NVIDIA AI Enterprise Software
Type: Software Catalog Tags: NVIDIA, AI Enterprise, software catalog, application layer, infrastructure layer, NGC, support matrix Related: NVIDIA-AI-Enterprise, NVIDIA-AI-Enterprise-Quick-Start-Guide, NVIDIA-AI-Enterprise-Lifecycle-Policy, NVIDIA-AI-Enterprise-Infrastructure-Support-Matrix, NGC, NVIDIA-NGC-Catalog, NVIDIA-NIM, NVIDIA-NeMo, NVIDIA-Omniverse, NVIDIA-Run-ai, NVIDIA-Run-ai-Support-and-Lifecycle, NVIDIA-RAPIDS, RAPIDS-Accelerator-for-Apache-Spark, NVIDIA-FLARE, TensorRT, Triton-Inference-Server, PyTorch, NVIDIA-Riva, NVIDIA-TAO, NVIDIA-DeepStream, NVIDIA-Holoscan, Morpheus, NVIDIA-Data-Center-GPU-Drivers, NVIDIA-DOCA, NVIDIA-DOCA-Platform-Framework, NVIDIA-vGPU, NVIDIA-vGPU-for-Compute, NVIDIA-MIG, NVIDIA-Container-Toolkit, NVIDIA-GPU-Operator, NVIDIA-Network-Operator, NVIDIA-NIM-Operator, NVIDIA-Base-Command-Manager, NVIDIA-Enterprise-Support-and-Services Sources: https://docs.nvidia.com/ai-enterprise/software/latest/overview.html, https://docs.nvidia.com/ai-enterprise/software/latest/application-software.html, https://docs.nvidia.com/ai-enterprise/software/latest/infrastructure-software.html, https://docs.nvidia.com/ai-enterprise/index.html Last Updated: 2026-04-30
Summary
NVIDIA AI Enterprise Software is the current NVIDIA catalog of AI Enterprise application-layer and infrastructure-layer components. It describes the composable AI Enterprise stack, links components to NGC catalog entries and product docs, explains independent application/infrastructure release cadences, and points administrators to infrastructure support matrices and release notes for deployment compatibility.
Detail
Purpose
Use this page to answer “what is included in NVIDIA AI Enterprise?” at the software-catalog level. Use NVIDIA-AI-Enterprise for the platform overview, NVIDIA-AI-Enterprise-Lifecycle-Policy for branch support and compatibility timelines, and NVIDIA-Enterprise-Support-and-Services for support entitlements and case workflows.
Layer model
- Application Development includes NIM microservices, NeMo tooling, Omniverse libraries, AI frameworks, ML libraries, domain SDKs, and pre-trained models built on CUDA-X and CUDA.
- Infrastructure Management includes GPU drivers, networking drivers, Kubernetes operators, vGPU, MIG, Run:ai self-hosted, Container Toolkit, DOCA components, and Base Command Manager.
- The two layers have independent release cadences so organizations can adopt new application capabilities without replacing validated infrastructure.
- Components include enterprise support with SLAs, security patches, and maintenance updates when used under the AI Enterprise support model.
- NGC is the distribution and catalog surface for supported software components, while some infrastructure software is supported but obtained through support portals, licensing portals, partner channels, or vendor channels.
Application layer
The current application-layer table includes catalog and documentation entries for inference/deployment, AI frameworks and libraries, domain SDKs/toolkits, and pre-trained models. Durable wiki connections include NVIDIA-NIM, TensorRT, Triton-Inference-Server, NVIDIA-NeMo, PyTorch, NVIDIA-RAPIDS, RAPIDS-Accelerator-for-Apache-Spark, NVIDIA-FLARE, NVIDIA-Riva, NVIDIA-TAO, NVIDIA-DeepStream, NVIDIA-Holoscan, Morpheus, NVIDIA-Omniverse, and model/NIM pages such as NIM-for-Large-Language-Models.
Infrastructure layer
The current infrastructure-layer table includes NGC catalog resources, core GPU/networking drivers, DOCA microservices, virtualization, container platform tooling, GPU orchestration, and Kubernetes operators. Durable wiki connections include NVIDIA-Data-Center-GPU-Drivers, NVIDIA-DOCA, NVIDIA-DOCA-Platform-Framework, NVIDIA-vGPU, NVIDIA-MIG, NVIDIA-Container-Toolkit, NVIDIA-Run-ai, NVIDIA-GPU-Operator, NVIDIA-Network-Operator, NVIDIA-NIM-Operator, and NVIDIA-Base-Command-Manager.
NVIDIA context
The software catalog is a map, not an installation guide. Use deployment-specific pages for bare metal, VMware, cloud, and Red Hat OpenShift installation paths; use the lifecycle policy to decide branches and validate compatibility; use NGC pages for artifact discovery.
Connections
- NVIDIA-AI-Enterprise - parent platform that includes this software catalog.
- NVIDIA-AI-Enterprise-Quick-Start-Guide - account activation, NGC access, and first software installation path that leads into this catalog.
- NVIDIA-AI-Enterprise-Lifecycle-Policy and NVIDIA-AI-Enterprise-Infrastructure-Support-Matrix - define branch timelines and validate supported infrastructure combinations for software layers.
- NGC and NVIDIA-NGC-Catalog - catalog/distribution path for AI Enterprise application and infrastructure software.
- NVIDIA-NIM, NVIDIA-NeMo, TensorRT, and Triton-Inference-Server - core application-layer inference and model development components.
- NVIDIA-RAPIDS and RAPIDS-Accelerator-for-Apache-Spark - accelerated data science, analytics, ML, and Spark data-engineering components.
- NVIDIA-FLARE - federated learning and privacy-preserving collaboration SDK adjacent to healthcare, edge, and regulated AI workflows.
- NVIDIA-Omniverse - application-layer physical AI, digital twin, and OpenUSD component now included in AI Enterprise software documentation.
- NVIDIA-Riva, NVIDIA-TAO, NVIDIA-DeepStream, NVIDIA-Holoscan, and Morpheus - domain SDK/toolkit examples from the application layer.
- NVIDIA-Data-Center-GPU-Drivers, NVIDIA-DOCA, NVIDIA-vGPU, NVIDIA-vGPU-for-Compute, NVIDIA-MIG, and NVIDIA-Container-Toolkit - infrastructure-layer runtime, virtualization, and driver foundations.
- NVIDIA-Run-ai and NVIDIA-Run-ai-Support-and-Lifecycle - self-hosted GPU orchestration component and its product support/lifecycle companion.
- NVIDIA-GPU-Operator, NVIDIA-Network-Operator, and NVIDIA-NIM-Operator - Kubernetes operators in the infrastructure layer.
- NVIDIA-Base-Command-Manager - cluster provisioning/management software supported for AI Enterprise deployments but not distributed through NGC.
- NVIDIA-Enterprise-Support-and-Services - support entitlement and case handling for supported AI Enterprise software components.
Source Excerpts
- The software overview describes AI Enterprise as a two-layer stack with independent release cadences.
- The application-layer page lists NIM, TensorRT, Triton, CUDA Deep Learning, NeMo, PyTorch, RAPIDS, domain SDKs, Omniverse, Riva, TAO, and pre-trained models.
- The infrastructure-layer page lists drivers, DOCA, vGPU for Compute, Container Toolkit, Run:ai, GPU Operator, Network Operator, NIM Operator, support matrices, and infrastructure release notes.