An administrator is deploying the required infrastructure on-premise using NKP on Nutanix to install NAI.

Comprehensive and Detailed Explanation From Exact Extract of Nutanix Artificial Intelligence documents knowledge without any external URL or links:

When deploying Nutanix Enterprise AI (NAI) on the Nutanix Kubernetes Platform (NKP), the storage architecture requires specific protocols for different types of data.

Model Repository Storage:For the storage of Large Language Models (LLMs)—whether they are pre-validated models downloaded from public hubs or custom models imported manually—the platform requires aReadWriteMany (RWX)compatible storage class.

Protocol Selection:The documentation explicitly mandates the creation of anNFS(Network File System) export (specifically NFS v4 is often recommended) on a Nutanix Files server to fulfill this RWX requirement.

Deployment Workflow:During the infrastructure setup, the administrator must create a storage class that dynamically or statically provisions these NFS shares. This allows multiple pods (such as inference servers and model managers) to access the heavy model files simultaneously across different nodes in the Kubernetes cluster.

Why not others:

Blockstorage (ReadWriteOnce) is used for internal components like the database (nai-db) and logging, but it cannot support the shared access required for the model repository.

CIFS(SMB) is not the standard protocol used for Kubernetes RWX Persistent Volumes in this specific NAI deployment workflow.