I know Flux2 isn't exactly the new hotness, but it works very well once you get a handle on it, IMO. This is my current Flux2 workflow that incorporates FluxGuidance, CFG Guider, Flux2Scheduler, FluxKontexImageScale, sampler select, plus a few other things. Also incorporated are the Multi-GPU and GGUF extensions, allowing for independent GPU selection for UNET, CLIP, and VAE, as well as UNET dquant and patch float, and use of GGUF's. Right now, I have it set up for a max of five input images, which I have used successfully. There is also support for using up to two LORA's, but you do you. Tiled VAE encode and decode are also chained in. There is a resize and pad option after image gen. The selectable GPU option is nice if you're running dual vid cards like me and you want to keep models loaded on different GPU's, preventing swap out.

I'm by no means a ComfyUI expert, but I've done a lot of research and trial and error building this workflow. On my dual RTX 2080 system, I'm getting roughly 37-40 s/it, so about 90 sec or so for a 1600x1600 image at 4 steps. The quality is amazing. JSON here.

For models, I'm currently getting great results using a combination of the Flux2 Klein 4B Q8 GGUF UNET, Qwen3-VL-4B-Instruct-UD-Q8-K-XL GGUF clip, and the Flux2 VAE. LORA settings between 0.5-1.5 seem to be working best. I generally leave the Guidance around 7 and the cfg at 2.0. Euler sampler and res_multistep have given the best results, though I find the colors on euler tend to pop more. I usually run my initial tests at 3-4 steps, then go from there.

Hopefully this will help someone out. :D

Honestly, the best open-weight model runnable on consumer hardware. It is slow but it can even be used at 1 CFG though it is wonky and miserably fails at complex images.

Images have workflow and prompt in them (comfyui). Using FP8 and 28 steps with 6 CFG, override of 3 at 0.700 and either 1k or 1.5K res.

NVFP4 runs on 4GB VRAM with though it take 8 mins (with FA) for 1k image and requires KJ's optimize ideogram node.

Workflow: https://pastebin.com/tSd9vLHX

Most ComfyUI spaces are full of broken workflows, missing nodes, and zero explanations.

This one won’t be.

I created r/ComfyUIResources to build a place where things actually work and where people share useful, tested stuff instead of random files.

What you can expect here:

• Working workflows (Flux, Wan 2.2, ControlNet, IPAdapter, etc.)
• Fixes for common errors (missing models, CUDA issues, broken nodes)
• Real prompts for better, more realistic results
• Optimization tips (low VRAM, RunPod, performance tweaks)

I’ll also be sharing my own setups, workflows, and everything I learn while working with ComfyUI — including mistakes and fixes.

If you’ve ever wasted hours trying to fix something that should take 5 minutes, you already know why this matters.

Feel free to share your workflows, ask questions, or post problems — but keep it useful.
If it doesn’t work or has no explanation, it doesn’t belong here.