From e316bcacb1a0caf4c2aa63e50a88c5ca2de4718c Mon Sep 17 00:00:00 2001
From: Mick <mickjagger19@icloud.com>
Date: Sat, 8 Nov 2025 01:04:44 +0800
Subject: [PATCH] update multimodal_gen readme (#12825)

Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>
---
 python/sglang/multimodal_gen/README.md       | 27 ++++++++------------
 python/sglang/multimodal_gen/docs/install.md |  6 ++---
 2 files changed, 13 insertions(+), 20 deletions(-)

diff --git a/python/sglang/multimodal_gen/README.md b/python/sglang/multimodal_gen/README.md
index 96880bd33..8b2655628 100644
--- a/python/sglang/multimodal_gen/README.md
+++ b/python/sglang/multimodal_gen/README.md
@@ -1,25 +1,18 @@
-<div align="center">
-<img src=assets/logos/logo.svg width="30%"/>
+<div align="center"  style="display:block; margin:auto;">
+<img src=https://github.com/lm-sys/lm-sys.github.io/releases/download/test/sgl-diffusion-logo.png width="80%"/>
 </div>
 
 **sgl-diffusion is an inference framework for accelerated image/video generation.**
 
-sgl-diffusion features an end-to-end unified pipeline for accelerating diffusion models. It is designed to be modular and extensible, allowing users to easily add new optimizations and techniques.
+SGLang-Diffusion features an end-to-end unified pipeline for accelerating diffusion models. It is designed to be modular and extensible, allowing users to easily add new models and optimizations.
 
 ## Key Features
 
-sgl-diffusion has the following features:
-
-- State-of-the-art performance optimizations for inference
-    - [Video Sparse Attention](https://arxiv.org/pdf/2505.13389)
-    - [Sliding Tile Attention](https://arxiv.org/pdf/2502.04507)
-    - [TeaCache](https://arxiv.org/pdf/2411.19108)
-    - [Sage Attention](https://arxiv.org/abs/2410.02367)
-    - USP
-    - CFG Parallel
-- Diverse hardware and OS support
-    - Supported hardware: H100, H200, A100, B200, 4090
-    - Supported OS: Linux, Windows, MacOS
+SGLang Diffusion has the following features:
+  - Broad model support: Wan series, FastWan series, Hunyuan, Qwen-Image, Qwen-Image-Edit, Flux
+  - Fast inference speed: enpowered by highly optimized kernel from sgl-kernel and efficient scheduler loop
+  - Ease of use: OpenAI-compatible api, CLI, and python sdk support
+  - Diverse hardware support: H100, H200, A100, B200, 4090
 
 ## Getting Started
 
@@ -27,7 +20,7 @@ sgl-diffusion has the following features:
 uv pip install 'sglang[diffusion]' --prerelease=allow
 ```
 
-For more information, check the [docs](https://github.com/sgl-project/sglang/tree/main/python/sglang/multimodal_gen/docs/install.md).
+For more installation methods (e.g. pypi, uv, docker), check the [docs](https://github.com/sgl-project/sglang/tree/main/python/sglang/multimodal_gen/docs/install.md).
 
 
 ## Inference
@@ -68,7 +61,7 @@ sglang generate --model-path Wan-AI/Wan2.1-T2V-1.3B-Diffusers \
     --save-output
 ```
 
-For more information, check the [docs](https://github.com/sgl-project/sglang/tree/main/python/sglang/multimodal_gen/docs/cli.md).
+For more usage examples (e.g. OpenAI compatible API, server mode), check the [docs](https://github.com/sgl-project/sglang/tree/main/python/sglang/multimodal_gen/docs/cli.md).
 
 ## Contributing
 
diff --git a/python/sglang/multimodal_gen/docs/install.md b/python/sglang/multimodal_gen/docs/install.md
index 46aaec4f7..c8c0f45de 100644
--- a/python/sglang/multimodal_gen/docs/install.md
+++ b/python/sglang/multimodal_gen/docs/install.md
@@ -11,7 +11,7 @@ It is recommended to use uv for a faster installation:
 ```bash
 pip install --upgrade pip
 pip install uv
-uv pip install 'sglang[diffusion]' --prerelease=allow
+uv pip install "sglang[diffusion]" --prerelease=allow
 ```
 
 ## Method 2: From source
@@ -23,10 +23,10 @@ cd sglang
 
 # Install the Python packages
 pip install --upgrade pip
-pip install -e "python/.[diffusion]"
+pip install -e "python[diffusion]"
 
 # With uv
-uv pip install --prerelease=allow  -e "python/.[diffusion]"
+uv pip install -e "python[diffusion]" --prerelease=allow
 ```
 
 ## Method 3: Using Docker