Google Cloud Platform中创建Tesla P100 GPU驱动VM实例时配额超限问题咨询

I’ve run into this exact quota issue before—let’s walk through what’s happening and how to resolve it:

Why This Error Happens #

The GPUS_ALL_REGIONS quota is a global cap that tracks every GPU instance (any type, any region) in your project. From your quota details:

• You have 1 committed NVIDIA P100 quota in europe-west1
• Your global total GPU quota is set to 1

That committed quota is already using up your entire global GPU limit. Even though your regional P100 quota shows 1 available, the global block stops you from launching any additional GPU instances—including the on-demand one you’re trying to create now.

Actionable Fixes #

• Check for running GPU instances: Head to the GCP Console’s VM Instances page and look for any existing VMs with a P100 GPU attached. If one is running, it’s using your committed quota and hitting the global limit. You’ll need to stop/delete it before launching a new instance, or request a quota increase.
• Raise your GPUS_ALL_REGIONS quota: If you need to run multiple GPU instances (e.g., one committed + one on-demand), you’ll need to increase the global total. Here’s how:
  1. Open the Quotas page in the GCP Console
  2. Search for GPUS_ALL_REGIONS in the quota list
  3. Click "Edit Quotas" and submit a request explaining your use case (e.g., "Requiring 2 total GPUs to run a committed P100 and on-demand P100 for ML workloads in europe-west1")
• Validate your committed quota setup: Double-check that your committed P100 quota is active and correctly tied to europe-west1. Rarely, committed use discounts can have activation delays or misconfigured regions, which can block on-demand requests even if regional quota looks free.
• Confirm your VM’s GPU selection: Double-check that you’re explicitly choosing the NVIDIA P100 in your VM creation settings. Accidentally picking a different GPU type (like T4 or V100) would still count against your global quota and trigger this error.

Key Note #

Committed quota reserves capacity for you, but it still counts toward your global GPU limit. With a global quota of 1, you can only run one GPU instance at a time—whether it’s using committed or on-demand resources.

内容的提问来源于stack exchange，提问作者EL Rabo