udpate: guide use nightly vllm

docs/vllm_deploy_guide.md

@@ -39,7 +39,7 @@ We recommend installing vLLM in a fresh Python environment:
 ```bash
 uv venv
 source .venv/bin/activate
-uv pip install -U vllm
+uv pip install -U vllm --extra-index-url https://wheels.vllm.ai/nightly
 ```
 
 Run the following command to start the vLLM server. vLLM will automatically download and cache the MiniMax-M2.1 model from Hugging Face.
@@ -98,6 +98,10 @@ SAFETENSORS_FAST_GPU=1 vllm serve \
     --compilation-config "{\"cudagraph_mode\": \"PIECEWISE\"}"
 ```
 
+### Output is garbled
+
+If you encounter corrupted output when using vLLM to serve these models, you can upgrade to the nightly version (ensure it is a version after commit [cf3eacfe58fa9e745c2854782ada884a9f992cf7](https://github.com/vllm-project/vllm/commit/cf3eacfe58fa9e745c2854782ada884a9f992cf7))
+
 ## Getting Support
 
 If you encounter any issues while deploying the MiniMax model:

docs/vllm_deploy_guide_cn.md

@@ -39,7 +39,7 @@
 ```bash
 uv venv
 source .venv/bin/activate
-uv pip install -U vllm
+uv pip install -U vllm --extra-index-url https://wheels.vllm.ai/nightly
 ```
 
 运行如下命令启动 vLLM 服务器，vLLM 会自动从 Huggingface 下载并缓存 MiniMax-M2.1 模型。
@@ -106,6 +106,10 @@ SAFETENSORS_FAST_GPU=1 vllm serve \
     --compilation-config "{\"cudagraph_mode\": \"PIECEWISE\"}"
 ```
 
+### 模型输出乱码
+
+如果您在使用 vLLM 运行这些模型时遇到输出乱码，可以升级到最新版本（请至少确保版本在提交 [cf3eacfe58fa9e745c2854782ada884a9f992cf7](https://github.com/vllm-project/vllm/commit/cf3eacfe58fa9e745c2854782ada884a9f992cf7) 之后）。
+
 ## 获取支持
 
 如果在部署 MiniMax 模型过程中遇到任何问题：