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54 lines
2.5 KiB
Markdown
54 lines
2.5 KiB
Markdown
# SGLang Diffusion
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SGLang Diffusion is a high-performance inference framework for image and video generation. It provides native SGLang pipelines, diffusers backend support, an OpenAI-compatible server, and an optimized kernel stack built on both precompiled `sgl-kernel` operators and JIT kernels for key inference paths.
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## Key Features
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- Broad model support across Wan, Hunyuan, Cosmos3, Qwen-Image, FLUX, Z-Image, GLM-Image, and more
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- Fast inference with `sgl-kernel`, JIT kernels, scheduler improvements, and caching acceleration
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- Multiple interfaces: `sglang generate`, `sglang serve`, and an OpenAI-compatible API
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- Multi-platform support for NVIDIA, AMD, Intel XPU, Ascend, Apple Silicon, and Moore Threads
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## Quick Start
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```bash
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uv pip install "sglang[diffusion]" --prerelease=allow
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```
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```bash
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sglang generate --model-path Qwen/Qwen-Image \
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--prompt "A beautiful sunset over the mountains" \
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--save-output
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```
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```bash
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sglang serve --model-path Qwen/Qwen-Image --port 30010
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```
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## Start Here
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- [Installation](installation.md): install SGLang Diffusion and platform dependencies
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- [Compatibility Matrix](compatibility_matrix.md): check model, optimization, and component override support
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- [CLI](api/cli.md): run one-off generation jobs or launch a persistent server
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- [OpenAI-Compatible API](api/openai_api.md): send image and video requests to the HTTP server
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- [Attention Backends](performance/attention_backends.md): choose the best backend for your model and hardware
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- [Caching Acceleration](performance/cache/index.md): use Cache-DiT or TeaCache to reduce denoising cost
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- [Quantization](quantization.md): load quantized transformer checkpoints
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- [Contributing](contributing.md): contribution workflow, adding new models, and CI perf baselines
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## Additional Documentation
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- [Post-Processing](api/post_processing.md): frame interpolation and upscaling
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- [Performance Overview](performance/index.md): overview of attention, caching, and profiling
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- [Environment Variables](environment_variables.md): platform, caching, storage, and debugging configuration
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- [Support New Models](support_new_models.md): implementation guide for new diffusion pipelines
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- [CI Performance](ci_perf.md): performance baseline generation
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## References
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- [SGLang GitHub](https://github.com/sgl-project/sglang)
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- [Cache-DiT](https://github.com/vipshop/cache-dit)
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- [FastVideo](https://github.com/hao-ai-lab/FastVideo)
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- [xDiT](https://github.com/xdit-project/xDiT)
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- [Diffusers](https://github.com/huggingface/diffusers)
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