old but relevant, it's like a production system. We can continue to tune and squeeze 1mp pictures out of it in high quality on relevant localized hardware without breaking a sweat. 1-3 seconds on a m3 system, and then cascade of tooling below stays the same.
replyA1111 also had its time. Comfy takes a couple hours to learn, and then it’s vastly superior. Like, if you are already on Mac there is no reason to also kick yourself in the face trying to go back to 1111.
replyThere's also sdcpp ( https://github.com/leejet/stable-diffusion.cpp ) . It is for people that know command line shells like bash or Powershell. SDCPP is like llama.cpp but it is for using text to image AI models. Not everyone likes the node/graph programming interface in Comfy or a Webpage interface. Some people need these GUI/web interfaces and get lost and frustrated in shell scripting.
replyTotally and sdcpp and drawthings were inspiration for this work. It's not just about the UI, there's a whole stack of plugins, APIs etc. It would be a bigger shift, than just use other UI. Composition etc.
replyPlus this was fun to learn where the attention and time spent is eating up. I plan to git into the UNet, and then do some Multi-Model Memory Attention tuning as well, for Refining and Inpaint Swaps for the 8Gb Macs.
A1111 (or rather Forge Neo at this point) can still be pretty useful (for a Windows user) if somebody just want a batteries-included approach because it makes it trivial to move back and forth between masking, manual inpainting, tacking on a high‑res fix and/or upscale, and swapping things out on the fly quickly.
replyCaveat: No idea how well A1111 and its variants function on Mac though.
These days I mostly use ComfyUI because after building out a node‑based workflow, it’s easy to export as a JSON file with websocket outputs that I can integrate into my programs.
https://github.com/Haoming02/sd-webui-forge-classic/tree/neo