Supporting NVIDIA and AMD accelerators on Vultr¶
As demand for AI infrastructure grows, the need for efficient, vendor-neutral orchestration tools is becoming
increasingly important.
At dstack
, we’re committed to redefining AI container orchestration by prioritizing an AI-native, open-source-first
approach.
Today, we’re excited to share a new integration and partnership
with Vultr .
This new integration enables Vultr customers to train and deploy models on both AMD
and NVIDIA GPUs with greater flexibility and efficiency–using dstack
.
About Vultr¶
Vultr provides cloud GPUs across 32 regions, supporting both NVIDIA and AMD hardware with on-demand and reserved capacity. Their offerings include AMD MI300X and NVIDIA GH200, H200, H100, A100, L40S, and A40, all available at competitive pricing .
Why dstack¶
Kubernetes wasn’t built for AI. It’s powerful, but it adds unnecessary complexity that slows down development, training,
and deployment. That’s where dstack
comes in.
dstack
is an open-source orchestrator designed specifically for AI. Here’s a quick look at how it simplifies running dev
environments and services on Vultr:
dstack
runs on any cloud or on-prem setup, providing a simple way to manage dev environments, tasks, services, fleets,
and volumes—so you can focus on building instead of troubleshooting infrastructure.
Getting started¶
To use dstack
with your Vultr account, you need to configure a vultr
backend:
Log into your Vultr account, click Account
in the sidebar, select API
, find the Personal Access Token
panel and click the Enable API
button. In the Access Control
panel, allow API requests from all addresses or from the subnet where your dstack
server is deployed.
Then, go ahead and configure the backend:
projects:
- name: main
backends:
- type: vultr
creds:
type: api_key
api_key: B57487240a466624b48de22865589
For more details, refer to Installation.
Interested in fine-tuning or deploying DeepSeek on Vultr? Check out the corresponding example.
What's next?
- Refer to Quickstart
- Sign up with Vultr
- Check dev environments, tasks, services, and fleets
- Join Discord