chore: bump v0.5.1.post3 (#9716)

benchmark/deepseek_v3/README.md

@@ -33,7 +33,7 @@ Add [performance optimization options](#performance-optimization-options) as nee
 
 ```bash
 # Installation
-pip install "sglang[all]>=0.5.1.post2"
+pip install "sglang[all]>=0.5.1.post3"
 
 # Launch
 python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3 --tp 8 --trust-remote-code

docker/Dockerfile

@@ -85,10 +85,10 @@ RUN python3 -m pip install --no-cache-dir --upgrade pip setuptools wheel html5li
  && python3 -m pip install --no-cache-dir nvidia-nccl-cu12==2.27.6 --force-reinstall --no-deps \
  && python3 -m flashinfer --download-cubin \
  && if [ "$CUDA_VERSION" = "12.8.1" ]; then \
-      python3 -m pip install --no-cache-dir https://github.com/sgl-project/whl/releases/download/v0.3.5/sgl_kernel-0.3.5+cu128-cp310-abi3-manylinux2014_x86_64.whl --force-reinstall --no-deps ; \
+      python3 -m pip install --no-cache-dir https://github.com/sgl-project/whl/releases/download/v0.3.7/sgl_kernel-0.3.7+cu128-cp310-abi3-manylinux2014_x86_64.whl --force-reinstall --no-deps ; \
     fi \
  && if [ "$CUDA_VERSION" = "12.9.1" ]; then \
-      python3 -m pip install --no-cache-dir https://github.com/sgl-project/whl/releases/download/v0.3.5/sgl_kernel-0.3.5+cu129-cp310-abi3-manylinux2014_x86_64.whl --force-reinstall --no-deps ; \
+      python3 -m pip install --no-cache-dir https://github.com/sgl-project/whl/releases/download/v0.3.7/sgl_kernel-0.3.7+cu129-cp310-abi3-manylinux2014_x86_64.whl --force-reinstall --no-deps ; \
     fi
 
 # Download source files

docs/get_started/install.md

@@ -12,7 +12,7 @@ It is recommended to use uv for faster installation:
 ```bash
 pip install --upgrade pip
 pip install uv
-uv pip install "sglang[all]>=0.5.1.post2"
+uv pip install "sglang[all]>=0.5.1.post3"
 ```
 
 **Quick fixes to common problems**
@@ -24,7 +24,7 @@ uv pip install "sglang[all]>=0.5.1.post2"
 
 ```bash
 # Use the last release branch
-git clone -b v0.5.1.post2 https://github.com/sgl-project/sglang.git
+git clone -b v0.5.1.post3 https://github.com/sgl-project/sglang.git
 cd sglang
 
 # Install the python packages

docs/platforms/amd_gpu.md

@@ -44,7 +44,7 @@ You can install SGLang using one of the methods below.
 
 ```bash
 # Use the last release branch
-git clone -b v0.5.1.post2 https://github.com/sgl-project/sglang.git
+git clone -b v0.5.1.post3 https://github.com/sgl-project/sglang.git
 cd sglang
 
 # Compile sgl-kernel

docs/platforms/ascend_npu.md

@@ -99,7 +99,7 @@ We are also providing a DeepEP-compatible Library as a drop-in replacement of de
 
 ```shell
 # Use the last release branch
-git clone -b v0.5.1.post2 https://github.com/sgl-project/sglang.git
+git clone -b v0.5.1.post3 https://github.com/sgl-project/sglang.git
 cd sglang
 
 pip install --upgrade pip

python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "sglang"
-version = "0.5.1.post2"
+version = "0.5.1.post3"
 description = "SGLang is yet another fast serving framework for large language models and vision language models."
 readme = "README.md"
 requires-python = ">=3.10"

python/sglang/version.py

-__version__ = "0.5.1.post2"
+__version__ = "0.5.1.post3"