Installation | NVIDIA Dynamo Documentation

Pip (PyPI)

Install a pre-built wheel from PyPI.

$ # Create a virtual environment and activate it
$ uv venv venv
$ source venv/bin/activate
$ 
$ # Install Dynamo from PyPI (choose one backend extra)
$ uv pip install "ai-dynamo[sglang]"  # or [vllm], [trtllm]

Pip from source

Install directly from a local checkout for development.

$ # Clone the repository
$ git clone https://github.com/ai-dynamo/dynamo.git
$ cd dynamo
$ 
$ # Create a virtual environment and activate it
$ uv venv venv
$ source venv/bin/activate
$ uv pip install ".[sglang]"  # or [vllm], [trtllm]

Docker

Pull and run prebuilt images from NVIDIA NGC (nvcr.io).

$ # Run a container (mount your workspace if needed)
$ docker run --rm -it \
>   --gpus all \
>   --network host \
>   nvcr.io/nvidia/ai-dynamo/sglang-runtime:0.8.1  # or vllm, tensorrtllm

Replace 0.8.1 with your desired version tag. Check the GitHub releases for available versions.

$	# Create a virtual environment and activate it
$	uv venv venv
$	source venv/bin/activate
$
$	# Install Dynamo from PyPI (choose one backend extra)
$	uv pip install "ai-dynamo[sglang]" # or [vllm], [trtllm]

$	# Clone the repository
$	git clone https://github.com/ai-dynamo/dynamo.git
$	cd dynamo
$
$	# Create a virtual environment and activate it
$	uv venv venv
$	source venv/bin/activate
$	uv pip install ".[sglang]" # or [vllm], [trtllm]

$	# Run a container (mount your workspace if needed)
$	docker run --rm -it \
>	--gpus all \
>	--network host \
>	nvcr.io/nvidia/ai-dynamo/sglang-runtime:0.8.1 # or vllm, tensorrtllm