diff --git a/docs/getting_started/installation/README.md b/docs/getting_started/installation/README.md
index 5abd9728b..20a737dca 100644
--- a/docs/getting_started/installation/README.md
+++ b/docs/getting_started/installation/README.md
@@ -4,4 +4,5 @@ vLLM-Omni supports the following hardware platforms:
 
 - [GPU](gpu.md)
     - [NVIDIA CUDA](gpu.md)
+    - [AMD ROCm](gpu.md)
 - [NPU](npu.md)
diff --git a/docs/getting_started/installation/gpu.md b/docs/getting_started/installation/gpu.md
index 42f716f30..5956ed102 100644
--- a/docs/getting_started/installation/gpu.md
+++ b/docs/getting_started/installation/gpu.md
@@ -14,6 +14,10 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr
 
     --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:requirements"
 
+=== "AMD ROCm"
+
+    --8<-- "docs/getting_started/installation/gpu/rocm.inc.md:requirements"
+
 ## Set up using Python
 
 ### Create a new Python environment
@@ -26,6 +30,11 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr
 
     --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:pre-built-wheels"
 
+
+=== "AMD ROCm"
+
+    --8<-- "docs/getting_started/installation/gpu/rocm.inc.md:pre-built-wheels"
+
 [](){ #build-from-source }
 
 ### Build wheel from source
@@ -34,8 +43,22 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr
 
     --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:build-wheel-from-source"
 
+=== "AMD ROCm"
+
+    --8<-- "docs/getting_started/installation/gpu/rocm.inc.md:build-wheel-from-source"
+
 ## Set up using Docker
 
+### Build wheel from source
+
+=== "NVIDIA CUDA"
+
+    --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:build-wheel-from-source-in-docker"
+
+=== "AMD ROCm"
+
+    --8<-- "docs/getting_started/installation/gpu/rocm.inc.md:build-wheel-from-source-in-docker"
+
 ### Pre-built images
 
 === "NVIDIA CUDA"
diff --git a/docs/getting_started/installation/gpu/cuda.inc.md b/docs/getting_started/installation/gpu/cuda.inc.md
index ac519d20e..52d365d9c 100644
--- a/docs/getting_started/installation/gpu/cuda.inc.md
+++ b/docs/getting_started/installation/gpu/cuda.inc.md
@@ -74,6 +74,9 @@ uv pip install --no-build-isolation --editable .
 
 # --8<-- [end:build-wheel-from-source]
 
+# --8<-- [start:build-wheel-from-source-in-docker]
+
+# --8<-- [end:build-wheel-from-source-in-docker]
 
 # --8<-- [start:pre-built-images]
 
diff --git a/docs/getting_started/installation/gpu/rocm.inc.md b/docs/getting_started/installation/gpu/rocm.inc.md
new file mode 100644
index 000000000..3b970267a
--- /dev/null
+++ b/docs/getting_started/installation/gpu/rocm.inc.md
@@ -0,0 +1,115 @@
+# --8<-- [start:requirements]
+
+- GPU: Validated on gfx942 (It should be supported on the AMD GPUs that are supported by vLLM.)
+
+# --8<-- [end:requirements]
+# --8<-- [start:set-up-using-python]
+
+vLLM-Omni current recommends the steps in under setup through Docker Images.
+
+# --8<-- [start:pre-built-wheels]
+
+# --8<-- [end:pre-built-wheels]
+
+# --8<-- [start:build-wheel-from-source]
+
+# --8<-- [end:build-wheel-from-source]
+
+# --8<-- [start:build-wheel-from-source-in-docker]
+
+#### Get the correct docker environment
+
+The v0.11.0 releases is on Oct 3, 2025, so we will pull a AMD nightly docker image close to the release period. `rocm/vllm-dev:nightly_main_20251005` is picked as it has a correct `transformers` version that supports qwen3_omni.
+
+`docker pull rocm/vllm-dev:nightly_main_20251005`
+
+#### Launch the docker environment
+
+In this docker environment, we have all the dependencies for vLLM installed, like `flash-attn` and `aiter`
+
+```bash
+#!/bin/bash
+docker run -it \
+   --privileged \
+   --network=host \
+   --group-add=video \
+   --ipc=host \
+   --cap-add=SYS_PTRACE \
+   --security-opt seccomp=unconfined \
+   --device /dev/kfd \
+   --device /dev/dri \
+   --name vllmomni \
+   rocm/vllm-dev:nightly_main_20251005 \
+   bash
+```
+
+#### Update docker dependencies
+
+```bash
+sudo apt update
+sudo apt install ffmpeg -y
+```
+
+#### Installation of vLLM
+Install the v0.11.0 release of vLLM as vLLM-Omni is currently depend on v0.11.0.
+
+```bash
+# uninstall existing vllm which is based on the main branch, not on the releases branch
+python3 -m pip uninstall -y vllm
+git clone https://github.com/vllm-project/vllm.git vllm0110
+cd vllm0110/
+
+# checkout the version tag v0.11.0
+git checkout -b v0.11.0 v0.11.0
+
+# you should see 0.11.0
+python -c "import setuptools_scm; print(setuptools_scm.get_version())"
+
+# PYTORCH_ROCM_ARCH=<your-gpu-arch> python3 setup.py develop
+PYTORCH_ROCM_ARCH=gfx942 python3 setup.py develop
+```
+
+!!! note
+    vLLM release wheels based on the branch with prefix `releases/`, not from the tag as vLLM may cherry pick bugfixes after cutting a branch.
+
+
+#### Installation of vLLM-Omni
+
+There are two approaches to installing `vllm-omni`
+
+
+1. Install from PyPI
+
+```bash
+pip install vllm-omni
+
+# you might want to also download the source code of the same version to run the examples
+```
+
+2. Install from source
+
+```bash
+# clone and checkout to the release version.
+git clone https://github.com/vllm-project/vllm-omni.git
+cd vllm-omni
+git checkout v0.11.0rc1
+pip install -e .
+```
+
+#### Setup Environment Variables
+
+After installing `vllm` and `vllm-omni` please setup the environment variable as well before running any of the examples and command.
+
+```bash
+export MIOPEN_FIND_MODE=FAST
+export VLLM_ROCM_USE_AITER=1
+export VLLM_ROCM_USE_AITER_MHA=1
+export VLLM_ROCM_USE_AITER_LINEAR=0
+export VLLM_ROCM_USE_AITER_RMSNORM=0
+```
+
+# --8<-- [end:build-wheel-from-source-in-docker]
+
+# --8<-- [start:pre-built-images]
+
+# --8<-- [end:pre-built-images]
diff --git a/docs/models/supported_models.md b/docs/models/supported_models.md
index c8a0e622c..391cab0b1 100644
--- a/docs/models/supported_models.md
+++ b/docs/models/supported_models.md
@@ -6,7 +6,7 @@ vLLM-Omni supports unified multimodal comprehension and generation models across
 
 If vLLM-Omni natively supports a model, its implementation can be found in <gh-file:vllm_omni/model_executor/models> and <gh-file:vllm_omni/diffusion/models>.
 
-## List of Supported Models for Nvidia GPU
+## List of Supported Models for Nvidia GPU / AMD GPU
 
 <style>
 th {