Stable Diffusion Users Seek Reliable Preset System for Forge-Neo UI Settings

Stable Diffusion users operating on the Forge-Neo platform are raising urgent concerns over the absence of a reliable, comprehensive preset system to save and recall user interface configurations. The issue, first highlighted in a Reddit thread on r/StableDiffusion, reveals a critical gap in functionality that has long been standard in the original AUTOMATIC1111 WebUI—where the now-legendary sd-webui-state-manager extension allowed users to save entire workflows, including checkpoints, LoRAs, embeddings, prompts, and generation parameters, with a single click.

When users migrated to Forge-Neo, a performance-optimized fork of the original WebUI, they expected similar capabilities. A community-developed continuation of the state manager, named sd-webui-state-manager-continued, was initially hailed as a solution. However, as reported by user /u/HentaiLootChest, the extension fails to persist key parameters such as sampling steps, CFG scale, and sometimes even sampler selection. When questioned, the developer acknowledged that the extension was only "technically compatible" with Forge-Neo and that fixing these incompatibilities was not a priority.

This revelation has sparked a broader conversation within the AI art community about the sustainability of third-party extensions in rapidly evolving platforms. Forge-Neo, while praised for its speed and memory efficiency, has not yet integrated native preset management into its core architecture. Unlike A1111, which has a mature ecosystem of community tools, Forge-Neo’s development team has focused primarily on core rendering improvements, leaving UI state persistence as an afterthought.

According to the original Reddit post, users are now left with brittle workarounds: manually documenting settings in text files, using browser bookmarks to save URLs with parameters, or reverting to the slower but more stable A1111 interface. Some have turned to scripting solutions using Python or JavaScript to automate parameter injection, but these require technical expertise far beyond the average artist’s skillset.

While the official Forge-Neo GitHub repository and its associated forums (such as the unofficial community hub on GitHub and Discord) have seen sporadic requests for preset functionality, no official roadmap item has been confirmed. In contrast, other AI platforms like ComfyUI have embraced node-based workflow saving as a foundational feature, demonstrating that such functionality is not only feasible but increasingly expected.

Industry analysts suggest that the lack of a native preset system may hinder Forge-Neo’s adoption among professional creators who rely on consistent, repeatable outputs for commercial projects. "If you’re producing 50 images a day for a client, you can’t afford to reconfigure your settings each time," said Dr. Lena Torres, an AI ethics and usability researcher at the Digital Creativity Lab. "This isn’t a convenience feature—it’s a productivity imperative."

Community members have begun calling for open collaboration: a GitHub issue has been opened urging developers to either integrate preset functionality into Forge-Neo’s core or support a community-driven fork with full compatibility. Some suggest that the original sd-webui-state-manager-continued project could be revived as a community-maintained initiative, with funding through Patreon or GitHub Sponsors.

Until then, artists remain in limbo—caught between the performance gains of Forge-Neo and the workflow integrity of legacy systems. The absence of a simple "Save Preset" button may seem minor, but for those whose livelihoods depend on efficiency, it represents a significant barrier to adoption. As one user aptly put it: "We don’t need more models. We need better tools to use the ones we already have."

For now, the ball is in the court of Forge-Neo’s maintainers. With growing pressure from users and the precedent set by other platforms, the demand for a native, reliable preset system may soon become impossible to ignore.