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From the NVIDIA edition of September 18, 2026

Standards or public-body guidanceEmergingUndated source

AI Enterprise Infra 8.2 pins GPU Operator 26.3.3 and NIM Operator 3.1.2 on Production Branch

NVIDIA · Enterprise AI infrastructure software · Global (enterprise support matrix)

NVIDIA
Publisher
NVIDIA AI Enterprise Documentation
Original publication
AI Enterprise Infra 8.2 release notes (current Production Branch docs)
Source retrieved
2026-09-19
Read original source

What happened

NVIDIA AI Enterprise Infrastructure 8.2 release notes identify the Production Branch component set, including Data Center GPU Driver 595.91.07, DOCA networking 3.4.0, Container Toolkit 1.19.1, GPU Operator 26.3.3, Network Operator 26.4.1, DPU Operator 26.4.0, NIM Operator 3.1.2, and Run:ai 2.26. Fabric Manager remains integrated into AI Enterprise drivers since 8.0. The notes point operators to per-component release notes for features, fixes, and known limitations and to the lifecycle policy for PB vs LTSB choices.

Why it matters

Practical pinning guide for SLED platform teams standardizing Kubernetes GPU/NIM stacks—especially alongside Government Ready packaging—without implying a single “8.2 solves deployment” outcome.

Evidence and measured results

Table of supported infrastructure software with versions; PB cadence note; links expectation to lifecycle policy and per-component notes; Fabric Manager inclusion since 8.0 restated.

Limitations and uncertainty

Release notes inventory, not a measured deployment study; known limitations live in linked per-component notes not fully reproduced here.

Cross-source patterns this evidence supports

Put this evidence to work

Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-09-19; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.

Sales

Role takeaway
Customer problem
Platforms assemble incompatible operator/driver mixes.
Stakeholders
  • platform eng
  • procurement
  • security
Discovery questions
  • Which AI Enterprise branch are you on?
  • Are GPU/NIM/Network operators matrix-aligned?
  • PB or LTSB required?
Value hypothesis
Matrix-aligned 8.2 reduces support and upgrade risk.
Potential engagement
Support-matrix alignment assessment for one cluster.
Unsupported claims
  • 8.2 removes all known issues
  • Any operator combo supported
  • Instant regulated ATO

Pre-sales engineering

Role takeaway
Fit
Fits Kubernetes AI platforms using NVIDIA operators.
Architecture and integration
Pin GPU Operator 26.3.3, NIM Operator 3.1.2, Network Operator 26.4.1 with matching drivers/toolkit.
Prerequisites
  • support matrix check
  • staging cluster
  • workload smoke tests
Constraints
  • Known issues in linked component notes
  • PB quarterly cadence
Security
Track driver/operator patches via component notes.
Proof of value
  • version inventory matches 8.2
  • GPU schedule smoke test
  • NIM serve smoke test

Delivery

Role takeaway
Work
Execute matrix upgrade with canary and rollback.
Dependencies
  • platform
  • security
  • app teams
Ownership
Platform engineering.
Skills and adoption
Operators need matrix literacy and canary discipline.
Governance checkpoints
  • PB/LTSB decision recorded
  • Matrix validation before prod
Acceptance criteria
  • Versions match table
  • Smoke tests pass
  • Rollback documented
Risks
  • Partial upgrades break support
  • Hidden component limitations

Implementation considerations

Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.

Architecture and integration

What must connect, and where does the AI sit in the workflow?

Treat AI Enterprise Infra as a version-locked operator/driver bundle; upgrades should move as a matrix, not one operator at a time without support-matrix checks.

Governance

Who approves, reviews and stays accountable for outcomes?

Change control should record PB vs LTSB selection and matrix-validated combinations before production promotion.

Security and privacy

What data, permissions and controls need testing?

Driver/operator currency affects patch posture; source does not enumerate CVEs here.

Accessibility and workforce

Who is affected, and what skills or accommodations follow?

None stated.

Procurement

What should contracts, pricing and exit terms secure?

Specify AI Enterprise Infra 8.2 component pins in SOWs; require matrix evidence at acceptance.

Operating model

Which teams own the service once it runs?

Platform upgrades become scheduled matrix events, not ad-hoc operator bumps.

Publication history

  1. 2026-09-18NVIDIA · Issue 138 resources
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Stable resource ID: nvidia-aie-infra-8-2-components-2026