn if you want, and porn collections are surprisingly easy to come by...). The higher resolution features are interesting. HuggingFace has got the 1.x models working for inference in under 1G of VRAM, and if those optimizations can be preserved it opens up a bunch of interesting possibilities.