Update README.md

README.md

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 <p align="center">
-  
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/63473b59e5c0717e6737b872/5DZez8C7TeFwRn3FcKDix.png)
-
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/63473b59e5c0717e6737b872/5DZez8C7TeFwRn3FcKDix.png" alt="HunyuanImage-2.1 Banner" />
 </p>
 
 <div align="center">
 
-# HunyuanImage-2.1: An Efficient Diffusion Model for High-Resolution (2K) Text-to-Image Generation​
+# **HunyuanImage-2.1**  
+### An Efficient Diffusion Model for High-Resolution (2K) Text-to-Image Generation
 
 </div>
 
 <div align="center">
-  <a href=https://github.com/Tencent-Hunyuan/HunyuanImage-2.1 target="_blank"><img src=https://img.shields.io/badge/Code-black.svg?logo=github height=22px></a>
+  <a href="https://github.com/Tencent-Hunyuan/HunyuanImage-2.1" target="_blank"><img src="https://img.shields.io/badge/Code-black.svg?logo=github" height="22px"></a>
   <a href="https://huggingface.co/spaces/tencent/HunyuanImage-2.1" target="_blank">
     <img src="https://img.shields.io/badge/Demo%20Page-blue" height="22px"></a>
-  <a href=https://huggingface.co/tencent/HunyuanImage-2.1 target="_blank"><img src=https://img.shields.io/badge/%F0%9F%A4%97%20Models-d96902.svg height=22px></a>
+  <a href="https://huggingface.co/tencent/HunyuanImage-2.1" target="_blank"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Models-d96902.svg" height="22px"></a>
   <a href="#" target="_blank"><img src="https://img.shields.io/badge/Report-Coming%20Soon-blue" height="22px"></a>
-  <a href= https://hunyuan-promptenhancer.github.io/ target="_blank"><img src=https://img.shields.io/badge/PromptEnhancer-bb8a2e.svg?logo=github height=22px></a>
-  <a href=https://x.com/TencentHunyuan target="_blank"><img src=https://img.shields.io/badge/Hunyuan-black.svg?logo=x height=22px></a>
+  <a href="https://hunyuan-promptenhancer.github.io/" target="_blank"><img src="https://img.shields.io/badge/PromptEnhancer-bb8a2e.svg?logo=github" height="22px"></a>
+  <a href="https://x.com/TencentHunyuan" target="_blank"><img src="https://img.shields.io/badge/Hunyuan-black.svg?logo=x" height="22px"></a>
 </div>
 
+---
+
+## **Performance on RTX 5090**
+> When using **HunyuanImage-2.1** with the **quantized encoder** + **quantized base model**,  
+> the VRAM usage on an **NVIDIA RTX 5090** typically ranges between **26 GB and 29 GB**,  
+> depending on resolution, batch size, and prompt complexity.
+
+---
+
+<p align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/63473b59e5c0717e6737b872/auZ_xmiKPw0QdBYUrTLn-.png" alt="Example Output 2" />
+</p>
+
+<p align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/63473b59e5c0717e6737b872/qod1zCPWjzOZSNcOWx49-.png" alt="Example Output 1" width="50%" />
+</p>
+
+
+---
+
+## **Download Quantized Model (FP8 e4m3fn)**
+[**Download hunyuanimage2.1_fp8_e4m3fn.safetensors**](https://huggingface.co/drbaph/HunyuanImage-2.1_fp8/blob/main/hunyuanimage2.1_fp8_e4m3fn.safetensors)
 
------
+---
 
-[Download fp8_e4m3fn](https://huggingface.co/drbaph/HunyuanImage-2.1_fp8/blob/main/hunyuanimage2.1_fp8_e4m3fn.safetensors)
+### **Workflow Notes**
+- **Model:** HunyuanImage-2.1  
+- **Mode:** Quantized Encoder + Quantized Base Model  
+- **VRAM Usage:** ~26GB–30GB on RTX 5090  
+- **Resolution Tested:** 2K (2048×2048)  
+- **Frameworks:** ComfyUI & Diffusers  
+- **License:** [tencent-hunyuan-community](https://github.com/Tencent-Hunyuan/HunyuanImage-2.1/blob/master/LICENSE)
+
+---
+
+<p align="center">
+  🚀 **Optimized for High-Resolution, Memory-Efficient Text-to-Image Generation**
+</p>