- A
n1-standard-4
Why wrong: CPU-only machine type.
- B
e2-standard-4
Why wrong: E2 is a general-purpose CPU-only family.
- C
a2-highgpu-1g (with A100 GPU)
Correct. This is a GPU-enabled machine type suitable for model inference.
- D
n1-highmem-8
Why wrong: CPU-only machine type.
Question 375 of 1,000
PMLE Serving and Scaling Models Practice Question
This PMLE practice question tests your understanding of serving and scaling models. 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.
You want to deploy a TensorFlow model to a Vertex AI endpoint and enable online predictions. The model requires GPU for inference. Which machine type should you select when deploying the model?
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
✓
a2-highgpu-1g (with A100 GPU)
Option C is correct because the a2-highgpu-1g machine type is specifically designed for GPU-accelerated workloads on Vertex AI, featuring an NVIDIA A100 GPU that meets the inference requirements of a TensorFlow model. Vertex AI online prediction endpoints require a machine type that supports GPU attachment, and the A2 series is the only option among the choices that provides a dedicated GPU for inference.
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.
- ✗
n1-standard-4
Why it's wrong here
CPU-only machine type.
- ✗
e2-standard-4
Why it's wrong here
E2 is a general-purpose CPU-only family.
- ✓
a2-highgpu-1g (with A100 GPU)
Why this is correct
Correct. This is a GPU-enabled machine type suitable for model inference.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
n1-highmem-8
Why it's wrong here
CPU-only machine type.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume any standard machine type (like n1 or e2) can be used with a GPU by simply attaching one later, but the question specifically asks for the machine type to select, and only the A2 series provides an integrated GPU option for Vertex AI endpoints.
Detailed technical explanation
How to think about this question
Vertex AI online prediction endpoints allocate machine resources at deployment time; selecting a machine type without a GPU will cause the model to fail if it attempts to use GPU ops (e.g., TensorFlow operations placed on '/device:GPU:0'). The A2 series uses NVIDIA A100 GPUs with high-bandwidth memory and Tensor Cores, which are optimized for deep learning inference, and the '1g' suffix indicates a single GPU configuration. In practice, you must also ensure the model's serving container has the appropriate CUDA and cuDNN libraries to leverage the GPU.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
- →
Serving and Scaling Models — study guide chapter
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FAQ
Questions learners often ask
What does this PMLE question test?
Serving and Scaling Models — This question tests Serving and Scaling Models — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: a2-highgpu-1g (with A100 GPU) — Option C is correct because the a2-highgpu-1g machine type is specifically designed for GPU-accelerated workloads on Vertex AI, featuring an NVIDIA A100 GPU that meets the inference requirements of a TensorFlow model. Vertex AI online prediction endpoints require a machine type that supports GPU attachment, and the A2 series is the only option among the choices that provides a dedicated GPU for inference.
What should I do if I get this PMLE 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.
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