ReReduxPatcher

Flux Redux is Black Forest Labs' own image-variation adapter - it encodes a reference image with SigLIP and hands that as a style/composition signal into a Flux generation, and it's genuinely good at style transfer as a result. It's also the model RES4LYF's author has publicly credited (naming Ostris's version specifically) as the backbone behind the pack's "universal style transfer" feature that spread across HiDream, Flux, Chroma, SD1.5, SDXL, SD3.5, AuraFlow, LTXV, and WAN. ReReduxPatcher patches the loaded style model - not the diffusion model - so RES4LYF's system can run its style-guide computation against it correctly.

What makes this one different from the other Re*Patcher nodes

Every other patcher in this pack (ReFluxPatcherAdvanced, ReChromaPatcherAdvanced, and the rest) takes a MODEL and hands back a patched MODEL. This one takes a STYLE_MODEL - the output of a style-model loader, i.e. Redux itself - and hands back a patched STYLE_MODEL. It's a sibling to the diffusion-model patchers conceptually (same style_dtype/enable shape, same job of getting RES4LYF's style machinery talking to a specific model correctly) but it sits at a different point in the graph: right after your style model loader, before whatever applies the style conditioning to your main generation.

The inputs and outputs that matter

• style_model (STYLE_MODEL, required) - your loaded Redux (or compatible) style model.
• style_dtype (default float64) - precision for the internal computation this patch adds. As with the diffusion-model patchers, this is a small, targeted precision setting rather than something that forces your whole pipeline to run at float64.
• enable (BOOLEAN, default true) - bypass switch, useful for A/B testing whether the patch is contributing anything without rewiring.

Output: a patched style_model, wired onward to whatever style-conditioning node consumes it downstream (typically alongside a StyleModelApply-type node or one of RES4LYF's own guide-conditioning nodes).

How to install it

Ships with RES4LYF - no separate install for individual nodes. Via ComfyUI Manager: search "RES4LYF", install, restart. Manually:

cd ComfyUI/custom_nodes
git clone https://github.com/ClownsharkBatwing/RES4LYF/
cd RES4LYF
pip install -r requirements.txt

You'll separately need Flux Redux's own weights (BFL's official release, or Ostris's variant, both work as a STYLE_MODEL input) and typically a CLIP vision encoder to feed it - this patcher assumes you already have a working Redux-based style transfer setup and slots into it.

Common issues & troubleshooting

You've never used Redux before and aren't sure this applies to you. If your workflow doesn't have a style model loader in it at all, this node has nothing to patch - it's specifically for people already using Flux Redux (or a compatible style model) for image variation or style transfer, not a general-purpose tool.

No visible change when toggling enable. Confirm you're actually feeding the patched style_model output into your style-conditioning path and not accidentally still wired to the unpatched original - it's an easy mistake to leave the old connection in place after inserting this node.

Style transfer results look muddy or washed out. That's more often a Redux/SigLIP conditioning-strength issue than something this patcher controls - check the strength setting on whatever node applies the style conditioning before adjusting style_dtype here.

Confusing it with the diffusion-model patchers. This node will not accept a MODEL input, and the diffusion-model patchers won't accept a STYLE_MODEL - they're not interchangeable, even in the same style-transfer workflow. Use the right one for the right slot in the graph.