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The FLUX.1 [dev] Model is licensed by Black Forest Labs. Inc. under the FLUX.1 [dev] Non-Commercial License. Copyright Black Forest Labs. Inc.
IN NO EVENT SHALL BLACK FOREST LABS, INC. BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.
# 🚀 SD Ultimate Upscaler with Nunchaku Setup Guide
This guide covers the complete setup for the enhanced SD Ultimate Upscaler workflow with Nunchaku, including Florence2 automatic captioning for optimal results.
## 🔧 Prerequisites
- ComfyUI installed and working
- NVIDIA GPU with 8GB+ VRAM (12GB+ recommended)
- CUDA 12.6+ (12.9 recommended)
## 📦 Custom Nodes Installation
### Required Nodes
- [ComfyUI_UltimateSDUpscale](https://github.com/ssitu/ComfyUI_UltimateSDUpscale)
Enables tiled upscaling for high-resolution images
- [ComfyUI-nunchaku](https://github.com/nunchaku-tech/ComfyUI-nunchaku)
Quantized Flux models for blazing speed
- [ComfyUI-Florence2](https://github.com/spacepxl/ComfyUI-Florence2)
Automatic image captioning for better upscaling prompts
- [rgthree-comfy](https://github.com/rgthree/rgthree-comfy)
Image comparison tools
- [was-node-suite-comfyui](https://github.com/WASasquatch/was-node-suite-comfyui)
Advanced save options
### Installation
- Clone all repositories into ComfyUI/custom_nodes/
- Restart ComfyUI after installation
## 📁 File Structure & Model Downloads
### Directory Layout
```
ComfyUI/
├── models/
│ ├── checkpoints/ # Nunchaku models
│ ├── clip/ # Text encoders
│ ├── vae/ # VAE models
│ ├── upscale_models/ # AI upscalers
│ └── loras/ # LoRA models (optional)
```
### 🤖 Nunchaku Models
Source: mit-han-lab/nunchaku-flux.1-dev
- RTX 20s/30s/40s: svdq-int4_r32-flux.1-kontext-dev.safetensors
- RTX 50 series: svdq-fp4_r32-flux.1-kontext-dev.safetensors
- Place in: models/checkpoints/
### 📝 Text Encoders
Source: comfyanonymous/flux_text_encoders
- t5xxl_fp16.safetensors (~9.79GB)
- ViT-L-14-TEXT-detail-improved-hiT-GmP-TE-only-HF.safetensors (~246MB)
- Place in: models/clip/
### 🎨 VAE Model
Source: black-forest-labs/FLUX.1-schnell
- flux_vae.safetensors (~335MB)
- Place in: models/vae/
### 🔍 Upscaler Models
Recommended Options:
- 4x_NMKD-Siax_200k.pth
- 4x-UltraSharp.pth
- RealESRGAN_x4plus.pth
- Place in: models/upscale_models/
### 🎯 LoRA Models (Optional)
- Photorealistic LoRAs for enhanced quality
- Place in: models/loras/Flux/
## 🧠 Florence2 Setup
### Model Download
Florence2 will auto-download the first time you run the workflow:
- Model: microsoft/Florence-2-large
- Size: ~1.5GB
- Purpose: Automatic image analysis and prompt generation
## 📋 Complete Workflow Features
### 🎨 Workflow Components
| Node | Purpose | Key Settings |
|------|---------|--------------|
| LoadImage | Input your image | Support for various formats |
| Florence2 | Auto-generate prompts | Analyzes image content automatically |
| NunchakuFluxDiTLoader | Load quantized model | INT4/FP4 variants available |
| NunchakuFluxLoraLoader | Apply LoRA enhancements | Optional for style improvement |
| UltimateSDUpscale | Main upscaling engine | Tiled processing with seam fixing |
| Image Comparer | Before/after comparison | Side-by-side visual comparison |
## ⚙️ Ultimate SD Upscaler Settings (From Actual Workflow)
### 🎯 Current Workflow Settings
| Parameter | Current Value | Purpose | Alternative Options |
|-----------|---------------|---------|-------------------|
| upscale_by | 2.0 | Upscaling factor | 4.0, 6.0, 8.0 for higher scaling |
| steps | 20 | Quality steps | 12-16 (faster), 26+ (max quality) |
| cfg | 1.0 | Must stay 1.0 | Never change for Flux models |
| denoise | 0.1 | Conservative enhancement | 0.15-0.30 for more changes |
| sampler | "euler" | Sampling method | dpmpp_2m, dpmpp_sde alternatives |
| scheduler | "normal" | Noise scheduling | karras, exponential options |
### 🧩 Tile Processing Settings
| Parameter | Current Value | Purpose | VRAM Optimization |
|-----------|---------------|---------|-------------------|
| tile_width/height | 1024 | Processing chunks | 768 (8-10GB), 512 (6-8GB) |
| mask_blur | 8 | Blend tile edges | 12-16 for softer blending |
| tile_padding | 32 | Tile overlap | 48-64 for better seams |
### 🔧 Seam Fixing Settings
| Parameter | Current Value | Purpose | When to Adjust |
|-----------|---------------|---------|----------------|
| seam_fix_mode | "Band Pass" | Fix tile boundaries | "None" for speed, "Half Tile" alternative |
| seam_fix_denoise | 1.0 | Seam blending strength | Lower if artifacts appear |
| seam_fix_width | 64 | Seam processing width | 32-128 based on image complexity |
| seam_fix_padding | 16 | Seam overlap area | Increase for complex images |
## 🎨 Florence2 Auto-Prompting
### How It Works
1. Automatic Analysis: Florence2 analyzes your input image
2. Caption Generation: Creates detailed description
3. Prompt Enhancement: Uses description for better upscaling
4. Manual Override: You can still edit the generated prompt
### Benefits
- Better Results: AI understands your image content
- Consistency: Maintains image characteristics during upscaling
- Time Saving: No need to manually describe images
- Accuracy: Preserves important visual elements
## 🚦 Optimization Presets
### ⚡ Speed Preset (Quick Preview)
```json
{
"upscale_by": 2.0,
"steps": 12,
"denoise": 0.1,
"seam_fix_mode": "None"
}
```
### ⚖️ Balanced Preset (Current Workflow)
```json
{
"upscale_by": 2.0,
"steps": 20,
"denoise": 0.1,
"seam_fix_mode": "Band Pass"
}
```
### 💎 Quality Preset (Maximum Detail)
```json
{
"upscale_by": 4.0,
"steps": 26,
"denoise": 0.2,
"seam_fix_mode": "Band Pass"
}
```
### 🔋 Low VRAM Preset (8GB GPUs)
```json
{
"tile_width": 768,
"tile_height": 768,
"steps": 16,
"seam_fix_mode": "None"
}
```
## 📱 Using the Workflow
### Step-by-Step Process
1. Load Image: Drop your image into the LoadImage node
2. Auto-Analysis: Florence2 automatically describes the image
3. Review Prompt: Check the generated caption in ShowText node
4. Adjust Settings: Modify upscaling parameters if needed
5. Run Workflow: Execute the complete pipeline
6. Compare Results: Use Image Comparer to see before/after
7. Save Output: Images automatically saved with timestamps
### 🎯 Prompt Customization
The workflow uses automatic prompting, but you can enhance it:
For Photos:
```
[Florence2 caption] + highly detailed, sharp focus, professional photography, enhanced details
```
For Art:
```
[Florence2 caption] + vibrant colors, sharp lines, professional quality, enhanced details
```
## 🔧 Troubleshooting
### 💥 Memory Issues
- Reduce tile size to 768 or 512
- Lower steps to 12-16
- Disable seam fixing temporarily
- Use smaller upscale factor (2x instead of 4x)
### 🧩 Visible Seams
- Keep "Band Pass" seam fixing enabled
- Increase tile_padding to 48-64
- Increase mask_blur to 12-16
- Check seam_fix_width is adequate (64-128)
### 🐌 Slow Performance
- Reduce steps to 12-16
- Set seam_fix_mode to "None"
- Use 2x upscaling instead of 4x+
- Increase tile size if VRAM allows
### 🎭 Florence2 Issues
- First run takes longer (model download)
- Restart ComfyUI if Florence2 fails to load
- Check internet connection for initial download
## ⏱️ Performance Benchmarks
| GPU | VRAM | Settings | Processing Time |
|-----|------|----------|-----------------|
| RTX 4090 | 24GB | 2x upscale, 1024px tiles, 20 steps | 15-30s |
| RTX 4080 | 16GB | 2x upscale, 1024px tiles, 16 steps | 25-45s |
| RTX 3080 | 10GB | 2x upscale, 768px tiles, 16 steps | 45-75s |
| RTX 3070 | 8GB | 2x upscale, 768px tiles, 12 steps | 60-90s |
## 🎁 Workflow Advantages
### 🚀 Speed Benefits
- Nunchaku quantization: 3-5x faster than standard Flux
- Smart tiling: Efficient memory usage
- LoRA integration: Enhanced quality without speed loss
### 🎯 Quality Features
- Florence2 analysis: Intelligent prompt generation
- Seam fixing: Professional tile blending
- Comparison tools: Easy before/after evaluation
- Flexible scaling: 2x to 8x upscaling options
### 🛠️ User Experience
- Automatic workflow: Minimal manual input required
- Visual feedback: Image comparison built-in
- Organized output: Timestamp-based file naming
- Memory efficient: Works on consumer GPUs
***
🎯 This enhanced workflow combines Nunchaku's speed, Florence2's intelligence, and Ultimate SD Upscaler's quality for professional results with minimal setup