Guides
GPU Instance Pricing
Guides
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 Billing Explore.
1. Computing Resources
Cost = Instance Unit Price × Billing Duration × Number of Cards
- Billing duration is accurate to the second and settled hourly;
- You can view the unit prices of various instance specifications on the GPU Instance Explore;
- 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 |
|---|---|---|---|
| Container 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 |
| Volume Disk | Pay-as-you-go | Charges based on capacity and usage duration. | Unit price: $0.002/GB/day |
| Network Volume | 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.
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