AUTOMATIC1111 Stable Diffusion WebUI vs Dzine
AUTOMATIC1111 Stable Diffusion WebUI
github.com
Dzine
dzine.aiSide by side
| Figure | AUTOMATIC1111 Stable Diffusion WebUI | Dzine |
|---|---|---|
| Price from | — | $8.99/mo |
| Free plan | — | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| iOS | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 0 | 6 |
| Spec score · AI image generators | 8.1 (#47) | 9.2 (#5) |
| API access | Yes | Yes |
| Free plan | Yes | Yes |
| Image editing | Features include color sketch, prompt matrix, tiling, and batch processing. | Yes |
| Output formats | PNG,JPEG | JPG,PNG,WebP |
| Reference images | Yes | Yes |
| Text-to-image | Yes | The image generator turns text prompts into custom images and exposes models including Dzine, Nano Banana Pro, Midjourney, Z-Image and Google Imagen. |
Plans
AUTOMATIC1111 Stable Diffusion WebUI
No plans published.
Dzine
- Beginner$8.99 a month
- Creator$24.99 a month
- Master$59.99 a month
- Master Pro$149.99 a month
- FreeFree
- API pay-as-you-go$50, paid once
In their own words
AUTOMATIC1111 Stable Diffusion WebUI
AUTOMATIC1111 Stable Diffusion WebUI is a Gradio-based interface for generating and editing images with Stable Diffusion. It provides text-to-image and image-to-image modes, plus inpainting, outpainting, color sketch, and prompt matrix tools. The Extras tab offers face restoration and upscaling tools including GFPGAN, CodeFormer, RealESRGAN, ESRGAN, SwinIR, Swin2SR, and LDSR. Users can train embeddings and hypernetworks, use LoRAs, and add custom scripts or community extensions. The project lists support for Stable Diffusion 2.0, Alt-Diffusion, and Segmind Stable Diffusion, and includes an API. It provides installation instructions for Windows, Linux, and Apple Silicon Macs, and lists PNG and JPEG output. The README recommends NVIDIA GPUs and links setup guidance for AMD GPUs, Intel CPUs and GPUs, and Ascend NPUs. Its one-click installation still needs Python and Git installed. The project lists support for 4 GB video cards, with reports of 2 GB working. It is free and self-hosted.