---
license: other
license_name: qwen-research
license_link: https://huggingface.co/Qwen/Qwen-Image-2.1/blob/main/LICENSE
language:
- en
- zh
tags:
- comfyui
- gguf
- qwen
- qwen2
- qwen3
- qwen-image
- qwen-image-2.1
- text-to-image
- image-to-image
- image-generation
- quantized
- diffusion
pipeline_tag: text-to-image
base_model: Qwen/Qwen-Image-2.1
base_model_relation: quantized
---

# Qwen-Image 2.1 GGUF (ComfyUI)

<div align="center">

[![Downloads](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fhuggingface.co%2Fapi%2Fmodels%2FAlperKTS%2FQwen-Image-2.1-GGUF&query=%24.downloads&label=Downloads&color=blue&logo=huggingface)](https://huggingface.co/AlperKTS/Qwen-Image-2.1-GGUF)
[![Likes](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fhuggingface.co%2Fapi%2Fmodels%2FAlperKTS%2FQwen-Image-2.1-GGUF&query=%24.likes&label=Likes&color=red&logo=huggingface)](https://huggingface.co/AlperKTS/Qwen-Image-2.1-GGUF)
[![ComfyUI](https://img.shields.io/badge/ComfyUI-GGUF-green.svg)](https://github.com/city96/ComfyUI-GGUF)
[![License](https://img.shields.io/badge/License-Qwen_Research-blue.svg)](https://huggingface.co/Qwen/Qwen-Image-2.1/blob/main/LICENSE)

</div>

Quantized GGUF weights of the state-of-the-art **Qwen-Image 2.1** diffusion model for **ComfyUI** using [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF).

These models allow running Qwen-Image 2.1 on consumer GPUs with significantly reduced VRAM footprint while preserving maximum visual quality, text-rendering capabilities, and composition fidelity.

---

## 📦 Quantization Versions

| File | Size | VRAM Recommended | Description |
| :--- | :--- | :--- | :--- |
| **`qwen_image_2.1_Q8_0.gguf`** | ~7.2 GB | 12GB+ | Near-lossless precision. Best quality & fidelity. |
| **`qwen_image_2.1_Q6_K.gguf`** | ~5.5 GB | 8GB - 12GB | Optimal balance of high quality and memory efficiency. |
| **`qwen_image_2.1_Q5_K_M.gguf`** | ~4.6 GB | 8GB | Fast inference, lowest VRAM consumption, excellent quality. |

*Note: The original BF16 diffusion model is ~14.2 GB.*

---

## 🚀 How to Use in ComfyUI

### 1. Install Prerequisites
Make sure you have [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) installed in your `custom_nodes` folder:
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/city96/ComfyUI-GGUF
```

### 2. Download Required Files

1. **Diffusion Model (GGUF):**
   - Download any of the `.gguf` files from this repo (e.g. `qwen_image_2.1_Q8_0.gguf`).
   - Place it in: `ComfyUI/models/diffusion_models/` (or `ComfyUI/models/unet/`)

2. **VAE:**
   - Download `qwen_image_2.1_vae_bf16.safetensors` from [Comfy-Org/Qwen-Image-2.1](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/tree/main).
   - Place it in: `ComfyUI/models/vae/`

3. **Text Encoder / CLIP:**
   - Download `qwen3vl_8b_fp8_scaled.safetensors` or `qwen3vl_8b_int8_convrot.safetensors` (or `qwen3vl_8b_bf16.safetensors`) from [Comfy-Org/Qwen-Image-2.1](https://huggingface.co/Comfy-Org/Qwen-Image-2.1/tree/main).
   - Place it in: `ComfyUI/models/text_encoders/` (or `ComfyUI/models/clip/`)
   - *Note: In ComfyUI's `CLIPLoader`, select loader type `qwen_image`.*

---

## 🎨 Workflows

Pre-configured workflows are included in the [`workflows/`](./workflows) folder:
- **`Qwen_Image_2.1_GGUF_Text_to_Image.json`**: Ready-to-run ComfyUI text-to-image workflow using `UnetLoaderGGUF`.
- **`Qwen_Image_2.1_GGUF_Image_Edit.json`**: Ready-to-run ComfyUI image-to-image / editing workflow using `UnetLoaderGGUF`.
- Drag and drop either workflow JSON directly into ComfyUI to start generating immediately.

### Key Node Configuration
- Node: **`UnetLoaderGGUF`** (from ComfyUI-GGUF)
- `unet_name`: Select `qwen_image_2.1_Q8_0.gguf` (or `Q6_K` / `Q5_K_M`)
- Connect to standard KSampler / ModelSamplingDiscrete nodes.

---

## 📜 Credits & License
- Original model created by the **Qwen Team (Alibaba)**.
- GGUF conversion & quantization by **AlperKTS**.
- Compatible with [ComfyUI-GGUF](https://github.com/city96/ComfyUI-GGUF) by [city96](https://github.com/city96).
- Licensed under the original Qwen Research License.