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After creating a GPU instance, you can run deep learning training, model fine-tuning, inference services, or other GPU-accelerated tasks on the instance. GPU instances use bare-metal resources. When creating one, you must configure the billing mode, region, network, specifications, image, storage, logon credential, and optional components.

Procedure

  1. Log in to the GPU Cloud console and go to the Instance page.
  2. On the GPU Instance tab, click Create GPU Instance.
  3. In the Billing mode section, select a billing mode.
  4. In the Basic Information section, configure the HostName and Region.
  5. In the Instance & Image section, select the network, specifications, Image, and runtime environment. If your workload has no specific container network requirements, we recommend keeping the default options. If existing workloads depend on legacy provisioning network behavior, select Use Legacy Provisioning Behavior.
  6. In the Storage section, configure the data disk.
  7. In the Authentication section, configure the Logon Credential.
  8. In the Options section, select whether to install optional components.
  9. Check the Estimated Cost on the right, and confirm the Instance Type, quantity, and Balance information.
  10. Click Continue to proceed to the Review step.
  11. After verifying that the configuration is correct, submit the creation request. Once creation is complete, confirm that the instance status is as expected on the Instance page.