Hardware Datasheet · GPU Server
Nexus Compute
Nexus H200 32-GPU Inference Cluster with Parallel Storage
Low-latency 32-GPU H200 serving with a GPUDirect parallel storage backbone.
Overview
This 32-GPU H200 cluster is tuned for high-availability, low-latency model serving, pairing four HGX H200 nodes with a GPUDirect-certified parallel storage tier for fast model and KV-cache loading. Nexus Compute specifies, integrates, and acceptance-tests compute, fabric, storage, and serving software as one warranty-backed system sourced through authorized channels.
Specifications
| GPU / Accelerator | 32× NVIDIA H200 141GB HBM3e SXM5 (4× HGX H200 nodes) |
| GPU Interconnect | NVSwitch intra-node; NDR InfiniBand inter-node |
| CPU | Dual Intel Xeon or AMD EPYC per node |
| Memory | Up to 2TB DDR5 ECC per node |
| Storage | GPUDirect-certified parallel filesystem (WEKA/VAST-class) |
| Networking / Fabric | Load-balanced NDR InfiniBand + high-speed Ethernet front end |
| Serving Software | vLLM or NVIDIA Triton pre-configured |
| Management | Out-of-band BMC + latency/throughput monitoring |
| Warranty | Nexus-backed, NVIDIA AI Enterprise eligible |
Typical Use Cases
- ·Production serving of large LLMs and generative models
- ·High-concurrency, latency-sensitive inference APIs
- ·Rapid model and adapter swapping at scale
- ·Cost-optimized inference at high request volume
Industries
Warranty & Support
Supplied through authorized channels with full manufacturer warranty. On-site, next-business-day support options available. Every system is configured, tested, and documented before delivery, with asset and warranty records provided for enterprise audit requirements.
Request a tailored quote
Configurations are tailored per engagement — contact us for pricing and lead times.
sales@nexus-compute.com
+1 737 276 1016
nexus-compute.com
Specifications are indicative and configured to each engagement. All product names, logos, and trademarks are the property of their respective owners. Nexus Compute is an independent enterprise hardware supplier.