AI-102 Implement generative AI solutions Practice Question
Network Topology
You run the Azure CLI command shown in the exhibit. After a few minutes, the deployment fails with a quota error. What is the most likely cause?
⚠ Common exam trap
The trap here is that candidates might confuse a quota error with a model deprecation or SKU issue, but the error message's explicit mention of 'quota' directly points to capacity limits, not configuration or availability problems.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The requested capacity of 10 exceeds the available quota for the gpt-4 model in that region.
The quota error indicates that the requested capacity (10 units) for the gpt-4 model exceeds the available quota in the target region. Azure OpenAI deployments require sufficient model-specific quota, which is region- and model-specific. The error is not related to SKU name validity, model version deprecation, or resource group existence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The SKU name 'Standard' is invalid for Azure OpenAI deployments.
Why it's wrong here
Standard is a valid SKU.
- ✗
The model version '0613' is deprecated and no longer available.
Why it's wrong here
0613 is a valid version.
- ✓
The requested capacity of 10 exceeds the available quota for the gpt-4 model in that region.
Why this is correct
Quota errors occur when capacity exceeds regional limits.
- ✗
The resource group name 'myResourceGroup' does not exist.
Why it's wrong here
A missing resource group would cause a different error.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.