Custom 7U 8-GPU AI Server — Purpose-Built for Large Model Inference

When deploying large language models at scale, every architectural decision compounds. This custom-engineered 7U 8-GPU AI server, built on the Intel Xeon 6 processor platform, eliminates bottlenecks at the source — delivering the memory bandwidth, GPU throughput, and system reliability that production AI workloads demand.

Maximum GPU Density, Maximum Bandwidth

The server accommodates eight of the latest 600W compute accelerators, each connected via PCIe 5.0 x16 lanes, providing the full-duplex bandwidth that keeps high-parameter models processing without pipeline stalls. Whether running inference on a 70B-parameter transformer or rendering complex graphical workloads, the eight-way GPU configuration ensures your most demanding jobs finish faster. The chassis supports both turbo-fan and passive-cooled accelerator cards up to quad-width form factors, giving deployment teams flexibility in hardware sourcing.

Memory Architecture That Keeps Pace

With 32 DDR5 DIMM slots operating at up to 6400 MT/s, the platform delivers a 33% memory bandwidth uplift over previous-generation DDR4 designs. This is critical for large model inference, where CPU-to-GPU data staging and pre-processing throughput directly impacts end-to-end latency. More bandwidth means less idle accelerator time and higher token-generation rates under concurrent user loads.

Versatile Expansion and Storage

Beyond the eight GPU slots, the system offers up to 11 PCIe 5.0 standard expansion slots with multiple riser configurations, plus an optional OCP 3.0 network adapter supporting various line rates. Storage is equally flexible: eight 3.5-inch or 2.5-inch SAS/SATA drive bays handle bulk data, while optional NVMe SSD support (up to four drives) provides high-performance local caching for hot datasets.

Enterprise Reliability by Design

All critical components — power supplies, fans, and drives — are hot-swappable and tool-free, minimizing downtime during field maintenance. An integrated intelligent management controller supports IPMI 2.0, Redfish, and SNMP protocols, enabling remote KVM, virtual media, component health monitoring, and proactive alerting. Whether deployed in a hyperscale inference cluster or a private AI data center, the platform stays manageable at scale.