Qwen image and Edit 2509 GGUF (Beginner Friendly)

TL;DR: This is a lightweight ComfyUI workflow designed to run Qwen Image on low to mid-end hardware.

It uses GGUF quantized models and optional Lightning LoRAs to drastically reduce VRAM usage while keeping image quality high.

✔ Tested on 12GB VRAM (Q8)
✔ Tested on 4GB VRAM (Q4_K_S)
✔ Supports both image generation and image editing
✔ Optimized for stability, speed, and low memory usage

Model links

You can find all the models on [QuantStack/Qwen-Image-Edit-2509-GGUF]( and [QuantStack/Qwen-Image-GGUF]( model

- Choose your quant from the links above

LoRA

- [Qwen-Image-Lightning-4steps-V2.0.safetensors]( [Qwen-Image-Lightning-8steps-V2.0.safetensors]( encoder

- [qwen_2.5_vl_7b_fp8_scaled.safetensors]( [qwen_image_vae.safetensors]( Storage Location

```

📂 ComfyUI/

├── 📂 models/

│ ├── 📂 diffusion_models/

│ │ └── Qwen-Image-Edit-2509-Q5_0.gguf

│ ├── 📂 loras/

│ │ └── Qwen-Image-Lightning-4steps-V2.0.safetensors

│ │ └── Qwen-Image-Lightning-8steps-V2.0.safetensors

│ ├── 📂 vae/

│ │ └── qwen_image_vae.safetensors

│ └── 📂 text_encoders/

│ └── qwen_2.5_vl_7b_fp8_scaled.safetensors

```

Custom Nodes

- [Kijay Nodes]( mode: activate all nodes except the image uploads youre not using and connect the latent to the k sampler.

-Image mode: Connect the emptylatent node to the k sampler

If you have any questions feel free to ask check out my youtube channel if you want to see more :) :