🌊 FLUX.1-Fill-dev Quantized: Advanced Diffusion for Seamless Image Editing

📌 Overview

FLUX.1-Fill-dev Quantized represents a breakthrough in efficient diffusion models for image editing. Built on Black Forest Labs' original architecture and optimized through GGUF quantization, it delivers professional-grade inpainting and outpainting capabilities while maintaining impressive performance even on consumer hardware.

🔑 Key Features

• Optimized Performance: Multiple quantization options (Q8, Q5_K_M, Q4_K_M) to balance quality and speed

• Versatile Editing: Excels at both inpainting (filling missing areas) and outpainting (extending images beyond boundaries)

• Seamless Integration: Compatible with popular frameworks like ComfyUI and other diffusion workflows

• Memory Efficient: Reduced model size without significant quality degradation

⚡ Available Versions

• Q8 Quantization: Highest quality, larger model size (recommended for high-end GPUs)

• Q5_K_M Quantization: Balanced performance and quality

• Q4_K_M Quantization: Fastest performance, smallest size (ideal for lower-end hardware)

📁 Recommended Setup

📂 ComfyUI/
├── 📂 models/
│   ├── 📂 diffusion_models/
│   │   └── 📄 fluxfill-dev-q8.gguf (or q5km or q4km)
│   ├── 📂 text_encoders/
│   │   ├── 📄 clip_l.safetensors
│   │   └── 📄 t5xxl_fp8_e4m3fn.safetensors (fp16 or fp8 scaled)
│   ├── 📂 vae/
│   │   └── 📄 ae.safetensors

🚀 Getting Started

System Requirements

• Minimum: 8GB VRAM (with Q4_K_M)

• Recommended: 12GB+ VRAM (for Q8 version)

• Optimal: 16GB+ VRAM (for complex workflows)

Installation Steps

1. Download your preferred quantization version

2. Place the model file in your ComfyUI/models/diffusion_models/ directory

3. Download required text encoders from Hugging Face

4. Download the VAE from Hugging Face

Note: You only need to choose ONE of the T5XXL options below based on your hardware capabilities

• clip_l.safetensors - Core understanding model

• T5XXL Options (choose only one):

  • t5xxl_fp16.safetensors - Highest quality, more demanding

  • t5xxl_fp8_e4m3fn.safetensors - Balanced performance

  • t5xxl_fp8_e4m3fn_scaled.safetensors - Optimized for speed

• ae.safetensors

💎 Optimal Workflows

• 🎨 Professional Inpainting

  • FLUX.1-Fill-dev excels at seamlessly patching areas within images while maintaining perfect context awareness:

    1. Load your image into ComfyUI

    2. Create or upload a mask for the area to fill

    3. Use 20-30 steps with a sampling method like DPM++ 2M Karras

• 🏞️ Creative Outpainting

  • Extend your images beyond their original boundaries with natural continuity:

    1. Load your image into ComfyUI

    2. Use the FluxFill outpainting workflow

    3. Choose the direction(s) to extend the image

🙏 Credits

• Special thanks to Black Forest Labs for developing the original FLUX.1-Fill-dev model.

👨‍💻 Developer Information

This workflow guide was created by Abdallah Al-Swaiti:

• LinkedIn Profile

• GitHub

• Hugging Face

For additional tools and updates, check out the OllamaGemini Node: GitHub Repository

✨ Elevate Your Creative Vision ✨