Related question: Whenever I try to run Image generation locally, be it with Flux or Qwen, I seem to be getting results that are about 1-2 years behind what ChatGPT can produce today - and take up to 5 minutes for a single image. Is this a hardware problem (running it on a decent windows gaming PC), a configuration problem or just the reality of what local models can deliver at the moment on consumer hardware?
With my gamer 4060 ti 16gb it takes around 20 or 30 seconds for flux 1024x1024 image. At least that's how I remember it.
I found that for Qwen Image 2.1 the prompt enhancer makes a big difference.
It won't bridge the gap to gpt-image-2.5 though, and it's going to slow down the process further.
With a 4090, Qwen Image 2.1 Turbo takes around 15s per image, depending on the resolution. That's without the prompt enhancer.
Configuration and maybe prompting problem in my experience. Are you doing the prompting or are you letting claude or something do it?
Look into r/StableDiffusion and follow their prompts and download their ComfyUI workflows.
Thanks, I've done that, but with mixed results. I've also tried comfyui wrappers and alternatives that try to hide the complexity and just set sensible defaults, but I'm beginning to suspect its ultimately a consumer hardware vs million dollar NVidia server question.
What are you trying to generate? I've also noticed that local models aren't as good as cloud models due to hardware but there are still ways of optimizing the process.
You can get results a billion times better than the horrible, disgusting look of ChatGPT in less than a couple of seconds with a model like Krea or MOSS, and ComfyUI. With just a 8GB VRAM GPU or so...
Just visit Civitai, look at the pages for the base models, filter for images with the ComfyUI workflow in them, then you can just download and drag and drop them onto your local ComfyUI app.
SwarmUI makes things a lot easier. Kroma generates an image in about 90s with a 4070.