[diffusion] docs: consolidate diffusion documentation into docs (#18095)

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> Co-authored-by: JiaxinD <djx2048@gmail.com>
2026-02-11 16:55:07 -08:00
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+# SGLang Diffusion
+
+SGLang Diffusion is an inference framework for accelerated image and video generation using diffusion models. It provides an end-to-end unified pipeline with optimized kernels and an efficient scheduler loop.
+
+## Key Features
+
+- **Broad Model Support**: Wan series, FastWan series, Hunyuan, Qwen-Image, Qwen-Image-Edit, Flux, Z-Image, GLM-Image, and more
+- **Fast Inference**: Optimized kernels, efficient scheduler loop, and Cache-DiT acceleration
+- **Ease of Use**: OpenAI-compatible API, CLI, and Python SDK
+- **Multi-Platform**: NVIDIA GPUs (H100, H200, A100, B200, 4090) and AMD GPUs (MI300X, MI325X)
+
+---
+
+## Quick Start
+
+### Installation
+
+```bash
+uv pip install "sglang[diffusion]" --prerelease=allow
+```
+
+See [Installation Guide](installation.md) for more installation methods and ROCm-specific instructions.
+
+### Basic Usage
+
+Generate an image with the CLI:
+
+```bash
+sglang generate --model-path Qwen/Qwen-Image \
+    --prompt "A beautiful sunset over the mountains" \
+    --save-output
+```
+
+Or start a server with the OpenAI-compatible API:
+
+```bash
+sglang serve --model-path Qwen/Qwen-Image --port 30010
+```
+
+---
+
+## Documentation
+
+### Getting Started
+
+- **[Installation](installation.md)** - Install SGLang Diffusion via pip, uv, Docker, or from source
+- **[Compatibility Matrix](compatibility_matrix.md)** - Supported models and optimization compatibility
+
+### Usage
+
+- **[CLI Documentation](api/cli.md)** - Command-line interface for `sglang generate` and `sglang serve`
+- **[OpenAI API](api/openai_api.md)** - OpenAI-compatible API for image/video generation and LoRA management
+
+### Performance Optimization
+
+- **[Performance Overview](performance/index.md)** - Overview of all performance optimization strategies
+- **[Attention Backends](performance/attention_backends.md)** - Available attention backends (FlashAttention, SageAttention, etc.)
+- **[Caching Strategies](performance/cache/)** - Cache-DiT and TeaCache acceleration
+- **[Profiling](performance/profiling.md)** - Profiling techniques with PyTorch Profiler and Nsight Systems
+
+### Reference
+
+- **[Environment Variables](environment_variables.md)** - Configuration via environment variables
+- **[Support New Models](support_new_models.md)** - Guide for adding new diffusion models
+- **[Contributing](contributing.md)** - Contribution guidelines and commit message conventions
+- **[CI Performance](ci_perf.md)** - Performance baseline generation script
+
+---
+
+## CLI Quick Reference
+
+### Generate (one-off generation)
+
+```bash
+sglang generate --model-path <MODEL> --prompt "<PROMPT>" --save-output
+```
+
+### Serve (HTTP server)
+
+```bash
+sglang serve --model-path <MODEL> --port 30010
+```
+
+### Enable Cache-DiT acceleration
+
+```bash
+SGLANG_CACHE_DIT_ENABLED=true sglang generate --model-path <MODEL> --prompt "<PROMPT>"
+```
+
+---
+
+## References
+
+- [SGLang GitHub](https://github.com/sgl-project/sglang)
+- [Cache-DiT](https://github.com/vipshop/cache-dit)
+- [FastVideo](https://github.com/hao-ai-lab/FastVideo)
+- [xDiT](https://github.com/xdit-project/xDiT)
+- [Diffusers](https://github.com/huggingface/diffusers)