Nexus Compute

H100 GPU Server

The proven data-center standard for large-scale AI training and inference.

Overview

The H100 GPU Server is built around NVIDIA's H100, the established workhorse of enterprise AI. Its high-bandwidth memory and Transformer Engine make it the reference choice for serious training and high-throughput inference. Nexus Compute sources H100 systems and advises on the configuration that fits your workload and facility. Sizing starts with memory. An H100 carries 80GB, and as a rough guide half-precision inference needs about 2GB per billion parameters for weights before any KV cache, while training with a standard optimizer needs closer to 16GB per billion once gradients and optimizer state are counted. That arithmetic decides whether you need four GPUs or eight, whether the model runs within one node or has to be split with tensor and pipeline parallelism, and whether quantization or CPU offload is a sensible answer or a performance trap. The second question is the building: an eight-way air-cooled H100 node is typically a 10kW-and-up rack proposition, and many server rooms are provisioned for a fraction of that. We would rather establish your per-rack power and cooling ceiling in the first conversation than at delivery.

Warranty & Support