Exam NCP-AII Topic 1 Question 110 Discussion

Actual exam question for NVIDIA's NCP-AII exam
Question #: 110
Topic #: 1

You have an NVIDIAAIOO GPU and need to configure it for optimal performance across two distinct AI workloads: a large language model (LLM) training job and a computer vision inference service. The LLM benefits from maximum memory bandwidth, while the inference service requires low latency and high throughput. Which MIG configuration would best suit this scenario?

A. Create two 7g.80gb MIG instances, one for each workload. B. Create one 14g.160gb MIG instance for the LLM and use CUDA MPS to multiplex the inference service. C. Create a single full-GPU instance and use Kubernetes resource quotas to isolate the workloads. D. Create one log. 120gb instance for the LLM and one 4g.40gb instance for inference. E. Utilize Time-Slicing on a single full-GPU instance, allocating specific time slots to each workload using NVIDIA Vgpu technology

Suggested Answer: D Vote an answer

Creating a log. 120gb instance for the memory-intensive LLM and a 4g.40gb instance for the inference service provides dedicated resources that cater to the specific needs of each workload, without the overhead or limitations of CUDA MPS or Kubernetes resource quotas. Option A is too conservative, potentially limiting the LLM performance. Option B sacrifices dedicated resources for inference, which may hurt latency. Option C does not leverage MIG and does not guarantee resource isolation and performance consistency. Option E introduces complexities associated with Time-Slicing and might not be suitable for real-time processing.

by Leona at Feb 11, 2026, 03:00 AM

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