Generative AI Leader Google Cloud's Generative AI Offerings Practice Question
A financial services firm uses a fine-tuned Gemini model in Vertex AI for regulatory compliance checks. They notice that token usage is high, increasing costs. They want to reduce costs without sacrificing accuracy. Which approach should they take?
⚠ Common exam trap
It's easy for candidates to confuse cost-reduction strategies that affect model behavior (like temperature or model size) with those that directly reduce token count, leading them to pick options that change output quality rather than token 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
✓
Set max output tokens to a lower value and use more precise prompts
Reducing max output tokens directly lowers the number of tokens generated per request, which is the primary cost driver in pay-per-token models like Gemini. Using more precise prompts further reduces token waste by guiding the model to produce concise, relevant outputs without sacrificing accuracy, as compliance checks often require specific, structured responses rather than verbose explanations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to a smaller base model like PaLM 2 Bison
Why it's wrong here
May reduce accuracy for compliance tasks.
- ✗
Enable context caching to reuse previous responses
Why it's wrong here
Caching saves on repeated prompts but doesn't reduce per-request token usage.
- ✓
Set max output tokens to a lower value and use more precise prompts
Why this is correct
Directly reduces output tokens; precise prompts maintain accuracy.
- ✗
Reduce temperature to 0.0
Why it's wrong here
Affects randomness, not token count.
Go deeper
Related to this question
About these practice questions
Courseiva writes every Generative AI Leader question from scratch — 683 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
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.