In evaluations, Stable Cascade outperformed other leading AI art models including SDXL in terms of image quality and prompt alignment. It also has faster inference times despite having 1.4 billion more parameters than SDXL. The model also supports other capabilities including image variations and image-to-image translations. Stable Cascade is currently in research preview and available for non-commercial usage with a code available on GitHub.
Key takeaways:
- Stability AI is previewing a new image generation model called Stable Cascade, which is designed to be more flexible and efficient than the current generation of Stable Diffusion models.
- Stable Cascade uses a three-stage architecture, which provides major advantages in training efficiency and customization. It also has the potential for Direct Preference Optimization (DPO) to further improve image quality.
- In Stability AI’s evaluations, Stable Cascade outperformed other leading AI art models including SDXL in terms of both image quality and prompt alignment. It also has faster inference times despite having 1.4 billion more parameters than SDXL.
- Stable Cascade supports other capabilities including image variations and image-to-image translations. It is currently in research preview and available for non-commercial usage with a code available on GitHub.