Deploy Instance
Browse GPU Marketplace
Commitment
Location
Instance
GPU
Please complete the previous selections to see this section.
CPU
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Node
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Operating System
This operating system is a vanilla version with NVIDIA drivers installed.
Storage
Local storage offers better performance but comes with its limitations. Virtual machines with local storage cannot be upgraded or downgraded. It's also not possible to change the GPU/CPU model or the instance type after the virtual machine is deployed.
Network storage provides lower performance but offers scalability for virtual machines. Virtual machines with network storage can be upgraded, downgraded, the selected GPU/CPU model and the instance type can be changed at any time after the virtual machine is deployed.
The root storage cannot be expanded after the virtual machine creation. To increase storage capacity, network-based additional disks can be added to the virtual machine.
We do not recommend using a HDD unless necessary. Delivery times of instances with HDD can double typical deployment times.
Storage Size (GB)
100GB - 20480GB
Network Storage
Network-based disks are provisioned on our internal network and can be attached to any instance in any data center.
Please log in to see your additional disks.
Pricing
Your instance configuration:
Term: On-Demand
Location: Undefined
Type: GPU
Resources
vCPUs: 1
$0.0110/hour (INCLUDED)
RAM: 1 GB
$0.0060/hour (INCLUDED)
Network: 10Gbps Unlimited
$0.0055/hour (IP Address)
Running Cost: $0.0055/hour
Stopped Cost: $0.0055/hour
Stock Deployable: -
Instance Details
You are deploying a Spot GPU instance.
Spot VMs offer lower pricing but can be interrupted, so they are best for flexible, fault-tolerant, or short-lived workloads.
Spot VMs offer lower pricing but can be interrupted, so they are best for flexible, fault-tolerant, or short-lived workloads.
Specify the commands to be executed during the initialization of your instance. For more detailed information, please refer to our documentation.
CommandsNumber of deployments
1 - 100+
Information
When to Use Spot VMs
Spot virtual machines are ideal for workloads that are flexible, fault-tolerant, or short-lived. They provide substantial cost savings compared to on-demand VMs, making them well-suited for scenarios where high performance is needed but uninterrupted uptime is not essential.
Ideal Use Cases
- Non-critical or interruptible workloads: Tasks that can handle unexpected interruptions, such as background jobs, testing environments, or temporary development setups.
- Batch processing: Workloads that run in scheduled or repeatable jobs, like data processing pipelines or rendering tasks.
- Machine learning and AI: Model training and experimentation that can be checkpointed and resumed as needed.
- Scaling compute-heavy workloads: When used alongside on-demand resources, spot VMs can help increase capacity at a lower cost.
Payment
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