- A
TPU v2-8
Why wrong: Too small for 175B model.
- B
TPU v3-32
Why wrong: v3 is older and less powerful than v5e for large models.
- C
TPU v4-64
Why wrong: v4 is powerful but may be costlier than v5e for equivalent performance.
- D
TPU v5e-256
v5e provides a good balance of performance and cost for large-scale training.
Question 566 of 997
Generative AI Leader Google AI Ecosystem and Strategy Practice Question
This Generative AI Leader practice question tests your understanding of google ai ecosystem and strategy. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 company wants to run a large-scale training job for a 175B parameter model. They need to minimize training time and cost. Which TPU version and configuration 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 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
✓
TPU v5e-256
Option D is correct because the TPU v5e-256 offers the best performance-per-dollar for large-scale training of a 175B parameter model. With 256 chips in a pod, it provides massive parallelism and high memory bandwidth, significantly reducing training time compared to earlier generations while maintaining cost efficiency through optimized architecture.
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.
- ✗
TPU v2-8
Why it's wrong here
Too small for 175B model.
- ✗
TPU v3-32
Why it's wrong here
v3 is older and less powerful than v5e for large models.
- ✗
TPU v4-64
Why it's wrong here
v4 is powerful but may be costlier than v5e for equivalent performance.
- ✓
TPU v5e-256
Why this is correct
v5e provides a good balance of performance and cost for large-scale training.
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume larger chip count alone (like v4-64) is sufficient, but fail to consider the memory capacity per chip and the cost-efficiency of newer generations, leading them to overlook the v5e-256's superior balance of scale and affordability.
Detailed technical explanation
How to think about this question
Under the hood, training a 175B parameter model requires model parallelism (e.g., Megatron-LM or FSDP) across multiple TPU chips, where the v5e-256's 256 chips provide 1.5 TB of aggregate HBM (6 GB per chip) and a 2D torus topology with 1600 Gbps inter-chip links, enabling efficient all-reduce operations. In real-world scenarios, the v5e-256 can achieve near-linear scaling for large models, reducing training time from weeks to days compared to smaller configurations, while its lower per-chip cost makes it the most economical choice for production workloads.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Visual reference
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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FAQ
Questions learners often ask
What does this Generative AI Leader question test?
Google AI Ecosystem and Strategy — This question tests Google AI Ecosystem and Strategy — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: TPU v5e-256 — Option D is correct because the TPU v5e-256 offers the best performance-per-dollar for large-scale training of a 175B parameter model. With 256 chips in a pod, it provides massive parallelism and high memory bandwidth, significantly reducing training time compared to earlier generations while maintaining cost efficiency through optimized architecture.
What should I do if I get this Generative AI Leader 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: "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.
About these practice questions
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Last reviewed: Jul 4, 2026
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