NCP-AIO Installation and Deployment Practice Question
Which NVIDIA tool allows you to verify that the GPU and its driver are properly installed and functioning on a Linux system?
⚠ Common exam trap
Candidates often confuse nvidia-smi with higher-level management tools like NVIDIA AI Enterprise or DCGM. They overlook that nvidia-smi is the fundamental, low-level command for basic driver and hardware verification.
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
✓
nvidia-smi
The 'nvidia-smi' (System Management Interface) tool is the standard utility for interacting with the NVIDIA driver. It provides a real-time status of GPU utilization, temperature, memory usage, and driver versions. Being proficient with this tool is essential for an AI Ops professional to quickly validate hardware health, confirm driver installation, and identify if a GPU is accessible by the host OS after a fresh installation or reboot.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
nvcc --version
Why it's wrong here
The 'nvcc' utility is the NVIDIA CUDA Compiler. It only checks the installed version of the compiler, not the health or presence of the physical GPU hardware or the status of the installed kernel driver. It is used for building code, not for system-level hardware management or driver validation.
- ✓
nvidia-smi
Why this is correct
This command is the primary tool for verifying that the NVIDIA driver is loaded and communicating correctly with the GPU. It provides essential diagnostic information, including device names, driver versions, and current memory usage, which are the fundamental metrics for confirming that a GPU installation was successful.
- ✗
lspci | grep nvidia
Why it's wrong here
While 'lspci' confirms that the hardware is physically present on the PCIe bus, it does not tell you if the NVIDIA driver is correctly installed or functional. It only verifies physical connectivity at the hardware level, leaving the driver-software handshake entirely unverified, which is insufficient for AI infrastructure validation.
- ✗
docker run --gpus all
Why it's wrong here
This command tests the container runtime's ability to access GPUs but is not a native tool for verifying the underlying host driver health itself. If this command fails, you still need 'nvidia-smi' to determine if the driver is the problem or if the issue lies with the container toolkit configuration.
About these practice questions
Courseiva writes every NCP-AIO question from scratch — 309 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
This NCP-AIO practice question is part of Courseiva's free NVIDIA 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 NCP-AIO exam.