Nexus H100 64-GPU SuperPOD-Class Cluster (8× HGX H100 Nodes)
Rail-optimized 64-GPU H100 fabric engineered for serious foundation-model runs.
We help you choose, configure, and deliver the right system — no obligation.
Configuration at a Glance
Tailored per engagement. Full technical overview below.
Configuration Options
Core specifications for this system. Every component is configurable to your workload — request a quote for a tailored build.
64× NVIDIA H100 80GB SXM5 (8× HGX H100 8-GPU nodes)
Dual Intel Xeon or AMD EPYC per node
Up to 2TB DDR5 ECC per node
Parallel filesystem with GPUDirect Storage (PB-scale)
Overview
This 64-GPU cluster combines eight HGX H100 nodes on a rail-optimized, non-blocking NDR InfiniBand fabric modeled on NVIDIA SuperPOD scalable-unit design. Nexus Compute specifies, integrates, and acceptance-tests compute, fabric, parallel storage, and management as one warranty-backed system sourced through authorized channels.
Who This Solution Is For
Business Benefits
Predictable scaling efficiency
Rail-optimized topology keeps every GPU one hop from its peers per rail, sustaining near-linear scaling across all 64 GPUs on large jobs.
Single accountable supplier
We coordinate compute, switching, cabling, storage, and orchestration into one validated delivery instead of a multi-vendor integration risk.
Owned-economics at scale
For sustained training campaigns, this owned cluster materially undercuts equivalent rented GPU-hours over its service life.
Typical Business Use Cases
Foundation and large custom model training
Tensor- and pipeline-parallel runs across 8 nodes
Multi-team shared research compute at pod scale
Internal AI platform on owned infrastructure
Industry Applications
Technical Overview
Eight NVIDIA HGX H100 8-GPU SXM5 nodes (64× H100 80GB) connect over a non-blocking, rail-optimized NVIDIA Quantum-2 NDR 400Gb/s InfiniBand compute fabric with a separate in-band management and storage network. A high-throughput parallel filesystem with GPUDirect Storage and Slurm or Kubernetes orchestration are sized to a SuperPOD scalable-unit blueprint.
| GPU / Accelerator | 64× NVIDIA H100 80GB SXM5 (8× HGX H100 8-GPU nodes) |
| GPU Interconnect | NVSwitch intra-node; rail-optimized NDR InfiniBand inter-node |
| CPU | Dual Intel Xeon or AMD EPYC per node |
| Memory | Up to 2TB DDR5 ECC per node |
| Networking / Fabric | Non-blocking Quantum-2 NDR with QM9700 spine/leaf |
| Storage | Parallel filesystem with GPUDirect Storage (PB-scale) |
| Management | Base Command / fabric manager + out-of-band BMC |
| Form Factor | Multi-rack pod, compute + dedicated switching rack |
| Warranty | Nexus-backed, NVIDIA AI Enterprise eligible |
Specifications are indicative and configured to each engagement. Request a quote for a configuration tailored to your requirements.
Warranty, Support & Fulfillment
Every system ships from an authorized channel, configured and tested, with the documentation enterprise buyers need — backed by warranty and a dedicated account team.
Enterprise Warranty
Full manufacturer warranty with optional on-site, next-business-day support and extended coverage.
Authorized Channel
Sourced through Tier-1 distribution and OEM partners — never grey market. Asset & warranty records included.
Lead Time & Deployment
48-hour quotes, then configured, burn-in tested, and delivered on a committed schedule.
Nationwide Fulfillment
Coordinated logistics, rack-and-stack, and delivery wherever your infrastructure lives.
Frequently Asked Questions
How big a model can 64 H100s train?
Sizing depends on parameters, sequence length, and parallelism strategy, but 64 H100s comfortably train and fine-tune many multi-billion-parameter models; our engineers map your target model to node count, fabric, and storage before quoting.
What does rail-optimized buy me?
It places GPUs so collective operations traverse the fewest hops, which preserves scaling efficiency as jobs span all eight nodes — the difference between 64 GPUs acting as one resource versus diminishing returns.
Do you handle delivery and commissioning?
Yes. We source through authorized channels, integrate and burn in the pod, and support staged delivery and on-site commissioning to acceptance.
Hardware Assistance
Configure the Nexus H100 64-GPU SuperPOD-Class Cluster (8× HGX H100 Nodes) with Nexus Compute
Tell us your requirements and a hardware specialist will help you specify, configure, and quote the right system — typically within two business days. No obligation.