Hyperstack Documentation
Learn how to deploy and manage GPU virtual machines, Kubernetes clusters, and AI workloads on Hyperstack
Getting Started
Deploy and connect to your first virtual machine in minutes.
GPU Cloud
Hardware & GPUs
GPU and CPU flavors, specs, and regional availability.
Virtual Machines
Images, snapshots, hibernation, and lifecycle management.
Kubernetes
On-demand cluster provisioning and management.
Storage
Volumes, object storage, and NVMe root disks.
Network
SSH, firewalls, public IPs, and high-speed networking.
Concepts
Environments, regions, dashboard, and platform fundamentals.
AI Studio
Overview
End-to-end platform for model fine-tuning, deployment, and inference.
Getting Started
Set up AI Studio and run your first inference request.
Models
Fine-tune, import, and deploy language models.
Build
Tutorials
Step-by-step guides for GPU workloads and platform features.
MCP Servers
Two servers connecting AI assistants to Hyperstack: one answers questions from the docs, one manages your infrastructure.
SDKs & Libraries
Python, Go, JavaScript, and Terraform clients for the Hyperstack API.