diff --git a/README.md b/README.md
index e91051734..77f647551 100644
--- a/README.md
+++ b/README.md
@@ -63,7 +63,7 @@ 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.
+- **RL & Post-Training Backbone**: SGLang is a proven rollout backend used for training many frontier models, 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)
diff --git a/docs/index.rst b/docs/index.rst
index def5f5959..60f52afc6 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -16,7 +16,7 @@ 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, Miles, slime, Tunix, verl and more.
+- **RL & Post-Training Backbone**: SGLang is a proven rollout backend used for training many frontier models, with native RL integrations and adoption by well-known post-training frameworks such as AReaL, Miles, slime, Tunix, verl and more.
 
 .. toctree::
    :maxdepth: 1