NVIDIA AI Enterprise 7.7 Release Notes#
These release notes describe NVIDIA AI Enterprise Infrastructure Release 7.7. They summarize what changed from 7.6, identify the supported infrastructure software components and versions in this release, review compatibility and support information, and link to the per-component release notes for new features, fixed issues, and known limitations.
Note
NVIDIA AI Enterprise Infra 7.7 is a Long-Term Support Branch (LTSB), providing extended support for stable production deployments. For branch lifecycle, support windows, and cross-branch migration guidance, refer to the NVIDIA AI Enterprise Lifecycle Policy.
For deployment guidance, refer to the Quick Start Guide. For a full list of supported platforms, hypervisors, operating systems, and orchestration software, refer to the 7.7 Support Matrix or the interactive support matrix in the Compatibility and Support section below. If you are upgrading from 7.6, refer to Upgrading from 7.6 to 7.7.
What is New in 7.7#
NVIDIA AI Enterprise Infra 7.7 is a maintenance update on the R580 Long-Term Support Branch. Only the following components change from 7.6:
Component |
7.6 |
7.7 |
|---|---|---|
NVIDIA Data Center GPU Driver |
580.167.08 |
|
NVIDIA Fabric Manager |
580.167.08 |
580.173.02 |
NVIDIA vGPU for Compute Guest Driver (Linux) |
580.167.08 |
580.173.02 |
NVIDIA vGPU for Compute Guest Driver (Windows) |
582.53 |
582.70 |
All other infrastructure components are unchanged from 7.6, including the NVIDIA Virtual GPU Manager (580.159.01), NVIDIA Run:ai (2.25), DOCA (3.4.0), and the GPU, Network, NIM, and DPU operators. Because the operator versions are unchanged, existing operator deployments do not require reinstallation when you update the driver stack.
For the fixed issues, security updates, and platform-support changes in the updated driver, refer to the NVIDIA Data Center GPU Driver 580.173.02 release notes.
What is Included in NVIDIA AI Enterprise Infra 7.7#
Complete list of infrastructure components with versions and documentation links. For platform-support detail (x86 / ARM / Government Ready), refer to the 7.7 Support Matrix - this release-notes table mirrors the canonical component versions defined there.
Component |
Description |
Version |
|---|---|---|
NVIDIA Data Center GPU Driver |
Provides hardware support for NVIDIA GPUs. |
|
NVIDIA DOCA Driver for Networking |
Provides hardware support for NVIDIA BlueField DPUs and SuperNICs. Installing DOCA on the host provides all necessary drivers and tools to manage BlueField and ConnectX devices. |
|
NVIDIA Fabric Manager |
Manages NVSwitch fabric to enable high-bandwidth, low-latency GPU-to-GPU communication for multi-GPU AI workloads |
|
NVIDIA DOCA Microservices |
Infrastructure acceleration and offload services for NVIDIA BlueField, enabling accelerated networking, storage, and security workloads. |
|
NVIDIA Virtual GPU Manager |
GPU driver deployed alongside the hypervisor in virtualized environments. Enables multi-tenant GPU sharing, live migration, and monitoring. |
|
NVIDIA vGPU for Compute Guest Driver [1] |
GPU driver deployed in the guest VM to enable multiple VMs to have simultaneous, direct access to a single physical GPU. |
|
NVIDIA Container Toolkit |
Enables GPU-accelerated containers by providing runtime components and utilities for container engines (Docker, containerd, CRI-O) |
|
NVIDIA Run:ai |
Provides a Kubernetes-native orchestration and management platform that maximizes GPU utilization for AI workloads through advanced scheduling and resource management. |
|
NVIDIA DPU Operator (DPF) |
Enables cluster administrators to automate provisioning, orchestration, and lifecycle management of BlueField DPUs and DOCA Microservices to enable DPU-accelerated North-South networking in Kubernetes. |
|
NVIDIA GPU Operator |
Simplifies deployment of NVIDIA AI Enterprise by automating management of all NVIDIA software components needed to provision GPUs in Kubernetes. |
|
NVIDIA Network Operator |
Simplifies deployment of high-speed networking by automating management of NVIDIA ConnectX NICs and SuperNICs required to optimize East-West traffic and remote direct memory access (RDMA) transfers in Kubernetes. |
|
NVIDIA NIM Operator |
Enables cluster administrators to operate the software components and services required to run LLM, embedding, and other models using NVIDIA NIM microservices in Kubernetes. |
|
NVIDIA Base Command Manager (BCM) |
Cluster management and provisioning tool for NVIDIA DGX systems. |
Compatibility and Support#
Support Matrix
Use the Interactive Support Matrix to compare NVIDIA AI Enterprise infrastructure compatibility across releases 4.4 through 7.7. The web tool lets you:
Filter by deployment type, operating system, hypervisor, or orchestration platform.
Search by GPU architecture, platform, Kubernetes distribution, or cloud provider.
Inspect per-configuration release badges and footnote tooltips.
For deep linking, printing, or offline reference, the same information is also available as the static 7.7 Support Matrix. Both forms cover supported GPU architectures, operating systems, hypervisor and orchestration platform versions, cloud provider instance types, and networking hardware.
Key support boundaries
The following limits are the most common deployment blockers. For the complete matrix and all footnotes, refer to the 7.7 Support Matrix.
NVIDIA vGPU for Compute on Linux with KVM is supported for single-node deployments only.
NVIDIA Grace Hopper and Grace Blackwell platforms are supported on bare metal only.
GPU Operator is not supported with KubeVirt or OpenShift Virtualization on NVIDIA HGX platforms.
Lifecycle and Compatibility Explorer
Use the Interactive Lifecycle and Compatibility Explorer on the NVIDIA AI Enterprise Lifecycle Policy documentation to:
Query by Infrastructure Branch, by release, or by component type and version.
Run a full-stack check from a GPU driver version to validate compatibility and plan upgrades.
Footnotes