GIGABYTE G593-ZX1 8-GPU EPYC AI Server

The GIGABYTE G593-ZX1 is a 5U rack-mount server designed around dual AMD EPYC 9005 series processors, delivering a dense, high-bandwidth compute foundation for modern AI inference clusters and high-performance computing environments. The platform accommodates eight dual-slot PCIe Gen 5.0 x16 GPUs simultaneously, providing exceptional aggregate GPU-to-GPU bandwidth and enabling full utilization of the latest accelerator generations without bottlenecks. With support for up to 12-channel DDR5 memory per CPU socket, the G593-ZX1 supplies the memory bandwidth necessary to feed GPU pipelines efficiently during large-model inference tasks.

The architecture leverages AMD EPYC 9005's Zen 5 core design, which offers significant IPC improvements and expanded L3 cache compared to prior generations, ensuring CPU-side preprocessing, tokenization, and orchestration tasks remain off the critical path during inference serving. The dual-socket topology allows system administrators to partition CPU resources between host management and accelerator coordination, an increasingly important capability as LLM serving frameworks demand dedicated CPU cores for scheduling and batching logic. PCIe Gen 5 connectivity doubles the available bandwidth per slot relative to Gen 4, directly benefiting GPU memory copy operations and NVLink-equivalent direct GPU communication paths supported through external fabric adapters.

Noted for its deployment flexibility, the G593-ZX1 targets hyperscale AI inference racks, GPU cloud tenancy builds, enterprise ML operations, and scientific HPC cluster nodes. The 5U chassis balances GPU density with adequate thermal headroom, incorporating a high-airflow cooling design with tool-less GPU sled access to minimize maintenance downtime. Dual redundant power supply units with high-efficiency platinum or titanium ratings support continuous 24/7 operation at full GPU load, and out-of-band management through GIGABYTE's MegaRAC BMC enables remote diagnostics, power capping, and health monitoring without requiring OS-level access.

Ideal for

• Large language model inference serving with multi-GPU tensor parallelism across up to eight accelerators per node
• Enterprise AI inference cluster deployment where PCIe Gen 5 bandwidth is required to support next-generation GPU models
• High-performance computing workloads combining dual EPYC 9005 CPU compute with GPU-accelerated simulation kernels
• GPU cloud node build-out for multi-tenant inference workloads requiring isolated dual-slot GPU slots per tenant
• Machine learning model pipeline execution demanding high DDR5 memory bandwidth for data preprocessing and feature engineering
• Scientific research environments running mixed CPU-GPU workloads such as molecular dynamics, climate modeling, and computational fluid dynamics

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.