NVIDIA NIM¶
The table below lists the topics included in the NVIDIA NIM section:
| Topic | Description |
|---|---|
| NVIDIA NIM air-gap deployment guide | Describes how to deploy NVIDIA Inference Microservice (NIM) in environments without direct internet connectivity ("air-gapped" clusters) |
| Air-gap cache processing script | Python utility to stage a local NIM cache and optionally upload model profiles to S3-compatible object storage. |
| Air-gap misc configuration | Optional tooling and cluster configuration for air-gapped NIM, including the Crane CLI and Trust Manager public CA bundles. |
| Air-gap troubleshooting | Common errors when running NIM without internet access, with symptoms, causes, and resolutions. |
| NVIDIA NIM configuration | Describes the NVIDIA NIM microservices included in NVIDIA AI Enterprise, which are a set of easy-to-use microservices for accelerating the deployment of foundation models. |
| GPU support matrix | NVIDIA-published minimum and optional GPU configurations validated for each NIM container image and version. |
| GPU resource bundles | How bundle labels map to GPU node types, counts, FP16 throughput, and memory on major managed Kubernetes platforms. |
| GPU bundle validation | Which NIM models are validated or estimated on standard GPU bundles for EKS, AKS, OpenShift, restricted network EKS, and OKE. |