Compute Instance
Launch an on-demand GPU instance and start building
On-demand GPU instances with SSH access to run any GPU-accelerated workloads and let you run, test, and experiment with any AI application seamlessly.
1. Select a base image
Spin up a compute instance with your preferred base image (e.g. PyTorch). Enter your ssh public key to configure access to the instance.
Finally, select a GPU instance type and click Deploy.
2. SSH into the instance
Once the instance is ready, ssh into the endpoint url provided in the deployment details page with username centml
.
The instance comes preinstalled with NVIDIA drivers and libraries, as well as those included in your selected base image. Additional packages and libraries can be installed via pip.
What’s Next
LLM Serving
Explore dedicated public and private endpoints for production model deployments.
Clients
Learn how to interact with the CentML platform programmatically
Resources and Pricing
Learn more about the CentML platform’s pricing.
Private Inference Endpoints
Learn how to create private inference endpoints
Submit a Support Request
Submit a Support Request.
Agents on CentML
Learn how agents can interact with CentML services.