Release Notes#
These release notes describe NVIDIA AI Enterprise Infrastructure Release 4.9. Use them to identify the supported infrastructure software components and versions in this release, review compatibility and support information, and locate the per-component release notes for new features, fixed issues, and known limitations.
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 Support Matrix or the interactive support matrix linked under Compatibility and Support.
Latest Release Highlights
Multi-Architecture GPU Support - GPU Data Center Driver 535.288.01 with support for Blackwell, Hopper, Ada Lovelace, and Ampere GPU architectures.
NVSwitch Fabric Management - NVIDIA Fabric Manager 535.288.01 enables high-bandwidth, low-latency GPU-to-GPU communication for multi-GPU AI workloads
Enhanced vGPU Virtualization - vGPU for Compute 16.13 with improved MIG-backed vGPU configurations and enhanced live migration capabilities
Kubernetes Automation - GPU Operator 25.10.1 and Network Operator 25.10.0 for streamlined GPU infrastructure management
High-Performance Networking - DOCA-OFED Driver 3.2.0 for enhanced networking and infrastructure acceleration
Enterprise Management - Base Command Manager 11.31.0 for cluster provisioning and workload orchestration at scale
What is Included in NVIDIA AI Enterprise Infra 4.9#
Complete list of infrastructure components with versions and documentation links:
Product |
Description |
Version |
|---|---|---|
NVIDIA GPU Data Center Driver |
Latest GPU driver with Blackwell, Hopper, Ada Lovelace, and Ampere architecture support |
|
NVIDIA Fabric Manager |
Manages NVSwitch fabric to enable high-bandwidth, low-latency GPU-to-GPU communication for multi-GPU AI workloads |
|
NVIDIA DOCA-OFED Driver for Networking |
High-performance networking for InfiniBand and Ethernet |
|
NVIDIA vGPU for Compute (Virtual GPU Manager and Guest Drivers) |
Enterprise GPU virtualization with advanced monitoring and management capabilities, enabling multiple VMs to run AI workloads with near bare metal performance |
|
NVIDIA Container Toolkit |
GPU-accelerated container runtime with enhanced security |
|
NVIDIA GPU Operator |
Automated GPU software lifecycle management for Kubernetes |
|
NVIDIA Network Operator |
Streamlined networking for GPU workloads in Kubernetes |
|
NVIDIA Base Command Manager (BCM) |
Enterprise cluster provisioning, workload orchestration, and lifecycle management |
Compatibility and Support#
Refer to the Support Matrix for:
Supported GPU architectures
Operating system compatibility
Hypervisor and orchestration platform versions
Cloud provider instance types
Networking hardware