diff --git a/docs.json b/docs.json
index c1d08caa..45d8057a 100644
--- a/docs.json
+++ b/docs.json
@@ -123,6 +123,7 @@
                   {
                     "group": "Image",
                     "pages": [
+                      "tutorials/image/qwen/qwen-image",
                       {
                         "group": "HiDream",
                         "pages": [
@@ -672,6 +673,7 @@
                   {
                     "group": "Image",
                     "pages": [
+                      "zh-CN/tutorials/image/qwen/qwen-image",
                       {
                         "group": "HiDream",
                         "pages": [
diff --git a/images/tutorial/image/qwen/image_qwen_image-guide.jpg b/images/tutorial/image/qwen/image_qwen_image-guide.jpg
new file mode 100644
index 00000000..05090107
Binary files /dev/null and b/images/tutorial/image/qwen/image_qwen_image-guide.jpg differ
diff --git a/tutorials/image/qwen/qwen-image.mdx b/tutorials/image/qwen/qwen-image.mdx
new file mode 100644
index 00000000..49fddce7
--- /dev/null
+++ b/tutorials/image/qwen/qwen-image.mdx
@@ -0,0 +1,72 @@
+---
+title: "Qwen-Image ComfyUI Native Workflow Example"
+description: "Qwen-Image is a 20B parameter MMDiT (Multimodal Diffusion Transformer) model open-sourced under the Apache 2.0 license."
+sidebarTitle: "Qwen-Image"
+---
+
+import UpdateReminder from '/snippets/tutorials/update-reminder.mdx'
+
+
+**Qwen-Image** is the first image generation foundation model released by Alibaba's Qwen team. It's a 20B parameter MMDiT (Multimodal Diffusion Transformer) model open-sourced under the Apache 2.0 license. The model has made significant advances in **complex text rendering** and **precise image editing**, achieving high-fidelity output for multiple languages including English and Chinese.
+
+**Model Highlights**:
+- **Excellent Multilingual Text Rendering**: Supports high-precision text generation in multiple languages including English, Chinese, Korean, Japanese, maintaining font details and layout consistency
+- **Diverse Artistic Styles**: From photorealistic scenes to impressionist paintings, from anime aesthetics to minimalist design, fluidly adapting to various creative prompts
+
+**Related Links**:
+ - [GitHub](https://github.com/QwenLM/Qwen-Image)
+ - [Hugging Face](https://huggingface.co/Qwen/Qwen-Image)
+ - [ModelScope](https://modelscope.cn/models/qwen/Qwen-Image)
+
+## Qwen-Image Native Workflow Example
+
+<UpdateReminder />
+
+The models used in this document can be obtained from [Huggingface](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) or [Modelscope](https://modelscope.cn/models/Comfy-Org/Qwen-Image_ComfyUI/files)
+
+## 1. Workflow File
+
+After updating ComfyUI, you can find the workflow file in the templates, or drag the workflow below into ComfyUI to load it.
+![Qwen-image Text-to-Image Workflow](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/qwen/qwen-image.png)
+
+<a className="prose"  target='_blank'  href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image.json" style={{ display: 'inline-block', backgroundColor: '#0078D6', color: '#ffffff', padding: '10px 20px', borderRadius: '8px', borderColor: "transparent", textDecoration: 'none', fontWeight: 'bold'}}>
+    <p className="prose" style={{ margin: 0, fontSize: "0.8rem" }}>Download JSON Workflow</p>
+</a>
+## 2. Model Download
+
+You can find all the models on [Huggingface](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) or [Modelscope](https://modelscope.cn/models/Comfy-Org/Qwen-Image_ComfyUI/files)
+
+**Diffusion Model**
+
+- [qwen_image_fp8_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_fp8_e4m3fn.safetensors)
+
+**Text Encoder**
+
+- [qwen_2.5_vl_7b_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)
+
+**VAE**
+
+- [qwen_image_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors)
+
+**Model Storage Location**
+
+```
+📂 ComfyUI/
+├── 📂 models/
+│   ├── 📂 diffusion_models/
+│   │   └── qwen_image_fp8_e4m3fn.safetensors
+│   ├── 📂 vae/
+│   │   └── qwen_image_vae.safetensors
+│   └── 📂 text_encoders/
+│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
+```
+### 3. Complete the Workflow Step by Step
+
+![Step Guide](/images/tutorial/image/qwen/image_qwen_image-guide.jpg)
+
+1. Load `qwen_image_fp8_e4m3fn.safetensors` in the `Load Diffusion Model` node
+2. Load `qwen_2.5_vl_7b_fp8_scaled.safetensors` in the `Load CLIP` node  
+3. Load `qwen_image_vae.safetensors` in the `Load VAE` node
+4. Set image dimensions in the `EmptySD3LatentImage` node
+5. Enter your prompts in the `CLIP Text Encoder` (supports English, Chinese, Korean, Japanese, Italian, etc.)
+6. Click Queue or press `Ctrl+Enter` to run
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diff --git a/zh-CN/tutorials/image/qwen/qwen-image.mdx b/zh-CN/tutorials/image/qwen/qwen-image.mdx
new file mode 100644
index 00000000..5d7a6b30
--- /dev/null
+++ b/zh-CN/tutorials/image/qwen/qwen-image.mdx
@@ -0,0 +1,72 @@
+---
+title: "Qwen-Image ComfyUI原生工作流示例"
+description: "Qwen-Image 是一个拥有 20B 参数的 MMDiT（多模态扩散变换器）模型，基于 Apache 2.0 许可证开源。"
+sidebarTitle: "Qwen-Image"
+---
+
+import UpdateReminder from '/snippets/zh/tutorials/update-reminder.mdx'
+
+
+**Qwen-Image** 是阿里巴巴通义千问团队发布的首个图像生成基础模型，这是一个拥有 20B 参数的 MMDiT（多模态扩散变换器）模型，基于 Apache 2.0 许可证开源。该模型在**复杂文本渲染**和**精确图像编辑**方面取得了显著进展，无论是英语还是中文等多种语言都能实现高保真输出。
+
+**模型亮点**：
+- **卓越的多语言文本渲染**：支持英语、中文、韩语、日语等多种语言的高精度文本生成，保持字体细节和布局一致性
+- **多样化艺术风格**：从照片级真实到印象派绘画，从动漫美学到极简设计，流畅适应各种创意提示
+
+*相关链接**:
+ - [GitHub](https://github.com/QwenLM/Qwen-Image)
+ - [Hugging Face](https://huggingface.co/Qwen/Qwen-Image)
+ - [ModelScope](https://modelscope.cn/models/qwen/Qwen-Image)
+
+## Qwen-Image 原生工作流示例
+
+<UpdateReminder />
+
+本文档中使用的模型你可以在 [Huggingface](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) 获取到 [Modelscope](https://modelscope.cn/models/Comfy-Org/Qwen-Image_ComfyUI/files) 获取到
+
+## 1. 工作流文件
+
+更新 ComfyUI 后你可以从模板中找到工作流文件，或者将下面的工作流拖入 ComfyUI 中加载
+![Qwen-image 文生图工作流](https://raw.githubusercontent.com/Comfy-Org/example_workflows/main/image/qwen/qwen-image.png)
+
+<a className="prose"  target='_blank'  href="https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/templates/image_qwen_image.json" style={{ display: 'inline-block', backgroundColor: '#0078D6', color: '#ffffff', padding: '10px 20px', borderRadius: '8px', borderColor: "transparent", textDecoration: 'none', fontWeight: 'bold'}}>
+    <p className="prose" style={{ margin: 0, fontSize: "0.8rem" }}>下载 JSON 格式工作流</p>
+</a>
+## 2. 模型下载
+
+You can find all the models on [Huggingface](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/tree/main) or [Modelscope](https://modelscope.cn/models/Comfy-Org/Qwen-Image_ComfyUI/files)
+
+**Diffusion Model**
+
+- [qwen_image_fp8_e4m3fn.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/diffusion_models/qwen_image_fp8_e4m3fn.safetensors)
+
+**Text Encoder**
+
+- [qwen_2.5_vl_7b_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors)
+
+**VAE**
+
+- [qwen_image_vae.safetensors](https://huggingface.co/Comfy-Org/Qwen-Image_ComfyUI/resolve/main/split_files/vae/qwen_image_vae.safetensors)
+
+Model Storage Location
+
+```
+📂 ComfyUI/
+├── 📂 models/
+│   ├── 📂 diffusion_models/
+│   │   └── qwen_image_fp8_e4m3fn.safetensors
+│   ├── 📂 vae/
+│   │   └── qwen_image_vae.safetensors
+│   └── 📂 text_encoders/
+│       └── qwen_2.5_vl_7b_fp8_scaled.safetensors
+```
+### 3. 按步骤完成工作流
+
+![步骤图](/images/tutorial/image/qwen/image_qwen_image-guide.jpg)
+
+1. 确保 `Load Diffusion Model`节点加载了`qwen_image_fp8_e4m3fn.safetensors`
+2. 确保 `Load CLIP`节点中加载了`qwen_2.5_vl_7b_fp8_scaled.safetensors`
+3. 确保 `Load VAE`节点中加载了`qwen_image_vae.safetensors`
+4. 确保 `EmptySD3LatentImage`节点中设置好了图片的尺寸
+5. 在`CLIP Text Encoder`节点中设置好提示词，目前经过测试目前至少支持：英语、中文、韩语、日语、意大利语等
+6. 点击 `Queue` 按钮，或者使用快捷键 `Ctrl(cmd) + Enter(回车)` 来运行工作流
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