Würstchen
Efficient latent diffusion model using highly compressed latent space.
About
Wurstchen is a text-to-image latent diffusion framework that moves the expensive text-conditional stage into a highly compressed latent space. It adds a second compression stage so that Stage A and Stage B reconstruct images while Stage C learns the text-conditional model in a low-dimensional space, reaching a 42x compression factor and reducing training and inference cost while keeping image quality. Created by Pablo Pernias under the MIT license.
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Details
- Category
- Image Generation
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Intermediate (3/5)
- License
- MIT
- Minimum VRAM
- 4 GB
- Added
- Apr 3, 2026
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