NVIDIA AI Enterprise is a suite of NVIDIA software that is portable across the cloud, data center, and edge. The software is designed to deliver optimized performance, robust security, and stability for development and production AI use cases. It consists of two types of software: Application Software for building AI agents, generative AI, and many other types of AI workflows, and Infrastructure Software such as NVIDIA GPU and Networking drivers and Kubernetes Operators to help optimize and manage the use of hardware accelerators by AI, data science, and HPC applications.
Application Software
- NVIDIA NIM and NVIDIA NeMo microservices enhance model performance and speed time to deployment for generative AI.
- SDKs, frameworks, and libraries across many domains, including speech AI, route optimization, cybersecurity, and vision AI.
- Inference and training runtimes including NVIDIA Triton Inference Server, with multiple optimized backends.
Infrastructure Software
- Kubernetes operators for deployment and lifecycle management, including NVIDIA GPU Operator, NVIDIA Network Operator, NVIDIA DOCA Platform Framework (DPF) DPU Operator, and NVIDIA NIM Operator.
- NVIDIA GPU and NVIDIA Network drivers to run in bare metal or virtualized configurations.
- Base Command Manager to streamline cluster provisioning and infrastructure monitoring.
Customers who build AI applications or operate AI Infrastructure can use whichever parts of the suite that they wish. NVIDIA has partnered with leading industry partners to ensure integration of NVIDIA software with their platform.
NVIDIA software is available across different branches to meet the needs of individual use cases.
| Software Layer | Description | Components Included | Support Matrix | Documentation |
| Infrastructure Software | Infrastructure software includes components for deploying, managing, and scaling AI applications. | Infrastructure Software | Infra Support Matrix | Infra Lifecycle Documentation |
| Application Software: Feature Branch | Feature Branches (FB) deliver the latest NVIDIA-built and NVIDIA-optimized AI frameworks, NVIDIA NIM microservices, pre-trained models, and SDKs with recent features and optimizations. | Application Feature Branch (FB) Software | Feature Branch (FB) Documentation | Feature Branch (FB) Lifecycle Documentation |
| Application Software: Production Branch | Production Branches (PB) provide production-ready AI frameworks and SDKs with API stability and security for mission-critical applications. | Application Production Branch (PB) Software | Production Branch (PB) Documentation | Production Branch (PB) Lifecycle Documentation |
| Application Software: Long-Term Support Branch | Long-Term Support Branches (LTSB) provide long-term supported AI frameworks and SDKs with 36 months of API stability and security for highly regulated industries. | Application Long Term Supported Branch (LTSB) Software | Long-Term Support Branch (LTSB) Documentation | Long-Term Support Branch (LTSB) Lifecycle Documentation |
Getting Started with NVIDIA AI Enterprise
Explains the NVIDIA AI Enterprise platform architecture, covering the infrastructure and application layers, software components, branch types, and support resources.
Guides you through deploying NVIDIA AI Enterprise in 30-60 minutes, from activating your enterprise account to deploying GPU-accelerated containers and running your first AI workload.
NVIDIA AI Enterprise Licensing and Support Policies
Covers entitlement, packaging, and licensing for NVIDIA Enterprise. Provides a quick reference to understand the product at a high level, including corresponding SKU information.
Explains the NVIDIA AI Enterprise software lifecycle, including release branch types (Feature, Production, LTS, Infrastructure), their support periods, and how to select the right branch for your deployment needs.
Lists End of Life (EOL) and deprecation notices for NVIDIA AI Enterprise software components, including deprecation schedules, final update dates, and migration recommendations.
Covers support and services for potential and existing enterprise customers. Informational and non-binding reference.
Enterprise Services designed to increase uptime and improve ROI for NVIDIA AI Enterprise, including Support Services, Infrastructure Services, and Education Services.
Application Software PB and LTSB Release Documentation
Active Production Branches (PB) and Long-Term Support Branches (LTSB)
| Software Branch | Compatible Infra Release | First Planned Release | Last Planned Release | Planned EOL |
| Production Branch - October 2025 (PB 25h2) | Infra Release 7.x | October 2025 | June 2026 | July 2026 |
| Long-Term Support Branch 2 (LTSB 2) | Infra Release 4.x and 7.x | November 2024 | August 2027 | October 2027 |
All Production Branches (PB) and Long-Term Support Branches (LTSB)
| Software Branch | Compatible Infra Release | First Planned Release | Last Planned Release | Planned EOL |
| Production Branch - May 2025 (PB 25h1) | Infra Release 6.x and 7.x | May 2025 | December 2025 | January 2026 |
| Production Branch - October 2024 (PB 24h2) | Infra Release 5.x and 6.x | October 2024 | June 2025 | July 2025 |
| Production Branch - May 2024 (PB 24h1) | Infra Release 4.x and 5.x | May 2024 | December 2024 | January 2025 |
| Production Branch - October 2023 (PB 23h2) | Infra Release 3.x | October 2023 | June 2024 | July 2024 |
| Long-Term Support Branch 1 (LTSB 1) | Infra Release 1.x | August 2021 | February 2024 | June 2024 |
Application Layer Release Branches
Describes the latest versions of NVIDIA-built and NVIDIA-optimized AI frameworks, NIM microservices, pre-trained models, and SDKs, including monthly release cadence, support timelines, and compatible infrastructure releases.
Lists production-ready AI frameworks and SDKs included in each release, including product versions, release timelines, EOL dates, Government Ready availability, and links to product documentation.
Lists long-term supported AI frameworks and SDKs included in each release, providing 36 months of API stability for highly regulated industries, including product versions, release timelines, EOL dates, and documentation links.
Application Layer Software on NGC
Easy-to-use microservices accelerate generative AI implementation in enterprises. Available exclusively to NVIDIA AI Enterprise Essentials subscribers, backed by NVIDIA's Enterprise support team.
Application Layer Software Documentation
Explains NVIDIA NIM microservices for accelerating foundation model deployment on any cloud or data center, including production-grade runtimes, security updates, deployment guides, API references, and integration options.
Infra Software Release Documentation
The following products are part of NVIDIA AI Enterprise Infrastructure software.
- Core Infrastructure Drivers
- NVIDIA GPU Data Center Driver Container
- NVIDIA Fabric Manager
- NVIDIA DOCA-OFED Driver for Networking
- Virtualization
- NVIDIA vGPU for Compute (Virtual GPU Manager and Guest Drivers)
- Container Platform
- NVIDIA Container Toolkit
- Kubernetes Operators
- NVIDIA GPU Operator
- NVIDIA Network Operator
- NVIDIA DPU Operator (DPF)
- NVIDIA NIM Operator
- Data Center Services
- NVIDIA DOCA Microservices
- Cluster Management and Orchestration
- NVIDIA Base Command Manager (BCM)
Infra Layer Release Branches
Active Infra Release Branches
| Software Branch | Driver Branch | Latest Driver in Branch | Branch | Latest Release in Branch | Latest Release Date in Branch | Branch EOL |
|---|---|---|---|---|---|---|
| NVIDIA AI Enterprise Infra 7.x | R580 | 580.126.09 | Long-Term Support | 7.4 | January 2026 | July 2028 |
| NVIDIA AI Enterprise Infra 6.x | R570 | 570.211.01 | Feature and Production | 6.7 | January 2026 | March 2026 |
| NVIDIA AI Enterprise Infra 4.x | R535 | 535.288.01 | Long-Term Support | 4.9 | January 2026 | July 2026 |
All Infra Release Branches
| Software Branch | Driver Branch | Latest Driver in Branch | Branch | Latest Release in Branch | Latest Release Date in Branch | Branch EOL |
|---|---|---|---|---|---|---|
| NVIDIA AI Enterprise Infra 5.x | R550 | 550.144.02 | Feature and Production | 5.3 | January 2025 | April 2025 |
| NVIDIA AI Enterprise Infra 3.x | R525 | 525.147.05 | Feature and Production | 3.3 | November 2023 | December 2023 |
| NVIDIA AI Enterprise Infra 2.x | R520 | 520.61.05 | Feature | 2.3 | October 2022 | November 2022 |
| NVIDIA AI Enterprise Infra 1.x | R470 | 470.256.02 | Long-Term Support | 1.9 | July 2024 | September 2024 |
Infra Layer Software on NGC
Lists all NVIDIA AI Enterprise supported software available on NGC, including AI frameworks, microservices, pre-trained models, SDKs, and tools with enterprise support.
This catalog page lists NVIDIA AI Enterprise Infrastructure collections available on NGC, including infrastructure software components such as drivers, operators, and management tools for deploying and managing AI workloads.
Infra Layer Softare Documentation
Version 7.4 is the latest release.
Version 6.7 is the latest release.
Version 4.9 is the latest release.
Deployment Guides
This document provides guidance for deploying and running NVIDIA AI Enterprise in the Cloud. This resource can be used for understand system pre-requisites, installation and configuration.
This document provides insights into deploying NVIDIA AI Enterprise for VMware vSphere and serves as a technical resource for understanding system pre-requisites, installation, and configuration.
This document provides insights into deploying NVIDIA AI Enterprise on Bare Metal Servers and serves as a technical resource for understanding system pre-requisites, installation, and configuration.
This document provides insights into deploying NVIDIA AI Enterprise with Red Hat OpenShift on bare metal servers. This technical resource can be used for understanding system pre-requisites, installation, and configuration.
This document provides insights into deploying NVIDIA AI Enterprise with Red Hat OpenShift on VMware vSphere. This technical resource can be used for understanding system pre-requisites, installation, and configuration.
This document provides insights into deploying NVIDIA AI Enterprise on Red Hat Enterprise Linux with KVM Virtualization and serves as a technical resource for understanding system prerequisites, installation, and configuration.
NVIDIA RAPIDS Accelerator for Apache Spark enables data engineers to speed up Apache Spark 3 data science pipelines and AI model training while lowering infrastructure costs.
This guide aims to provide guidance on how to set up a high-performance multi-node cluster as virtual machines. Within this guide, you will become familiar with GPUDirect RDMA and ATS while using Docker as the platform for running high-performance multi-node Deep Learning Training. ATS is a VMware PCIe support enhancement in vSphere 7 Update 2. GPUDirect RDMA benefits from ATS and is certified and supported by NVIDIA AI Enterprise.
This solution guide outlines the creation of an AI pipeline on NVIDIA AI Enterprise by leveraging a Natural Language Processing use case example.
Reference Architecture
This reference architecture provides an example deployment of NVIDIA AI Enterprise software suite. It showcases a deployment with VMWare vShpere, and provides example workloads to showcase the platform’s capabilities. Topics such as hardware, network, and workload topologies will be discussed.
This sizing guide is intended to guide customers who want to implement NVIDIA AI Enterprise with NVIDIA-Certified Systems at scale.
This document outlines a reference architecture for a cost-effective, performant Kubernetes-as-a-Service to build out an infrastructure stack for large-scale AI training and inference workload in virtualized environments.
White Papers
The NVIDIA AI Factory for Government Reference Design is a purpose-built, full-stack architecture that enables federal agencies to deploy secure, scalable AI in mission-critical environments. Designed to meet stringent government requirements, it integrates NVIDIA accelerated computing, high-performance networking, NVIDIA-Certified Systems and Storage, Nemotron models, and NVIDIA AI Enterprise government-ready software with a broad partner ecosystem.
This white paper describes how NVIDIA is helping to accelerate the deployment of AI into government and regulated industries by providing a new secure baseline for NVIDIA AI Enterprise software.
This white paper details NVIDIA's commitment to securing the NVIDIA AI Enterprise software stack. It outlines the processes and measures NVIDIA takes to ensure container security.
This whitepaper outlines the essential components, integration strategies, and tools needed for enterprises to deploy robust, single-tenant AI solutions efficiently and securely with the help of ecosystem partners.
This white paper provides detailed guidance on configuring virtual machines (VMs) to support AI/ML workloads when a hypervisor layer is deployed on top of HGX systems.