- A
frequency_penalty
Why wrong: Frequency penalty reduces repetition, not length.
- B
max_tokens
Max_tokens sets the maximum number of tokens in the output.
- C
top_p
Why wrong: Top_p controls nucleus sampling, not length.
- D
temperature
Why wrong: Temperature controls randomness, not length.
Question 128 of 991
1Z0-1127 Using OCI Generative AI Service Practice Question
This 1Z0-1127 practice question tests your understanding of using oci generative ai service. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
An organization wants to use OCI Generative AI to summarize long legal documents. They need to ensure the summary is concise and retains key information. Which model parameter should they set to control the length of the summary?
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
✓
max_tokens
The `max_tokens` parameter directly controls the maximum number of tokens (words or subwords) the model can generate in its response. By setting a lower value for `max_tokens`, the organization can enforce a concise summary, ensuring the output length is capped while retaining key information. Other parameters like `temperature` or `top_p` affect randomness or diversity, not output length.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
frequency_penalty
Why it's wrong here
Frequency penalty reduces repetition, not length.
- ✓
max_tokens
Why this is correct
Max_tokens sets the maximum number of tokens in the output.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
top_p
Why it's wrong here
Top_p controls nucleus sampling, not length.
- ✗
temperature
Why it's wrong here
Temperature controls randomness, not length.
Common exam traps
Common exam trap: answer the scenario, not the keyword
OCI often tests the distinction between parameters that control output length (`max_tokens`) versus those that control output diversity or repetition (`temperature`, `top_p`, `frequency_penalty`), leading candidates to confuse `temperature` or `top_p` as length controls.
Detailed technical explanation
How to think about this question
Under the hood, `max_tokens` acts as a hard stop on the autoregressive generation loop: once the model has produced that many tokens, generation ceases, even if the model would naturally continue. In OCI Generative AI, the tokenizer counts tokens (not characters), so a `max_tokens` value of 100 might yield roughly 75–150 words depending on the language and tokenization scheme. For legal document summarization, setting `max_tokens` too low can truncate critical clauses, so it is often combined with a prompt instructing the model to produce a summary of a specific length.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the 1Z0-1127 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
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FAQ
Questions learners often ask
What does this 1Z0-1127 question test?
Using OCI Generative AI Service — This question tests Using OCI Generative AI Service — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: max_tokens — The `max_tokens` parameter directly controls the maximum number of tokens (words or subwords) the model can generate in its response. By setting a lower value for `max_tokens`, the organization can enforce a concise summary, ensuring the output length is capped while retaining key information. Other parameters like `temperature` or `top_p` affect randomness or diversity, not output length.
What should I do if I get this 1Z0-1127 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This 1Z0-1127 practice question is part of Courseiva's free Oracle 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 1Z0-1127 exam.
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