Typical configuration
Reference 4Γ H100
- cpu
- AMD EPYC 9554 (DDR5 ECC)
- gpu
- 4Γ NVIDIA H100 (PCIe)
- ram
- 512GB DDR5 ECC
- storage
- 4Γ NVMe U.3 (3.84TB, scratch RAID0)
Enterprise rack servers
A practical sweet spot for many AI and HPC deployments β balance of density and thermals.

Supports 4Γ PCIe datacenter GPUs for training and inference to keep GPUs fed and raise throughput.
Validated 4Γ PCIe datacenter GPUs against power and thermal envelopes for sustained utilisation.
Optimised NVMe staging path for training and inference to cut staging latency and keep accelerators compute-bound.
Aligns DDR5 ECC memory bandwidth with batch throughput to avoid CPU bottlenecks during training and inference.
Engineered 240V / high-amp power options to hold thermal and electrical margins under sustained load.
Our team will spec the right platform for your workload, validate compatibility, and turn it around fast.
PCIe bandwidth & expansion
Supports 4Γ PCIe datacenter GPUs lanes and slot topology to minimise interconnect stalls and raise throughput.
GPU support & density
Provides 4Γ PCIe datacenter GPUs expansion with sufficient power and thermal headroom for sustained utilisation.
Cooling & power considerations
Engineered 240V / high-amp power options for stable thermal and electrical margins under sustained load.
Representative configurations β every build is tailored to your workload and environment.
Typical configuration
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