diff --git a/docker/Dockerfile.rocm b/docker/Dockerfile.rocm
index 8b5a3992d40..ca7625f7db9 100644
--- a/docker/Dockerfile.rocm
+++ b/docker/Dockerfile.rocm
@@ -1,5 +1,5 @@
 # Usage (to build SGLang ROCm docker image):
-#   docker build --build-arg SGL_BRANCH=v0.4.5 -t v0.4.5-rocm630 -f Dockerfile.rocm .
+#   docker build --build-arg SGL_BRANCH=v0.4.5.post1 -t v0.4.5.post1-rocm630 -f Dockerfile.rocm .
 
 # default base image
 ARG BASE_IMAGE="rocm/sgl-dev:vllm20250114"
diff --git a/docs/developer/setup_github_runner.md b/docs/developer/setup_github_runner.md
index eefe2dc6c20..cd852f3ea3b 100644
--- a/docs/developer/setup_github_runner.md
+++ b/docs/developer/setup_github_runner.md
@@ -11,9 +11,9 @@ docker pull nvidia/cuda:12.1.1-devel-ubuntu22.04
 # Nvidia
 docker run --shm-size 128g -it -v /tmp/huggingface:/hf_home --gpus all nvidia/cuda:12.1.1-devel-ubuntu22.04 /bin/bash
 # AMD
-docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.5-rocm630 /bin/bash
+docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.5.post1-rocm630 /bin/bash
 # AMD just the last 2 GPUs
-docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.5-rocm630 /bin/bash
+docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.5.post1-rocm630 /bin/bash
 ```
 
 ### Step 2: Configure the runner by `config.sh`
diff --git a/docs/start/install.md b/docs/start/install.md
index fb3b9f1001d..b5a40ee3a32 100644
--- a/docs/start/install.md
+++ b/docs/start/install.md
@@ -11,7 +11,7 @@ It is recommended to use uv to install the dependencies for faster installation:
 ```bash
 pip install --upgrade pip
 pip install uv
-uv pip install "sglang[all]>=0.4.5" --find-links https://flashinfer.ai/whl/cu124/torch2.5/flashinfer-python
+uv pip install "sglang[all]>=0.4.5.post1" --find-links https://flashinfer.ai/whl/cu124/torch2.5/flashinfer-python
 ```
 
 **Quick Fixes to Common Problems**
@@ -29,7 +29,7 @@ uv pip install "sglang[all]>=0.4.5" --find-links https://flashinfer.ai/whl/cu124
 
 ```bash
 # Use the last release branch
-git clone -b v0.4.5 https://github.com/sgl-project/sglang.git
+git clone -b v0.4.5.post1 https://github.com/sgl-project/sglang.git
 cd sglang
 
 pip install --upgrade pip
@@ -44,7 +44,7 @@ Note: For AMD ROCm system with Instinct/MI GPUs, do following instead:
 
 ```bash
 # Use the last release branch
-git clone -b v0.4.5 https://github.com/sgl-project/sglang.git
+git clone -b v0.4.5.post1 https://github.com/sgl-project/sglang.git
 cd sglang
 
 pip install --upgrade pip
@@ -73,7 +73,7 @@ docker run --gpus all \
 Note: For AMD ROCm system with Instinct/MI GPUs, it is recommended to use `docker/Dockerfile.rocm` to build images, example and usage as below:
 
 ```bash
-docker build --build-arg SGL_BRANCH=v0.4.5 -t v0.4.5-rocm630 -f Dockerfile.rocm .
+docker build --build-arg SGL_BRANCH=v0.4.5.post1 -t v0.4.5.post1-rocm630 -f Dockerfile.rocm .
 
 alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/dri --ipc=host \
     --shm-size 16G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
@@ -82,11 +82,11 @@ alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/d
 drun -p 30000:30000 \
     -v ~/.cache/huggingface:/root/.cache/huggingface \
     --env "HF_TOKEN=<secret>" \
-    v0.4.5-rocm630 \
+    v0.4.5.post1-rocm630 \
     python3 -m sglang.launch_server --model-path meta-llama/Llama-3.1-8B-Instruct --host 0.0.0.0 --port 30000
 
 # Till flashinfer backend available, --attention-backend triton --sampling-backend pytorch are set by default
-drun v0.4.5-rocm630 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
+drun v0.4.5.post1-rocm630 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
 ```
 
 ## Method 4: Using docker compose
diff --git a/python/pyproject.toml b/python/pyproject.toml
index 5003358c57d..0b22b8cb982 100644
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "sglang"
-version = "0.4.5"
+version = "0.4.5.post1"
 description = "SGLang is yet another fast serving framework for large language models and vision language models."
 readme = "README.md"
 requires-python = ">=3.8"
diff --git a/python/sglang/version.py b/python/sglang/version.py
index 98a433b3105..f4a80302345 100644
--- a/python/sglang/version.py
+++ b/python/sglang/version.py
@@ -1 +1 @@
-__version__ = "0.4.5"
+__version__ = "0.4.5.post1"