Nutanix NCP-AI Practice Exam Questions & Answers
7 Free Questions
· Last reviewed: October 28, 2026
· Prepared & Reviewed by the ValidExamDumps Editorial Team
Exam Facts
Nutanix NCP-AI Exam Details
Key details for this exam, checked against the published exam outline
75
Practice Questions (Our Bank)
120 minutes
Exam Duration
70%
Passing Score
USD 165
Official Exam Fee (United States)
- Exam Code
- NCP-AI
- Full Name
- Nutanix Certified Professional - Artificial Intelligence v6.10
- Issuing Body
- Nutanix
- Question Format (Our Bank)
- Multiple Choice
- Delivery
- Online proctored or at a PSI testing center
- Eligibility
- At least three years of virtual infrastructure experience, one year of experience with cloud native technologies and Linux command-line interface (CLI), foundational knowledge of virtual machines, hypervisors, and virtual networking, knowledge of NCI clou
- Validity
- 3 years
Practice Questions
Free NCP-AI Practice Questions
Each question shows the correct answer and an explanation of why it is right
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An administrator is setting up Nutanix Enterprise AI with a custom domain (ai.company.com) and must comply with security policies requiring a valid TLS certificate from the corporate certificate authority (CA).
Which two steps are necessary to complete this configuration successfully? (Choose two.)
Correct Answer:
A, C
Explanation
Before creating an API key in Nutanix Enterprise AI, you must first create an endpoint. The endpoint is the interface that serves your model and generates the authentication credentials needed for API access. Without an active endpoint, there is nowhere to attach or generate the API key for client applications to use.
A data-science team wants to test an unvalidated Hugging Face model within the NAI DashboarD.
Which option lets them onboard it?
Correct Answer:
D
Explanation
When one GPU node is at 100% utilization while others are underutilized, the workload is unbalanced. Rebuilding the endpoint with multiple instances spreads the inference requests across more resources. This reduces the load on the bottlenecked node and improves overall latency. The Critical Service Health status confirms that the current configuration cannot handle the demand.
An AI/ML administrator has been contacted by an endpoint owner who advises that one of their endpoints is not working properly anymore suggesting the API key has been removeD. The AI/ML administrator can see that the API key is no longer listed under the endpoint.
What filter under the Audit Events page can the AI/ML administrator use to help understand what has happened?
Correct Answer:
B
Explanation
The GPU GB license is required to create an inference endpoint in Nutanix Enterprise AI. This license type specifically governs the ability to deploy and run inference endpoints that consume GPU resources. Other license types may cover different functionalities, but GPU GB is the specific license needed for inference endpoint creation and operation.
An administrator has been ask to troubleshoot the import of a new NIM LLM in NAI. The import Status is Pending.
What could be the most common issue?
Correct Answer:
D
Explanation
OpenAI compatible clients require a valid API key to authenticate requests to the endpoint. If the API key has been removed from the endpoint configuration, clients will fail to authenticate and cannot access it. The key must be present and properly configured on the endpoint for compatibility clients to establish a successful connection.
An administrator is deploying the required infrastructure on-premise using NKP on Nutanix to install NAI.
Which type of storage should be created during the deployment process to save the models?
Correct Answer:
C
Explanation
When an endpoint creation process remains in Pending status, it typically indicates that the system cannot allocate the resources requested. If the endpoint configuration requires a specific number of GPUs and those GPUs are not available across the cluster, the endpoint creation will not complete. The system waits in Pending state until sufficient resources become available or the configuration is adjusted.
Which Nutanix AI deployment platform is supported?
Correct Answer:
C
Explanation
To set up a custom domain with proper TLS security, you need two things. First, add a DNS A record that maps the custom domain name to the NAI system IP address so clients can resolve it. Second, you need a valid CA-signed TLS certificate for that domain to enable secure HTTPS connections. Both are required to complete a compliant configuration.
Refer to the exhibit
An administrator needs to troubleshoot an import failure from a AI/ML user and does not have the admin right to try to do a manual upload of LLM.
What is the cause of the import failure?
Correct Answer:
D
Explanation
The endpoint works correctly within NAI and returns accurate responses when tested. The developers are getting 400 Bad Request errors, which suggests a formatting or request structure problem. The Sample Request code from the endpoint shows exactly how the API expects requests to be formatted. Providing this code ensures developers use the correct syntax and payload structure that matches what the endpoint requires.
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Domain 1: Deploy a Nutanix Enterprise AI Environment
Validate installation prerequisites and verify system requirements before deployment. Install Nutanix Enterprise AI components including container runtimes and Kubernetes distributions. Configure DNS, establish and manage SSL/TLS certificates, and set up application URLs to ensure secure and reliable access to the AI platform.
Sample question from this domain above:
Q6
Domain 2: Configure a Nutanix Enterprise AI Environment
Onboard users to Nutanix Enterprise AI with appropriate role-based access. Import Large Language Models and manage their availability within the system. Create API endpoints for application integration and generate secure API keys for endpoint authentication and access control.
Sample questions from this domain above:
Q1Q3
Domain 3: Perform Day 2 Operations
Prepare infrastructure and networking requirements for application connectivity. Review performance metrics and make optimization decisions based on resource utilization and response times. Monitor access logs and usage patterns to identify anomalies and select appropriate models to improve output quality.
Sample question from this domain above:
Q2
Domain 4: Troubleshoot a Nutanix Enterprise AI Environment
Identify and resolve performance bottlenecks and resource contention issues. Run and interpret health checks to identify cluster problems and apply appropriate remediations. Address failures during model import and endpoint creation by analyzing logs and error messages.
Sample question from this domain above:
Q5
Domain 5: Connect Applications to a Nutanix Enterprise AI Environment
Configure applications to communicate with Nutanix Enterprise AI endpoints using appropriate authentication and network settings. Validate endpoint functionality and monitor metrics that correspond to application requests and usage patterns.
Sample questions from this domain above:
Q4Q7
FAQ
NCP-AI Exam FAQ
Common questions about the exam itself
What background and experience do I need to take the NCP-AI exam?
You need at least three years of virtual infrastructure experience and one year working with cloud native technologies and Linux command-line tools. You should also have foundational knowledge of virtual machines, hypervisors, virtual networking, GPUs, and Kubernetes at a CKA certification level.
What does the NCP-AI exam actually test?
The exam measures your ability to install, configure, optimize, and troubleshoot Nutanix Enterprise AI, as well as integrate generative AI applications and agents with the platform. You will be tested on deployment, configuration, operations, troubleshooting, and application integration.
How is the NCP-AI exam delivered?
You can take the exam remotely with online proctoring or in person at a PSI testing center. Scheduling opened on November 11, 2025.
Which objective area in NCP-AI is most challenging for candidates?
Troubleshooting Nutanix Enterprise AI environments tends to be difficult because it requires understanding both the platform architecture and how to interpret performance data and logs to diagnose complex issues. Hands-on lab experience with actual troubleshooting scenarios is essential preparation for this domain.
How long should I prepare for the NCP-AI exam?
Most candidates benefit from three to four months of focused study combining hands-on experience with Nutanix Enterprise AI, completion of the official Nutanix Enterprise AI Administration course, and regular practice with exam-style questions. Your preparation timeline depends on your existing Kubernetes and cloud infrastructure background.
What does exam day look like for NCP-AI?
If taking the exam remotely, you must use a secure browser and ensure your test environment meets PSI requirements including camera, microphone, and clear desk space. At a testing center, you will follow standard proctoring procedures. Be prepared to verify your identity and check in before the exam begins.
Can I retake the NCP-AI exam if I fail?
Nutanix follows standard industry retake policies through PSI. Most vendors allow retakes after a waiting period. Check the PSI or Nutanix website for current retake scheduling rules and any applicable fees at the time you attempt the exam.
How long is the NCP-AI certification valid?
Nutanix certifications typically maintain a validity period, though the specific duration for NCP-AI should be confirmed on the official exam page or with Nutanix directly as this information may not be publicly listed.
What job roles are best suited for the NCP-AI certification?
The NCP-AI certification is ideal for IT administrators, AI and machine learning administrators, platform engineers, and DevOps professionals who deploy and manage enterprise AI solutions on Nutanix infrastructure. It validates expertise needed for roles managing production AI workloads.
How does NCP-AI relate to other Nutanix certifications?
NCP-AI is part of the Nutanix Certified Professional track alongside NCP-MCI, NCP-EUC, and others. It is specialized for AI platform management, while NCP-MCI covers broader infrastructure management. You may pursue both certifications to demonstrate comprehensive infrastructure and AI platform expertise.
