Mochi Diffusion vs Stable Diffusion WebUI Forge
Mochi Diffusion
github.com
Stable Diffusion WebUI Forge
github.comSide by side
| Figure | Mochi Diffusion | Stable Diffusion WebUI Forge |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 0 | 1 |
| Spec score · AI image generators | 6.8 (#117) | 8.9 (#12) |
| License | The GitHub repository identifies the project license as GPL-3.0. | The repository identifies its license as AGPL-3.0. |
| Model support | The app supports Core ML Stable Diffusion models and FLUX.2 Klein models; Stable Diffusion models must be converted for Core ML, while Klein models need no conversion. | The README says Flux BitsandBytes NF4 and several GGUF quantizations are natively supported, with LoRA support for specified NF4 and GGUF variants. |
| Purpose | Mochi Diffusion is a native macOS app for generating images locally with Core ML Stable Diffusion and FLUX.2 Klein models. | Forge is a platform built on Stable Diffusion WebUI and Gradio to ease development, optimize resource management, speed up inference, and study experimental features. |
| Reference images | Yes | Yes |
| Support | The project directs bug reports and feature requests to GitHub issues and code contributions to pull requests. | The maintainer invites users to open issues for problems and says they will check them every several days. |
| Text-to-image | Yes | Yes |
Plans
In their own words
Mochi Diffusion
Mochi Diffusion has no write-up on Specifiction yet; its figures are above.
Stable Diffusion WebUI Forge
Stable Diffusion WebUI Forge is a free, open-source platform built on Stable Diffusion WebUI for image generation and editing. It supports text-to-image creation, reference images, and image editing, with PNG, JPG, JPEG, WebP, AVIF, and GIF listed as output formats. The project aims to ease development, manage resources, speed inference, and explore experimental features. Its interface is based on Gradio, and the README offers a one-click installation package that includes Git and Python. Windows launch scripts, shell scripts, a macOS environment script, and source installation instructions are listed. Forge includes GPU memory management and components such as LoRAs, ControlNets, IP-Adapters, Instant-IDs, reference-only methods, and extensions. Several Flux BitsandBytes and GGUF variants are natively supported, with GPU weight and swap controls; some variants support LoRA. The README lists txt2img and img2img API endpoints as normal, while improved Flux support is pending. The project is described as under construction, so its documentation, interface, and functionality may change. Its license is AGPL-3.0.