This workflow is designed to squeeze everything possible out of SDXL using a 5-pass quality refinement process. It’s easy to use, easy to read, and built for users who want the most polished SDXL output possible.Each phase adds controlled improvements to detail, clarity, and finish using res_2 samplers, Detail Daemon, FaceDetailer, HandDetailer, upscale, sharpening, and desaturation. Step-by-step preview outputs are included so you can compare every phase and see exactly where the quality gains happen.SDXL may not be the newest model on the block, but with the right workflow it can still produce beautiful, high-quality images and this setup is built to prove it. <h1 id="features">Features</h1><ul><li>5-pass SDXL refinement workflow</li><li>Res2 samplers for stronger fidelity</li><li>SageAttention support for speed</li><li>FaceDetailer</li><li>HandDetailer</li><li>Detail Daemon sampler + graph sigmas</li><li>Foolhardy upscale</li><li>Sharpening</li><li>Desaturation</li><li>Step-by-step phase previews / comparison</li></ul><h1 id="node-packs-used-in-this-workflow">Node packs used in this workflow</h1><ul><li>rgthree-comfy<ul><li>Power Lora Loader (rgthree)</li><li>Image Comparer (rgthree)</li><li>GetNode</li><li>SetNode</li></ul></li><li>ComfyUI Impact Pack<ul><li>FaceDetailer</li><li>SAMLoader</li><li>UltralyticsDetectorProvider</li></ul></li><li>ComfyUI KJNodes<ul><li>Patch Sage Attention KJ</li></ul></li><li>Detail Daemon<ul><li>DetailDaemonSamplerNode</li><li>DetailDaemonGraphSigmasNode</li></ul></li></ul><ul><li>ImageCASharpening+</li><li>ImageDesaturate+</li><li>ResizeLongestToNode</li></ul><ul><li>CheckpointLoaderSimple</li><li>CLIPTextEncode</li><li>KSampler</li><li>SamplerCustomAdvanced</li><li>VAEDecode</li><li>Upscale Model Loader</li><li>ImageUpscaleWithModel</li><li>PreviewImage</li><li>SaveImage</li></ul><ul><li>Foolhardy Remacri upscale model</li><li>Ultralytics + SAM models for FaceDetailer / HandDetailer</li><li>SageAttention for speed</li></ul><h1></h1><h1></h1><h1></h1><h1></h1><h1></h1><h1></h1>

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