1. Workflow Overview

This workflow optimizes commercial-grade portraits with:

• 3x Faster Generation: Uses Nunchaku quantized models.

• Skin Enhancement: Auto-fixes flaws via W_skin.safetensors LoRA.

• Tile Processing: Splits images to avoid VRAM overload.

Core Models:

• svdq-int4-flux.1-dev: Quantized model for speed.

• W_skin.safetensors: Custom skin LoRA (weight=0.7).

• 4x_NMKD-Siax_200k: Upscales to 4K.

2. Key Nodes

Dependencies:

• Download models:

  • W_skin.safetensors → Save to models/loras/.

  • 4x_NMKD-Siax_200k.pth → Save to models/upscale_models/.

3. Workflow Groups

1. Input Image: Upload portrait (e.g., 1d21adbf...png).

2. Model Load: Load Nunchaku model and skin LoRA.

3. Tile Sampling: Process high-res images in tiles.

4. Post-Processing: Upscale and reassemble tiles.

5. Output & Compare: Save 4K results with A/B comparison.

4. Inputs & Outputs

• Inputs:

  • Image: ≥1024x1024 resolution.

  • Prompts: e.g., "fair skin, 8k photo".

• Output:

  • 4K portrait (saved to ComfyUI/output).

5. Notes

• VRAM: ≥12GB GPU (8GB with tiling).

• Debugging:

  • Missing models → Check loras and upscale_models paths.

• Optimization:

  • Set FluxGuidance=3.5 for better skin details.

  • Reduce denoise=0.4 in BasicScheduler for cleaner results.