AI-300 Generative AI Optimization Practice Question
Which THREE factors contribute to increased latency in an LLM application?
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 size/complexity of the chosen model.
Model size, input/output token count, and network transit time are the main drivers of latency.
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 number of system messages used.
Why it's wrong here
System messages are relatively cheap.
- ✓
The size/complexity of the chosen model.
Why this is correct
Larger models take longer to compute per token.
- ✓
The number of output tokens generated.
Why this is correct
Generation is sequential; longer responses take more time.
- ✗
The use of JSON output mode.
Why it's wrong here
JSON mode has negligible impact on latency.
- ✓
The number of input tokens provided.
Why this is correct
More input tokens require more processing time.
About these practice questions
This AI-300 question is part of Courseiva's 204-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-300 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-300 exam.