Fundamentals of Large Language Models →easyMultiple ChoiceObjective-mapped

1Z0-1127-25 Fundamentals of Large Language Models Practice Question

Network Topology

Refer to the exhibit. What is the primary reason the response is incomplete?

⚠ Common exam trap

Oracle often tests the distinction between parameters that affect output quality (temperature, top_p) versus those that constrain output length (max_tokens, stop sequences), and the trap here is that candidates mistake a short prompt or missing temperature for the cause of truncation when the real culprit is the token budget.

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 max-tokens limit is too low.

The response is incomplete because the max-tokens limit is too low, causing the model to truncate its output before completing the full answer. When the token budget is exhausted, the generation stops mid-sentence or mid-thought, leaving the response unfinished regardless of prompt length or other parameters.

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 temperature is not set.
Why it's wrong here
Temperature default is used; it does not cause incompleteness.
✗
The model-id is incorrect.
Why it's wrong here
The model-id is valid and works.
✓
The max-tokens limit is too low.
Why this is correct
Setting max-tokens to 100 restricts the output length, causing truncation.
✗
The prompt is too short.
Why it's wrong here
Prompt length is not the issue; the model can produce longer answers.

Go deeper

1Z0-1127-25 Fundamentals of Large Language Models Practice Question

Why each option matters

Option-by-option breakdown

Related to this question