Question 27
Domain 3: NVIDIA Tools, Performance, and DeploymentIn production LLM deployment, what is the most critical consideration for cost optimization?
Correct answer: B
Explanation
Cost optimization in production LLM deployment depends on tradeoffs among model quality, response time, and infrastructure spend. The key is to "balance performance, latency, and computational costs" so the system meets user needs without wasting compute or slowing responses.
Why each option is right or wrong
A. Model accuracy only
B. Balancing performance, latency, and computational costs
In production deployments, the governing constraint is not a single metric but the joint optimization of model quality, response time, and infrastructure spend; the practical target is to keep inference within acceptable latency while avoiding unnecessary GPU/CPU utilization. Because no statute or regulation applies here, the correct choice is the one that reflects the standard engineering tradeoff among accuracy, latency, and compute cost rather than maximizing any one dimension in isolation.
C. Using the largest available model
D. Maximum throughput regardless of cost