How to Fix AWS GPU instance Launch Failures: Checking & Increasing vCPU GPU Limits

The frustration is real: you’ve built your environment, configured your AMI, and you’re ready to scale your GPU-intensive workload. Then, the Max Spot Instance count exceeded or VCPU limit exceeded error hits. For many AWS users trying to launch g4dn.4xlarge instances (NVIDIA GPUs), the bottleneck isn’t usually hardware availability—it’s an invisible “ceiling” called the vCPU Service Quota.

In this guide, we’ll break down why your g4dn instances are failing to launch and provide a step-by-step walkthrough on how to check and increase your vCPU limits for both On-Demand and Spot “G” class instances.

The Hidden Barrier: Understanding GPU vCPU Quotas

AWS manages its massive infrastructure through Service Quotas. These are guardrails designed to prevent runaway costs and ensure capacity is distributed fairly across users. For graphics-intensive instances like the G family (which includes g4dn, g5, and g6), AWS doesn’t limit you by the number of instances, but by the total number of vCPUs those instances consume.

A single g4dn.2xlarge instance uses 8 vCPUs. If your regional quota for “All G and VT On-Demand Instance Requests” is set to 0 (the default for many new accounts) or 5, your launch will fail immediately because you don’t have enough “vCPU room” to fit even one instance. Crucially, these limits are tracked separately for On-Demand and Spot instances, meaning you may need to request two separate increases if you plan to use both.

How to Check Your vCPU Limit for On-Demand Graphic Instances

Before you can fix the problem, you need to see exactly where your limit stands. Follow these steps to check your current capacity in a specific AWS Region:

Sign in to the AWS Management Console and navigate to the Service Quotas dashboard.
In the left navigation pane, select AWS services.
Search for Amazon Elastic Compute Cloud (Amazon EC2) and click on it.
In the search bar within the EC2 quotas list, type “G” to filter for graphics instances.
Look for the quota named “Running On-Demand G and VT instances”.
Here, you will see your Applied quota value. This number represents the total vCPUs you are allowed to run across all G-series instances in that region.

If you are trying to launch Spot instances, look for the quota named “All G and VT Spot Instance Requests”. Note that the number of vCPUs required is cumulative; if you want to run five g4dn.2xlarge instances, you will need a quota of at least 40 vCPUs ($5 \times 8 = 40$).

How to Request a Quota Increase

If your current limit is lower than what your project requires, you must submit a request to AWS. This is not instantaneous—it can take anywhere from a few minutes to a couple of business days for the AWS support team to approve the increase.

Click on the specific quota (e.g., Running On-Demand G and VT instances) and select “Request increase at account level.” Enter the total number of vCPUs you need (not just the amount you want to add). For example, if you have 8 and need 32 more, enter 40. Providing a brief “Use Case” description—such as “Machine learning inference” or “Video transcoding”—often helps speed up the approval process.

Strategic Tips for G4dn Availability

While vCPU limits are the most common technical hurdle, physical capacity can also play a role. If you have the correct quota but still receive an InsufficientInstanceCapacity error, try spreading your instances across multiple Availability Zones (AZs). Not every AZ in a region has the same stock of NVIDIA T4 GPUs at any given moment. By utilizing a “Fleet” approach or simply trying a different subnet, you increase your chances of securing the hardware you need.

By proactively managing your Service Quotas and understanding the vCPU math behind your instance types, you can avoid deployment delays and keep your GPU workloads running smoothly.

Would you like me to help you calculate the exact vCPU quota you’ll need based on a specific number of different G-series instance types?