The answer is to use a real-time endpoint with an instance that has sufficient memory. This is the correct choice because deploying a large model that requires 16 GB of memory demands a dedicated instance with enough RAM to load the entire model into memory, avoiding the resource contention and swapping that would occur with shared hosting options. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of how to deploy large models while minimizing inference latency, often by contrasting real-time endpoints with serverless, batch, or asynchronous options. A common trap is assuming serverless inference can handle large models, but its 6 GB memory limit and cold starts make it unsuitable for latency-sensitive workloads. Remember: for large models needing low latency, go real-time and right-size the instance—think "big model, big instance, no sharing."
MLS-C01 Modeling Practice Question
This MLS-C01 practice question tests your understanding of modeling. 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 Amazon SageMaker to deploy a custom model container. The model is a large transformer that requires 16 GB of memory. The scientist wants to minimize inference latency. Which SageMaker hosting option should they choose?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use a real-time endpoint with an instance that has sufficient memory.
Option B is correct because multi-model endpoints allow multiple models to share resources, but for a single large model, a real-time endpoint with a suitable instance is best. Option A is wrong because serverless inference has memory limits (up to 6 GB) and may cold start. Option C is wrong because batch transform is for offline. Option D is wrong because asynchronous inference introduces latency for processing requests.
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.
✓
Use a real-time endpoint with an instance that has sufficient memory.
Why this is correct
Real-time endpoints provide low latency and can accommodate large models.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use an asynchronous inference endpoint.
Why it's wrong here
Asynchronous adds latency for queuing and processing.
✗
Use SageMaker Serverless Inference.
Why it's wrong here
Serverless has memory limits up to 6 GB, insufficient for 16 GB model.
✗
Use a batch transform job.
Why it's wrong here
Batch transform is for offline inference, not real-time.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a real-time endpoint with an instance that has sufficient memory. — Option B is correct because multi-model endpoints allow multiple models to share resources, but for a single large model, a real-time endpoint with a suitable instance is best. Option A is wrong because serverless inference has memory limits (up to 6 GB) and may cold start. Option C is wrong because batch transform is for offline. Option D is wrong because asynchronous inference introduces latency for processing requests.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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