GPU VMs | ibee | Documentation

GPU VMs are KVM-based virtual machines with NVIDIA GPUs attached. Use them for model training and fine-tuning, inference APIs, rendering, video processing, and any workload that needs GPU acceleration. You deploy and manage them from the portal much like Cloud VMs, with a GPU plan catalog and an extra GPU Metrics tab.

Ready to deploy? Follow Create a GPU VM.

What you can do

Deploy GPU plans that combine a GPU model and GPU memory with vCPU, RAM, and disk — up to 5 identical VMs at once.
Boot from GPU-compatible OS templates, or from an ISO, snapshot, or backup.
Sign in with SSH keys (Linux) or a password, shown under Overview → Connection Details.
Connect with a public IP, or place the VM in a VPC with Private + NAT or Private only networking. Attach Reserved IPs and protect it with a firewall group.
Watch CPU, memory, disk, and network on the Monitoring tab, and GPU utilization, VRAM, temperature, and power on the GPU Metrics tab.
Protect data with scheduled backups and manual snapshots.
Change plans and manage IPs, VPCs, SSH keys, and passwords from the Settings tab.

Find GPU VMs in the portal

In the portal sidebar, open Infrastructure → GPU VMs. The GPU Virtual Machines page lists your GPU VMs with their Instance, OS, Location, IP Address, and Status. Click Deploy GPU VM to create one, or click a row to open its detail page.

How GPU VMs differ from Cloud VMs

	GPU VMs	Cloud VMs
Plans	Each plan lists the GPU model and GPU memory, plus vCPU, RAM, disk, and price.	vCPU, memory, storage, and bandwidth. See Instance types.
Billing	Hourly.	Hourly, or Monthly / Yearly commitments where offered.
Templates	Only GPU-compatible images are listed.	Only Cloud VM images are listed.
Detail tabs	Overview, Monitoring, GPU Metrics, Backups, Snapshots, Settings.	Overview, Monitoring, Backups, Snapshots, Settings.

Everything else — location, SSH keys, network configuration, instance count, hostnames, power actions, and the delete dialog — works the same way as for Cloud VMs.

Lifecycle of a GPU VM

Stage	What you do	Where
Deploy	Pick location, GPU plan, OS, SSH keys, network, and hostname.	Create a GPU VM
Set up	Confirm the GPU with `nvidia-smi`; install a compatible NVIDIA driver if it’s missing.	Create a GPU VM
Operate	Start, stop, reboot; watch Monitoring and GPU Metrics.	Power actions
Connect	Manage public IP, Reserved IPs, VPCs, and access.	Networking for VMs
Protect	Enable scheduled backups or take manual snapshots.	Backups · Snapshots
Scale	Change plan from Settings → Change Plan.	Resize a VM
Retire	Delete the VM, optionally keeping its public IP as a Reserved IP.	Power actions

GPU Metrics

The GPU Metrics tab charts GPU Utilization, VRAM Utilization, Temperature, and Power Draw over 30m, 1h, 6h, 24h, or 7d. Collection is off until you turn it on:

Start the VM, and make sure qemu-guest-agent is running inside it.
On GPU Metrics, click Enable monitoring. A lightweight IBEE agent is installed through the guest agent — it opens no network port on the VM.
If the tab shows NVIDIA guest driver required, install a compatible NVIDIA driver inside the VM. Monitoring starts automatically once nvidia-smi works; CUDA is optional.

If the agent goes offline or setup fails, the tab explains why and offers Repair monitoring. Historical values stay visible while the VM is stopped.

Browser console access isn’t available in the portal yet — the Console action is shown as Soon. Use SSH or RDP with the details under Overview → Connection Details.