Quickstart

Get started with Dynamo locally in just a few commands.

1. Install Dynamo

$ # Install uv (recommended Python package manager)
$ curl -LsSf https://astral.sh/uv/install.sh | sh
$ 
$ # Create virtual environment and install Dynamo
$ uv venv venv
$ source venv/bin/activate
$ # Use prerelease flag to install RC versions of flashinfer and/or other dependencies
$ uv pip install --prerelease=allow "ai-dynamo[sglang]"  # or [vllm], [trtllm]

2. Start etcd/NATS

$ # Fetch and start etcd and NATS using Docker Compose
$ VERSION=$(uv pip show ai-dynamo | grep Version | cut -d' ' -f2)
$ curl -fsSL -o docker-compose.yml https://raw.githubusercontent.com/ai-dynamo/dynamo/refs/tags/v${VERSION}/deploy/docker-compose.yml
$ docker compose -f docker-compose.yml up -d

3. Run Dynamo

$ # Start the OpenAI compatible frontend (default port is 8000)
$ python -m dynamo.frontend
$ 
$ # In another terminal, start an SGLang worker
$ python -m dynamo.sglang --model-path Qwen/Qwen3-0.6B

4. Test your deployment

$ curl localhost:8000/v1/chat/completions \
>   -H "Content-Type: application/json" \
>   -d '{"model": "Qwen/Qwen3-0.6B",
>        "messages": [{"role": "user", "content": "Hello!"}],
>        "max_tokens": 50}'

Next Steps

Installation - Detailed installation options
Examples - More deployment examples
Support Matrix - Supported models and configurations

$	# Install uv (recommended Python package manager)
$	curl -LsSf https://astral.sh/uv/install.sh \| sh
$
$	# Create virtual environment and install Dynamo
$	uv venv venv
$	source venv/bin/activate
$	# Use prerelease flag to install RC versions of flashinfer and/or other dependencies
$	uv pip install --prerelease=allow "ai-dynamo[sglang]" # or [vllm], [trtllm]

$	# Fetch and start etcd and NATS using Docker Compose
$	VERSION=$(uv pip show ai-dynamo \| grep Version \| cut -d' ' -f2)
$	curl -fsSL -o docker-compose.yml https://raw.githubusercontent.com/ai-dynamo/dynamo/refs/tags/v${VERSION}/deploy/docker-compose.yml
$	docker compose -f docker-compose.yml up -d

$	# Start the OpenAI compatible frontend (default port is 8000)
$	python -m dynamo.frontend
$
$	# In another terminal, start an SGLang worker
$	python -m dynamo.sglang --model-path Qwen/Qwen3-0.6B

$	curl localhost:8000/v1/chat/completions \
>	-H "Content-Type: application/json" \
>	-d '{"model": "Qwen/Qwen3-0.6B",
>	"messages": [{"role": "user", "content": "Hello!"}],
>	"max_tokens": 50}'