CCDV-F Claude API Mechanics Practice Question
A developer is using the Anthropic Messages API and wants to ensure that Claude's response is deterministic and reproducible for a given prompt. They set the temperature parameter to 0. However, they observe that repeated calls with the same input sometimes yield slightly different outputs. Which factor is the most likely cause of this non-determinism?
⚠ Common exam trap
The trap here is assuming that temperature 0 guarantees identical outputs, overlooking that hardware-level non-determinism can still cause slight variations.
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 model's internal computations involve non-deterministic operations such as floating-point arithmetic or parallel processing.
Even with temperature set to 0, which makes the model choose the most probable next token, the underlying probability distribution can vary slightly between calls due to non-deterministic operations in the model's execution on distributed hardware. This includes floating-point arithmetic order and parallel processing. The API does not provide a seed parameter to enforce determinism. Therefore, the most likely cause is the model's internal non-determinism, not misconfiguration of temperature or top_p.
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 model's internal computations involve non-deterministic operations such as floating-point arithmetic or parallel processing.
Why this is correct
Large language models like Claude run on distributed hardware and may use non-deterministic algorithms for efficiency, such as asynchronous floating-point operations or parallel reductions. Even with temperature 0, which selects the most likely token, the probability distribution itself can vary slightly due to these hardware-level nondeterminisms, leading to occasional different tokens. This is a known limitation.
- ✗
The API automatically injects a random seed into each request unless one is explicitly provided.
Why it's wrong here
The Anthropic Messages API does not automatically inject a random seed. There is no seed parameter available in the API to control randomness. Therefore, this cannot be the cause. The non-determinism arises from other factors, not from an implicit seed. Developers cannot set a seed to enforce determinism, so this option is incorrect.
- ✗
The top_p parameter is set to a value less than 1, introducing randomness even with temperature 0.
Why it's wrong here
While top_p can introduce randomness, if it is set to 1 (the default), it does not cause non-determinism. The scenario does not mention top_p being changed. Even if top_p is less than 1, temperature 0 would still make the sampling greedy, so top_p would have no effect. Thus, top_p is not the likely cause here.
- ✗
The temperature parameter is ignored when set to 0, and the default temperature is used instead.
Why it's wrong here
The temperature parameter is respected when set to 0; it is not ignored. Setting temperature to 0 makes the model more deterministic by reducing randomness in sampling. However, it does not guarantee identical outputs across calls due to other factors. The non-determinism is not because temperature is ignored, but because of inherent model behavior or other parameters.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Anthropic exam blueprint
This CCDV-F practice question is part of Courseiva's free Anthropic 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 CCDV-F exam.