<h1 id="illustrious-workflow-as-of-version-18f">⚡ Illustrious Workflow as of version 18f</h1><h2 id="purpose-and-design-philosophy">🛠️ Purpose &amp; Design Philosophy</h2>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.<ul><li>Not for Speed: This is a heavy-duty refinement tool. If you want 2-second previews, use a basic SDXL workflow.</li><li>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.</li><li>All-in-One Logic: The workflow handles generation, detailing, and upscaling in one continuous pass.</li><li>If you're needing all the bells and whistles: Try checking out <a target="_blank" rel="ugc" href="https://civarchive.com/models/1386234/comfyui-image-workflows?modelVersionId=2811282">ComfyUI Image Workflows</a> by Legendaer here on CivitAI.</li></ul><hr /><h2 id="key-features-and-2026-logic">🚀 Key Features &amp; 2026 Logic</h2><ul><li>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.</li><li>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.</li><li>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.<ul><li>Ultimate SD Upscale: Re-draws the upscaled canvas at a 0.2 to 0.35 denoise to lock in fine textures.</li></ul></li><li>Power LoRA Loader: Manage multiple Illustrious-specific LoRAs without messy wiring.</li><li>Triple Detailer Groups: 3-stage targeted refinement for faces, hands, and clothing using standard detection models.</li><li>CivitAI Meta-Sync: Images are saved with full metadata (Model, LoRAs, Sampler info) for automatic site parsing.</li></ul><hr /><h2 id="disclaimer-and-compatibility">⚠️ Disclaimer &amp; Compatibility</h2><ul><li>Install at Your Own Risk: Custom nodes can break your environment. I am not responsible for troubleshooting your specific installation.</li><li>ComfyUI Portable: Built and tested on the Portable version. Desktop app users may face additional hurdles.</li><li>The "Your Version" Factor: Your node versions and environment are 99.9% likely to differ from mine.</li><li>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.</li></ul><hr /><h2 id="support-and-boundaries">🤝 Support &amp; Boundaries</h2><ul><li>No DMs: DMs are disabled due to repeat spam. Please check the Discussions tab below; most questions have already been answered.</li><li>Modifications: You are free to hack this workflow apart. However, you are responsible for fixing it if it breaks.</li><li>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.</li></ul><h2 id="other-related-info">🛠️ Other Related Info</h2>ComfyUI version: v0.19.3ComfyUI frontend: v.1.43.1Custom node links for manual install:<a target="_blank" rel="ugc" href="https://github.com/ltdrdata/ComfyUI-Impact-Pack">ComfyUI Impact Pack</a><a target="_blank" rel="ugc" href="https://github.com/pythongosssss/ComfyUI-Custom-Scripts">ComfyUI-Custom-Scripts</a><a target="_blank" rel="ugc" href="https://github.com/rgthree/rgthree-comfy">rgthree-comfy</a><a target="_blank" rel="ugc" href="https://github.com/kijai/ComfyUI-KJNodes">ComfyUI-KJNodes</a><a target="_blank" rel="ugc" href="https://github.com/ssitu/ComfyUI_UltimateSDUpscale">ComfyUI_UltimateSDUpscale</a><a target="_blank" rel="ugc" href="https://github.com/ClownsharkBatwing/RES4LYF">RES4LYF</a><a target="_blank" rel="ugc" href="https://github.com/Jonseed/ComfyUI-Detail-Daemon">ComfyUI-Detail-Daemon</a><a target="_blank" rel="ugc" href="https://github.com/ltdrdata/ComfyUI-Inspire-Pack">ComfyUI Inspire Pack</a><a target="_blank" rel="ugc" href="https://github.com/ltdrdata/ComfyUI-Impact-Subpack">ComfyUI Impact Subpack</a><a target="_blank" rel="ugc" href="https://github.com/alexopus/ComfyUI-Image-Saver">ComfyUI Image Saver</a><a target="_blank" rel="ugc" href="https://github.com/JPS-GER/ComfyUI_JPS-Nodes">JPS Custom Nodes for ComfyUI</a><a target="_blank" rel="ugc" href="https://github.com/Goshe-nite/comfyui-gps-supplements">GPS' Supplements for ComfyUI</a><a target="_blank" rel="ugc" href="https://github.com/PixWizardry/ComfyUI-PIX_Nvidia_RTX_Deblur_Denoise">ComfyUI-PIX_Nvidia_RTX_Deblur_Denoise</a><a target="_blank" rel="ugc" href="https://github.com/regiellis/ComfyUI-EasyColorCorrector">Easy Color Corrector</a><a target="_blank" rel="ugc" href="https://github.com/evanspearman/ComfyMath">ComfyMath</a>

Not so simple (or is it?) Illustrious Workflow

This is an alternative to v11fKSampler (Inspire) replaces all of the SamplerCustomAdvanced nodes<ul><li>Previews during the upscale portion (if used) look ugly, but the output comes out properly. You can verify in the image comparer nodes.</li></ul>Makes use of Global Sampler node to control the Sampler/Scheduler across the workflow.<ul><li>Using this pretty much makes it required to use the KSampler (Inspire) nodes because the schedulers in it are not compatible with SamplerCustomAdvanced.</li><li>This also resulted in no longer needing the BasicScheduler and Impact Scheduler Adapter nodes. There is always at least one person who runs into an issue with one or both of these nodes.</li></ul><s>This version will likely not be updated since I prefer to use SamplerCustomAdvanced nodes.</s>I'm probably going to work from this going forward. I am getting results that I like when using it with Dynamic Thresholding. The USDU nodes are a bit more sensitive, but I can work with that.

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