How Does Frequency Penalty Reduce Repetition in Azure OpenAI?
A developer uses Azure OpenAI Service to generate long-form articles. The developer notices that the model tends to repeat the same sentence structures and vocabulary, making the output monotonous. Which parameter should the developer increase to reduce this repetition?
Quick Answer
The correct answer is C, increasing the frequency penalty parameter. This works by applying a negative weight to tokens that have already been generated, effectively reducing their probability of being selected again. In Azure OpenAI, the frequency penalty directly targets repetition by scaling down the log-probability of any token based on how often it has already appeared in the output, which forces the model to explore less common words and sentence structures. On the AI-900 exam, this concept tests your understanding of how to control text diversity versus coherence—a common trap is confusing frequency penalty with presence penalty, which penalizes any token that has appeared at least once regardless of frequency. Remember that frequency penalty fights *frequent* repetition, while presence penalty fights *any* repetition. A helpful mnemonic: “Frequency fights the frequent fliers” — the more a word shows up, the harder it is to get picked again.
⚠ Common exam trap
Candidates often confuse the 'frequency penalty' with 'presence penalty' or 'temperature'—candidates often think temperature controls repetition, but it only affects randomness, not the specific suppression of repeated tokens.
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
✓
C
Increasing the 'frequency penalty' parameter (option C) reduces repetition by penalizing tokens that have already appeared in the generated text. This encourages the model to use a wider variety of sentence structures and vocabulary, making the output less monotonous.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A
Why it's wrong here
Temperature controls the randomness of token selection; increasing it makes outputs more creative but does not specifically reduce repetition.
When this WOULD be correct
If the question asked about a different service or a generic concept where 'A' is a placeholder for a correct parameter like 'temperature' in a multiple-choice list, but in this specific Azure OpenAI context, it is incorrect.
- ✗
B
Why it's wrong here
Top_p (nucleus sampling) also controls randomness by limiting token selection to a cumulative probability; it does not directly target repetition.
When this WOULD be correct
If the question were: 'A developer notices the model generates text that repeatedly uses the same rare words. Which parameter should be increased to penalize token frequency?' then increasing 'frequency_penalty' (option B) would be correct.
- ✓
C
Why this is correct
Frequency penalty reduces the likelihood of repeating tokens that have already appeared, making the generated text less repetitive.
- ✗
D
Why it's wrong here
Max_tokens sets the maximum number of tokens in the output and does not affect the diversity or repetition of the content.
When this WOULD be correct
Option D would be correct if the question were: 'A developer uses Azure OpenAI Service to generate text and notices that the model repeatedly uses the same words or phrases. Which parameter should the developer increase to reduce this word-level repetition?'
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The AI-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓CCorrect answer▾
Why this is correct
Frequency penalty reduces the likelihood of repeating tokens that have already appeared, making the generated text less repetitive.
✗AWrong answer — click to see why▾
Why this is wrong here
Option A is not a valid parameter in Azure OpenAI Service; the actual parameter to control repetition is 'frequency_penalty' or 'presence_penalty'.
★ When this WOULD be the correct answer
If the question asked about a different service or a generic concept where 'A' is a placeholder for a correct parameter like 'temperature' in a multiple-choice list, but in this specific Azure OpenAI context, it is incorrect.
Why candidates choose this
Candidates might confuse 'A' with 'temperature' or another common parameter, or they may misread the options and think 'A' refers to a known parameter.
✗BWrong answer — click to see why▾
Why this is wrong here
Increasing the 'B' parameter (likely 'frequency_penalty') would reduce repetition by penalizing tokens that have already appeared, but the question asks for reducing repetition of sentence structures and vocabulary, which is better addressed by increasing 'temperature' or 'top_p' to introduce more randomness. 'B' is not the correct parameter for this specific issue.
★ When this WOULD be the correct answer
If the question were: 'A developer notices the model generates text that repeatedly uses the same rare words. Which parameter should be increased to penalize token frequency?' then increasing 'frequency_penalty' (option B) would be correct.
Why candidates choose this
Candidates may confuse 'frequency_penalty' with 'presence_penalty' or think that penalizing repetition directly addresses the monotony, but the question focuses on structural and vocabulary repetition, which is more about diversity than frequency.
✗DWrong answer — click to see why▾
Why this is wrong here
Increasing the 'frequency penalty' parameter (option D) reduces repetition by penalizing tokens that have already appeared, but the question asks for reducing repetition of sentence structures and vocabulary, which is better addressed by increasing 'temperature' or 'top_p' to introduce more randomness. Option D is not the correct parameter for this specific issue.
★ When this WOULD be the correct answer
Option D would be correct if the question were: 'A developer uses Azure OpenAI Service to generate text and notices that the model repeatedly uses the same words or phrases. Which parameter should the developer increase to reduce this word-level repetition?'
Why candidates choose this
Candidates may confuse 'frequency penalty' with a general repetition-reduction mechanism, not realizing that it specifically targets token-level repetition rather than structural or vocabulary diversity.
Analysis generated from the official AI-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
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Azure Machine Learning Studio
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
Azure OpenAI Service
Azure OpenAI Service is a cloud platform from Microsoft that lets developers use powerful artificial intelligence models, like GPT-4, to build applications that can understand and generate human-like text, code, images, and more.
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Same concept, more angles
1 more way this is tested on AI-900
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A developer uses Azure OpenAI Service to generate product reviews for an e-commerce site. The developer notices that the model often repeats the same phrases within the same review, making the output sound unnatural. Which parameter should the developer adjust to reduce this repetition?
easy- A.Temperature
- B.Top_p
- C.Max_tokens
- ✓ D.Frequency_penalty
Why D: The frequency_penalty parameter reduces the likelihood of the model repeating the same phrases by penalizing tokens that have already appeared in the generated text. A higher frequency_penalty value (e.g., 0.5 to 1.0) discourages the model from reusing the same words or phrases, making the output more diverse and natural. This directly addresses the issue of repetitive phrasing in product reviews.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 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-900 exam.