diff --git a/docs/developer_guide/bench_serving.md b/docs/developer_guide/bench_serving.md
index b0a746de9..bc13765d0 100644
--- a/docs/developer_guide/bench_serving.md
+++ b/docs/developer_guide/bench_serving.md
@@ -21,7 +21,7 @@ If `--base-url` is provided, requests are sent to it. Otherwise, `--host` and `-
 
 ### Prerequisites
 
-- Python 3.8+
+- Python 3.10+
 - Dependencies typically used by this script: `aiohttp`, `numpy`, `requests`, `tqdm`, `transformers`, and for some datasets `datasets`, `pillow`, `pybase64`. Install as needed.
 - An inference server running and reachable via the endpoints above
 - If your server requires authentication, set environment variable `OPENAI_API_KEY` (used as `Authorization: Bearer <key>`)
diff --git a/docs_new/docs/developer_guide/bench_serving.mdx b/docs_new/docs/developer_guide/bench_serving.mdx
index e02a0ff37..b77097808 100644
--- a/docs_new/docs/developer_guide/bench_serving.mdx
+++ b/docs_new/docs/developer_guide/bench_serving.mdx
@@ -24,7 +24,7 @@ If `--base-url` is provided, requests are sent to it. Otherwise, `--host` and `-
 
 ### Prerequisites
 
-- Python 3.8+
+- Python 3.10+
 - Dependencies typically used by this script: `aiohttp`, `numpy`, `requests`, `tqdm`, `transformers`, and for some datasets `datasets`, `pillow`, `pybase64`. Install as needed.
 - An inference server running and reachable via the endpoints above
 - If your server requires authentication, set environment variable `OPENAI_API_KEY` (used as `Authorization: Bearer <key>`)
diff --git a/docs_new/docs/get-started/install.mdx b/docs_new/docs/get-started/install.mdx
index 5199c865d..ad2d801af 100644
--- a/docs_new/docs/get-started/install.mdx
+++ b/docs_new/docs/get-started/install.mdx
@@ -11,6 +11,10 @@ You can install SGLang using one of the methods below.
 This page primarily applies to common NVIDIA GPU platforms.
 For other or newer platforms, please refer to the dedicated pages for [AMD GPUs](../hardware-platforms/amd_gpu), [Intel Xeon CPUs](../hardware-platforms/cpu_server), [Google TPU](../hardware-platforms/tpu), [NVIDIA DGX Spark](https://lmsys.org/blog/2025-11-03-gpt-oss-on-nvidia-dgx-spark/), [NVIDIA Jetson](../hardware-platforms/nvidia_jetson), [Ascend NPUs](../hardware-platforms/ascend-npus/ascend_npu), and [Intel XPU](../hardware-platforms/xpu).
 
+<Note>
+Prerequisites: Python 3.10 or higher.
+</Note>
+
 ## Method 1: With pip or uv
 
 It is recommended to use uv for faster installation:
diff --git a/docs_new/docs/get-started/quickstart.mdx b/docs_new/docs/get-started/quickstart.mdx
index 706e389b6..37bc0564d 100644
--- a/docs_new/docs/get-started/quickstart.mdx
+++ b/docs_new/docs/get-started/quickstart.mdx
@@ -17,7 +17,7 @@ By the end, you'll have a working SGLang server responding to your prompts.
 
 ## Prerequisites
 
-- **Python**: 3.9 or higher
+- **Python**: 3.10 or higher
 - **GPU**: NVIDIA GPU with CUDA support (sm75 and above, e.g., T4, A10, A100, L4, L40S, H100)
 - **OS**: Linux (recommended)