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AI-102 Implement generative AI solutions Practice Question

Which THREE factors should you consider when selecting a model for a generative AI solution on Azure?

⚠ Common exam trap

Many exam-takers confuse internal model architecture (like transformer layers) with selection criteria, when in fact Azure abstracts those details and you only need to consider cost, capability, latency, and deployment options.

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

Cost per token and deployment options.

Cost per token directly impacts operational expenses in pay-per-use models like GPT-4 on Azure OpenAI, and deployment options (e.g., global vs. regional, provisioned throughput) affect availability and scalability. These are fundamental considerations when operationalizing a generative AI solution.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Cost per token and deployment options.

    Why this is correct

    Cost and deployment flexibility are key considerations.

  • Model capability and modality (text, code, image).

    Why this is correct

    Capability determines if the model suits the task.

  • Latency and throughput requirements.

    Why this is correct

    Latency affects real-time applications.

  • Number of transformer layers in the model.

    Why it's wrong here

    Layer count is not a selection criterion.

  • Training data source and licensing.

    Why it's wrong here

    Training data is not disclosed to users.

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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.