Launching GPU Instances
Deploy on-demand GPU instances in minutes.
Prerequisites
- Wallet funded with at least 1 hour of instance cost
- At least one SSH key added to your account
Not ready? Complete Getting Started first.
Browse GPU Marketplace
The Home page displays available GPU configurations in real-time.
GPU Listing Information
| Specification | Description |
|---|---|
| GPU Model | Type and count (e.g., A100, H100, RTX 4090) |
| VRAM | GPU memory per card |
| vCPU | Number of CPU cores |
| RAM | System memory |
| Storage | NVMe instance storage |
| Region | Datacenter location |
| Price | Hourly rate in EUR (€) |
| Status | Available / Coming soon |
Filter options: Region, GPU type, availability
Note: Availability updates in real-time.
Select Configuration
Click on a GPU card to view detailed specifications and launch configuration.
Key information displayed:
- Complete hardware specs
- Pricing (hourly, daily, monthly estimates)
- Region and cloud provider
- Operating system options
Configure Instance
Required Settings
Instance Name:
- 1-50 characters
- Use descriptive names (e.g., ml-training-01, render-job-42)
Region:
- Pre-selected based on GPU availability
- Cannot be changed
SSH Key:
- Select from your added keys
- Required for instance access
Operating System:
- Choose from available images
- All images include CUDA drivers and GPU tools
- Format: Ubuntu version + CUDA version
Optional Settings
Tags:
- Add labels for organization (e.g., production, ml-training, team-alpha)
- Useful for filtering and cost tracking
Environment Variables:
- Set key-value pairs for your instance
- Example: API_KEY=your_key, MODEL_PATH=/mnt/volume/models
Startup Script:
- Bash script executed on first boot
- Use for installing software, downloading data, configuring services
- Runs as root user
Example:
#!/bin/bash
apt-get update
pip3 install torch torchvision transformers
cd /root
git clone https://github.com/your-repo/project.git
Storage Volume:
- Attach existing volume or create new volume
- Volumes must be in same cloud region as instance
- Choose size (50 GB to 10,000 GB)
- Additional hourly cost applies
Launch
- Review pricing estimate
- Verify wallet balance is sufficient (minimum 1 hour cost)
- Click "Launch Instance"
The system checks availability in real-time. If available, the first hour is charged and instance creation begins.
Instance Status
After launch, instances progress through these states:
- creating: Infrastructure provisioning (1-2 minutes)
- pending_provider: Cloud provider setup (2-5 minutes)
- pending: Final configuration (1-2 minutes)
- active: Running and accessible
- failed: Launch failed (first hour refunded)
- suspended: Insufficient wallet balance
- deleting: Terminating (1-2 minutes)
- deleted: Removed
Total launch time: 5-10 minutes
Connect via SSH
Once status is active, connect using:
ssh -i /path/to/private_key.pem root@<IP_ADDRESS>
Connection details (IP address, SSH port, SSH user) are available on the Resources page.
Verify GPU access:
nvidia-smi
Common Issues
GPU Unavailable:
- Try different region or GPU type
- Availability changes in real-time
Insufficient Balance:
- Add funds to wallet
- Minimum required: 1 hour of total cost (instance + volume)
Cannot Connect:
- Wait for status to be active
- Verify correct IP address and private key
- Check key permissions:
chmod 600 key.pem - Ensure status is active, not creating or pending
Instance Stuck in Creating:
- Normal duration: 5-10 minutes
- If exceeds 15 minutes, contact support
- Failed instances automatically refund first hour
Next Steps
- Managing Resources - Monitor and control instances
- Storage Volumes - Persistent data storage
- Advanced Configuration - Automation and optimization