⚡ Illustrious Workflow as of version 18f
🛠️ 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. Adjust the settings and models to fit your needs.
All-in-One Logic: The workflow handles generation, detailing, and upscaling in one continuous pass.
If you're needing all the bells and whistles: Try checking out ComfyUI Image Workflows by Legendaer here on CivitAI.
🚀 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 RTX VSR 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 0.2 to 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.
🛠️ Other Related Info
ComfyUI version: v0.19.3
ComfyUI frontend: v.1.43.1
Custom node links for manual install:
Description
v5 changes:
Dropped ComfyUI-APG_ImYourCFGNow from the workflow.
Ran into an issue when using FaceDetailer on certain setting that would break the workflow. Performed testing using non-custom nodes with FaceDetailer and added in custom nodes one by one. APG node was found to be the cause.
Dropped sd-dynamic-thresholding.
While testing (with the same seed/prompts) on the v5 workflow with/without this, I found the results to be better without it.
You can just use your normal CFG values now (if you weren't already).
Dropped MaHiRo
It seemed to do the opposite of it's intended function for me.
Added sd-perturbed-attention
If you want to know what it does, the paper on it can be found here.
My experience so far with PAG seems to be that you should take the total of your CFG + PAG scale to equal what you would normally use for your CFG setting by itself.
Example: if you are using a sampler from CFG++SamplerSelect, then your total should equal 2. CFG 0.5 + scale 1.5 = 2.
So if you are using a normal sampler that would be something like CFG 6, then you could do something like CFG 3 + scale 3.
This is just from a non-technical standpoint and personal testing, so I could still be wrong.
Most of the groups in the workflow can be bypassed again since this workflow is not using the SET/GET nodes.
The tradeoff is oodles of noodles.