⚡ Illustrious Workflow as of version 18

🛠️ Purpose & Design Philosophy

This workflow is a high-fidelity environment built for Illustrious XL. It prioritizes stability and professional texture over generation speed. It follows an "all-in-one" philosophy: configure your prompts, hit queue, and let the workflow handle the multi-stage refinement from start to finish.

Not for Speed: This is a heavy-duty refinement tool. If you want 2-second previews, use a basic SDXL workflow.
Personal Use: Built for my specific production needs. It is shared as-is for those who want a "set-and-forget" pipeline for Illustrious.
All-in-One Logic: The workflow handles generation, detailing, and upscaling in one continuous pass.

🚀 Key Features & 2026 Logic

Global Model Patching (RescaleCFG): Includes a pre-configured RescaleCFG patch (Multiplier: 0.7) applied globally. This acts as "HDR Insurance," preventing the "deep-fried" or over-saturated look common in high-CFG Illustrious runs.
Detail Daemon Sampler: Integrated to enhance structural depth. In this version, it is tuned to start at 0.4 to preserve the core Illustrious character proportions while sharpening hair and eye details.
Hybrid Upscale Strategy: * Group Bypass Switch: Easily toggle between a Pixel-only (Lanczos) path for flat anime styles and an Upscale-Model path for 2.5D/highly detailed renders.
- Ultimate SD Upscale: Re-draws the upscaled canvas at a 0.35 denoise to lock in fine textures.
Power LoRA Loader: Manage multiple Illustrious-specific LoRAs without messy wiring.
Triple Detailer Groups: 3-stage targeted refinement for faces, hands, and clothing using standard detection models.
CivitAI Meta-Sync: Images are saved with full metadata (Model, LoRAs, Sampler info) for automatic site parsing.

⚠️ Disclaimer & Compatibility

Install at Your Own Risk: Custom nodes can break your environment. I am not responsible for troubleshooting your specific installation.
ComfyUI Portable: Built and tested on the Portable version. Desktop app users may face additional hurdles.
The "Your Version" Factor: Your node versions and environment are 99.9% likely to differ from mine.
Nodes 2.0: I do not recommend using Nodes 2.0. It creates unpredictable UI behavior; I will not provide support for issues involving this feature.

🤝 Support & Boundaries

No DMs: DMs are disabled due to repeat spam. Please check the Discussions tab below; most questions have already been answered.
Modifications: You are free to hack this workflow apart. However, you are responsible for fixing it if it breaks.
Custom Requests: I do not make private workflows. If you need a custom solution, post a Bounty on CivitAI. There are many talented creators ready to help you for a fee.

Description

USDU + Laplace changes

You no longer need to do math here. Just plug in your denoise and steps in the nodes for Steps and Denoise. The math will be done in the background to use the amount of steps you entered.

Added ModelSamplingDiscrete

This used to be required for v-pred models. The reason why I added it, is because I found some documentation talking about how Laplace works well with ZSNR enabled. The toggle for ZSNR is on this node. If using ZSNR doesn't seem to affect anything, then the model you are using isn't meant to work with it.
This node will be bypassed by default. If you enable it, then you need to make sure you set the sampling setting correctly: eps for Epsilon models and v_prediction for v-pred models. If you don't know what that means, then it's best to leave this bypassed.

The default settings on the Laplace scheduler nodes on the saved workflow are what I used in the sample images.

I still haven't found much info regarding Laplace. You can even do a quick Google Search and my workflow pops up. That should tell you how little info there is.

Changed the default precision setting on the Batch Resize w/Lanczos node to bf16.

This seemed to help some people in regards to speed, though I never noticed a difference personally.

As previously mentioned:

The Laplace Scheduler is not recommended for people new to ComfyUI and/or are not comfortable with figuring out settings on your own.

If you do want to try it out, I suggest not messing with the settings on the LaplaceScheduler node other than "steps".
It's very sensitive to what you prompt in both positive and negative prompts, so prompt with caution (or go wild).

The Basic Scheduler node (which is the default) works like the same normal KSampler settings, but some people have ran into random compatibility issues with it before. It's a Comfy Core node, so it has to be something on their installs causing the conflict.

On the Basic Scheduler node: you control the Scheduler, Steps, and Denoise.

SamplerCustomAdvanced is now the only KSampler for the initial image on this workflow

Confirmed it works even with RES4LYF installed
This node is not affected by the Global Sampler node, so the sampler and scheduler have to bet set manually here.
The CFG setting is also separate here since I tend to use sa_solver with Laplace but other combos for the rest of the workflow.

The Global Seed and Global Sampler nodes will override any of the settings related to them across the workflow.

Using a sampler or scheduler not compatible with any of the nodes will result in an error.
You can bypass or delete these two nodes if you want to do these settings manually on each node.
Does not affect the sampler or scheduler settings connected to SamplerCustomAdvanced (if it is in the workflow).

CFG is tied to the “CFG” node to the left of the KSampler.

Delete this node if you want to set CFG manually on each node.

The detailers can be used for whatever you want as long as you have the detection models.

The detailer nodes used in this workflow take all detected items and do them at the same time.
You can use whatever detection model you want. You don't have to use what I use.

If you are seeing busted results in the detailers try adding something to the wildcard spec field to help guide the detailer.

Example: only one eye is detected and the detailer is turning into nightmare fuel