UPDATED

Flux2Klein Ksampler has been added to the repo : here

Sample Workflow: here

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dropping some news real quick

I’m releasing a proper Ksampler for flux2klein because I figured out that using the raw formula produces way more accurate colors and I genuinely think THIS is the main reason we keep getting that color shift and washed out results.

and before anyone asks, yes I benchmarked it against ModelSamplingFlux using the exact same shift settings and the ksampler I built wins every time. accurate colors, zero washout, no exceptions.

the difference comes down to the ODE formula. what’s inside comfy right now is:

x_new = x + dt * (x + v)

that extra x getting thrown in is what’s drifting your colors every single step. my ksampler uses the raw formula the way it’s actually supposed to be:

x_new = x + dt * v

that’s it. clean velocity, straight line, no gray fog creeping into your renders.

what people are missing here is that this is not happening in isolation. ComfyUI’s sampling path also includes extra internal transforms around sigma handling, prediction scaling, and latent normalization that effectively bias the trajectory toward lower variance over time. even if the model output is correct, those extra layers accumulate and show up visually as desaturation and that washed out look.

on top of that I’m also not using the standard schedule behavior. I’m using a custom timestep schedule with image-size dependent shifting, which changes how detail and color are distributed across the denoising process. that part turned out to matter a lot more than expected for keeping color stability consistent across steps.

so when I say the difference is:

x_new = x + dt * v

I don’t just mean a simplified equation. I mean the full update path is kept clean and direct, without the extra stabilizing transforms that are baked into the default ComfyUI sampling stack, which is what I believe is causing the gradual gray drift in the first place.

proper release coming soon!!!

will post results in the comments