11 months ago

Originally Posted to Hugging Face and shared here with permission from Stability AI.

SDXL consists of a two-step pipeline for latent diffusion: First, we use a base model to generate latents of the desired output size. In the second step, we use a specialized high-resolution model and apply a technique called SDEdit (https://arxiv.org/abs/2108.01073, also known as "img2img") to the latents generated in the first step, using the same prompt.

Model Description

  • Developed by: Stability AI

  • Model type: Diffusion-based text-to-image generative model

  • Model Description: This is a model that can be used to generate and modify images based on text prompts. It is a Latent Diffusion Model that uses two fixed, pretrained text encoders (OpenCLIP-ViT/G and CLIP-ViT/L).

  • Resources for more information: GitHub Repository.

Model Sources


Direct Use

The model is intended for research purposes only. Possible research areas and tasks include

  • Generation of artworks and use in design and other artistic processes.

  • Applications in educational or creative tools.

  • Research on generative models.

  • Safe deployment of models which have the potential to generate harmful content.

  • Probing and understanding the limitations and biases of generative models.

Excluded uses are described below.

Out-of-Scope Use

The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.

Limitations and Bias


  • The model does not achieve perfect photorealism

  • The model cannot render legible text

  • The model struggles with more difficult tasks which involve compositionality, such as rendering an image corresponding to “A red cube on top of a blue sphere”

  • Faces and people in general may not be generated properly.

  • The autoencoding part of the model is lossy.


While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.

The chart above evaluates user preference for SDXL (with and without refinement) over Stable Diffusion 1.5 and 2.1. The SDXL base model performs significantly better than the previous variants, and the model combined with the refinement module achieves the best overall performance.


What is SD XL?

SD XL is a highly specialized Image generation AI Model of type Safetensors / Checkpoint AI Model created by AI community user civitai. Derived from the powerful Stable Diffusion (SDXL 1.0) model, SD XL has undergone an extensive fine-tuning process, leveraging the power of a dataset consisting of images generated by other AI models or user-contributed data. This fine-tuning process ensures that SD XL is capable of generating images that are highly relevant to the specific use-cases it was designed for, such as base model, official, stability ai.

With a rating of 4.81 and over 1330 ratings, SD XL is a popular choice among users for generating high-quality images from text prompts.

Can I download SD XL?

Yes! You can download the latest version of SD XL from here.

How to use SD XL?

To use SD XL, download the model checkpoint file and set up an UI for running Stable Diffusion models (for example, AUTOMATIC1111). Then, provide the model with a detailed text prompt to generate an image. Experiment with different prompts and settings to achieve the desired results. If this sounds a bit complicated, check out our initial guide to Stable Diffusion – it might be of help. And if you really want to dive deep into AI image generation and understand how set up AUTOMATIC1111 to use Safetensors / Checkpoint AI Models like SD XL, check out our crash course in AI image generation.

Download (5.53 GB) Download available on desktop only
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Base model: SDXL 1.0

Version v1.0 Refiner VAE fix: 1 File

To download these files, please visit this page from a desktop computer.

6 Versions

SD XL v1.0 Refiner VAE fix prompts

Explore the best SD XL prompts