Nexus Compute HGX B200 8-GPU EPYC Inference Server
EPYC-driven Blackwell density for high-throughput, low-latency model serving.
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.
NVIDIA HGX B200 8-GPU (180GB HBM3e each, 1.4TB total)
Dual AMD EPYC (9004/9005 series)
Up to 3TB DDR5 ECC
Hot-swap NVMe array + M.2 boot
Overview
This server pairs the NVIDIA HGX B200 8-GPU platform with dual AMD EPYC processors and abundant PCIe lanes, tuned for high-concurrency inference where memory bandwidth and tokens-per-second matter most. Nexus Compute specifies, configures, tests, and warranty-backs each system through authorized channels, optimizing GPU partitioning and networking around your latency and volume targets.
Who This Solution Is For
Business Benefits
High serving throughput
1.4TB of fast HBM3e across eight Blackwell GPUs drives high tokens-per-second for memory-bound inference.
Efficient cost-per-request
Dense GPUs with MIG-style partitioning keep utilization high and per-request economics competitive at volume.
EPYC I/O headroom
Dual EPYC CPUs supply ample cores and PCIe lanes to keep GPUs fed and NICs saturated under load.
Typical Business Use Cases
Production LLM and generative model serving
High-concurrency, latency-sensitive inference
Multi-tenant GPU serving with partitioning
Retrieval-augmented generation at scale
Industry Applications
Technical Overview
The NVIDIA HGX B200 8-GPU baseboard provides 1.4TB of HBM3e and 1.8TB/s NVLink bandwidth across eight Blackwell GPUs, fronted by dual AMD EPYC CPUs with high core counts and PCIe Gen5 connectivity. A 1:1 GPU-to-NIC mapping with ConnectX-7 sustains line-rate networking for distributed and disaggregated serving.
| GPU | NVIDIA HGX B200 8-GPU (180GB HBM3e each, 1.4TB total) |
| GPU Interconnect | 5th-gen NVLink + NVSwitch, 1.8TB/s per GPU |
| CPU | Dual AMD EPYC (9004/9005 series) |
| System Memory | Up to 3TB DDR5 ECC |
| Storage | Hot-swap NVMe array + M.2 boot |
| Networking | 8x ConnectX-7 up to 400Gb/s (1:1 GPU:NIC) |
| GPU Partitioning | Multi-instance partitioning for multi-tenant serving |
| Form Factor | 8U–10U rackmount (air-cooled) |
| Warranty | Enterprise warranty with support options |
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
Why EPYC instead of Xeon for this node?
Dual EPYC offers high core counts and abundant PCIe Gen5 lanes that suit I/O-heavy inference pipelines and NIC saturation. We recommend the CPU platform that best matches your serving stack.
How many models or tenants can it serve?
With partitioning, the eight GPUs can host many concurrent models or isolated tenants. Capacity depends on model size and latency targets, which we size with you.
Can it also handle training?
It can train and fine-tune effectively, but it is tuned for serving. For sustained large-model pretraining we typically recommend our liquid-cooled training node or NVL72 rack.
Hardware Assistance
Configure the Nexus Compute HGX B200 8-GPU EPYC Inference Server 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.