- A
The number of API requests made
Why wrong: While request count matters, token count per request is usually the dominant cost factor for long documents.
- B
The total number of tokens processed (input + output)
Pricing is typically per token; longer documents mean more tokens and higher cost.
- C
The choice of sampling strategy (e.g., top-k vs greedy)
Why wrong: Sampling strategy affects output quality but not token pricing.
- D
The latency of the inference endpoint
Why wrong: Latency does not directly affect cost; token count does.
Question 490 of 991
1Z0-1127 LLM Fundamentals Practice Question
This 1Z0-1127 practice question tests your understanding of llm fundamentals. 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.
A data scientist is using OCI Generative AI to process a large batch of legal documents. The total cost is higher than expected. Which factor is most likely the primary driver of cost?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Clue:
"primary"Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
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 total number of tokens processed (input + output)
In OCI Generative AI, pricing is primarily based on the total number of tokens processed, which includes both input (prompt) and output (generated) tokens. Processing large batches of legal documents generates high token counts due to lengthy text inputs and verbose outputs, directly increasing cost. The number of API requests alone does not determine cost—a single request with many tokens costs more than many requests with few tokens.
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.
- ✗
The number of API requests made
Why it's wrong here
While request count matters, token count per request is usually the dominant cost factor for long documents.
- ✓
The total number of tokens processed (input + output)
Why this is correct
Pricing is typically per token; longer documents mean more tokens and higher cost.
Clue confirmation
The clue words "most likely", "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
The choice of sampling strategy (e.g., top-k vs greedy)
Why it's wrong here
Sampling strategy affects output quality but not token pricing.
- ✗
The latency of the inference endpoint
Why it's wrong here
Latency does not directly affect cost; token count does.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that API request count is the primary cost driver, when in reality token-based pricing means a single large request can cost more than hundreds of tiny requests.
Trap categories for this question
Command / output trap
Sampling strategy affects output quality but not token pricing.
Detailed technical explanation
How to think about this question
Tokenization in OCI Generative AI uses subword tokenization (e.g., Byte-Pair Encoding), where a single word may be split into multiple tokens, and whitespace and punctuation also count. For legal documents with dense legalese and long paragraphs, token counts can be 2-3x higher than word counts, amplifying costs. Additionally, output tokens are often priced higher than input tokens in some models, so verbose model responses can disproportionately increase the bill.
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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LLM Fundamentals — study guide chapter
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FAQ
Questions learners often ask
What does this 1Z0-1127 question test?
LLM Fundamentals — This question tests LLM Fundamentals — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The total number of tokens processed (input + output) — In OCI Generative AI, pricing is primarily based on the total number of tokens processed, which includes both input (prompt) and output (generated) tokens. Processing large batches of legal documents generates high token counts due to lengthy text inputs and verbose outputs, directly increasing cost. The number of API requests alone does not determine cost—a single request with many tokens costs more than many requests with few tokens.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely", "primary". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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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