GPU Instance Pricing
GPU Instance Pricing
On-Demand Pricing
Introduction
On-Demand Pricing is designed to offer users the flexibility to access computational resources without any long-term commitments or upfront costs. This pricing model is ideal for users who require compute power on an as-needed basis, whether for short-term projects, variable workloads, or unpredictable processing demands.
Billing Structure of On-Demand Pricing
Includes "computing resources" and "storage resources", you can view the billing details on the .
1. Computing Resources
Cost = Instance Unit Price × Billing Duration × Number of Cards
Note
- Billing duration is accurate to the second and settled hourly;
- You can view the unit prices of various instance specifications on the ;
- The billing start time is when the instance is successfully created and enters the pulling state, and the billing stop time is when the instance is stopped.
2. Storage Resources
Billing Item | Billing Method | Explanation | Billing Logic |
---|---|---|---|
System Disk | Pay-as-you-go | Supports 60GB free quota, charges for the excess based on capacity and usage duration. | Unit price for the excess capacity: $0.002/GB/day |
Local Disk | Pay-as-you-go | Supports 30GB free quota, charges for the excess based on capacity and usage duration. | Unit price for the excess capacity: $0.002/GB/day |
Cloud Storage | Pay-as-you-go | Charges based on capacity and usage duration. | Unit price: $0.002/GB/day |
Advantages of On-Demand Pricing for Different Scenarios
- Short-Term Projects: For projects with a limited duration, On-Demand Pricing allows you to align your compute costs with the project timeline.
- Variable Workloads: If your workloads fluctuate, On-Demand Pricing provides the flexibility to scale up or down as needed without incurring fixed costs.
- Testing and Development: For testing new applications or developing code, On-Demand Pricing offers a cost-effective way to access necessary compute resources without long-term financial commitments.