Extremely Simplified SDXL Workflow
A clean, no-nonsense SDXL workflow built for people who want results without fighting their node graph. Whether you are brand new to ComfyUI or just tired of bloated workflows, this gets you generating fast. Everything that matters is surfaced in APP Mode - prompts, model, sampler settings, resolution, and LoRAs. Everything else stays out of your way.
Who Is This For?
- ComfyUI beginners who want a solid starting point without being overwhelmed
- No-nonsense users who just want to hit generate and get a good image
- Low VRAM users - aggressive GPU memory cleanup nodes are placed throughout the workflow to keep things stable
- If you have ever opened a "simple" workflow and found 200 nodes staring back at you, this is the antidote
VRAM Requirements
| VRAM | Experience |
|---|---|
| 8 GB | Suitable - cleanup nodes help keep it stable |
| 12 GB | Recommended sweet spot |
| 16 GB+ | Smooth, no compromises |
The workflow uses dedicated VRAM cleanup nodes between passes so even lower-end cards can get through the full two-pass pipeline without running out of memory.
What's Included
- Two-pass generation with a built-in hires fix (first pass + upscale/refine)
- rgthree KSampler Config - set steps, CFG, sampler, and scheduler once, applies to both passes automatically
- Lora Loader Stack with 4 LoRA slots
- SAM + bbox detector for the second pass (automatic subject detection and detailing)
- Resolution Selector with proper SDXL aspect ratios and megapixel scaling built in
- CLIPSetLastLayer at -2 for cleaner conditioning
- GPU memory cleanup nodes between passes so VRAM does not get eaten alive
- You only see the final result - the first pass preview is intentional and hidden to keep things clean
- The detailers come pre-tuned with balanced settings that should work well for the vast majority of users. If you find the results are not quite to your liking, you will need to switch to workflow mode and adjust the detailer nodes manually - that said, the defaults I chose should be more than sufficient for 90% of use cases.
The Work Behind This
This workflow went through nearly 4 hours of testing, tweaking, and iteration to find the right balance between simplicity and output quality. Every node placement, every cleanup point, and every default setting was chosen deliberately. The goal was to build something that a beginner can pick up instantly but that does not cut corners on what matters.
Required Custom Nodes
Install these via ComfyUI Manager before loading the workflow:
- rgthree-comfy
- ComfyUI Easy Use
- ComfyUI Impact Pack
Required Models
bbox Detector (for the detailer/second pass)
The workflow uses Eyeful_v2-Paired.pt as the default bbox detector. This is NOT included with Impact Pack by default.
Download it here:
👉 Eyeful_v2_paired
Installation:
1. Download Eyeful_v2-Paired.pt (or any other .pt bbox model you prefer)
2. Place it in: ComfyUI/models/ultralytics/bbox/
3. Create the folder if it does not exist
4. Restart ComfyUI - it will appear in the model dropdown automatically
> You can swap it for any other bbox model from the adetailer collection such as face_yolov8m.pt or hand_yolov8s.pt - same install location.
Default Settings
| Setting | Value |
|---|---|
| First Pass Steps | 30 |
| Hires Fix Steps | 15 |
| CFG | 4.5 |
| Sampler | Euler |
| Scheduler | Simple |
| Resolution | 1344x768 (16:9 @ 1MP) |
Change any of it from the Linear Mode panel without touching the graph.
Designed for people who know what they want to generate, not people who want to spend 2 hours wiring nodes.
