[Docs] Add RL documentation (#17663)

Co-authored-by: JD <jaedon.guo@gmail.com>
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zijiexia
2026-01-26 12:16:54 -08:00
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co-authored by JD
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@@ -61,6 +61,7 @@ Its core features include:
- **Broad Model Support**: Supports a wide range of language models (Llama, Qwen, DeepSeek, Kimi, GLM, GPT, Gemma, Mistral, etc.), embedding models (e5-mistral, gte, mcdse), reward models (Skywork), and diffusion models (WAN, Qwen-Image), with easy extensibility for adding new models. Compatible with most Hugging Face models and OpenAI APIs.
- **Extensive Hardware Support**: Runs on NVIDIA GPUs (GB200/B300/H100/A100/Spark), AMD GPUs (MI355/MI300), Intel Xeon CPUs, Google TPUs, Ascend NPUs, and more.
- **Active Community**: SGLang is open-source and supported by a vibrant community with widespread industry adoption, powering over 400,000 GPUs worldwide.
- **RL & Post-Training Backbone**: SGLang is a proven rollout backend across the world, with native RL integrations and adoption by well-known post-training frameworks such as [**AReaL**](https://github.com/inclusionAI/AReaL), [**Miles**](https://github.com/radixark/miles), [**slime**](https://github.com/THUDM/slime), [**Tunix**](https://github.com/google/tunix), [**verl**](https://github.com/volcengine/verl) and more.
## Getting Started
- [Install SGLang](https://docs.sglang.io/get_started/install.html)