easyMultiple Choice
Generative AI Leader Practice Question: A startup wants to quickly prototype a…
A startup wants to quickly prototype a conversational AI application using Gemini. They need free access during development and do not require VPC controls. Which access tier should they choose?
⚠ Common exam trap
The Generative AI Leader exam often tests the misconception that any Google Cloud service requires a billing account, but Google AI Studio's free tier explicitly bypasses this for prototyping, while options like Vertex AI or Cloud Run always incur costs even at low usage.
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
✓
Google AI Studio free tier
Google AI Studio's free tier provides free access to Gemini models for rapid prototyping without requiring VPC controls or any billing setup. This aligns directly with the startup's need for quick, cost-free development iteration before moving to production.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Vertex AI on a pay-as-you-go basis
Why it's wrong here
Pay-as-you-go Vertex AI bills per token or hour from the first request, so it provides no free development tier. It is tempting because Vertex AI offers enterprise controls and Gemini access, making it the right pick when production governance, quotas and VPC-SC are required rather than free prototyping.
- ✗
Vertex AI with VPC-SC
Why it's wrong here
VPC-SC adds a service perimeter requiring organisation-level networking and IAM configuration, which the startup explicitly does not need and which blocks quick free prototyping. It is tempting because VPC-SC is the correct choice when regulated data must stay inside a controlled perimeter.
- ✗
Gemini API via Cloud Run
Why it's wrong here
Cloud Run is a compute host for containers, not an access tier; deploying the Gemini API there still requires a billed API key or Vertex AI endpoint behind it. It is tempting when you need to host a custom wrapper service, but that adds infrastructure the prototype does not need.
- ✓
Google AI Studio free tier
Why this is correct
Google AI Studio's free tier provides immediate, no-cost API access to Gemini models, satisfying the startup's prototyping budget constraint. It omits enterprise controls such as VPC Service Controls and data residency guarantees, which the stem explicitly does not require. This makes it the fastest path to building a conversational proof of concept.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This Generative AI Leader practice question is part of Courseiva's free Google Cloud 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 Generative AI Leader exam.