Gigabyte G492-Z54-AAX1 AMD EPYC 8-GPU OAM Server

The Gigabyte G492-Z54-AAX1 is a purpose-built 4U high-density GPU server engineered around AMD EPYC processors and an eight-slot OAM (OCP Accelerator Module) architecture, making it a leading platform for large-scale AI training, high-performance inference, and GPU-accelerated HPC workloads. The system is designed to accommodate eight OAM-form-factor GPU accelerators, enabling extreme parallelism and massive aggregate GPU memory bandwidth essential for foundation model training, scientific simulation, and deep learning pipelines at datacenter scale.

Built to meet the demands of modern AI infrastructure, the G492-Z54-AAX1 supports AMD EPYC processors delivering high core counts, large memory capacity across multiple DDR4/DDR5 DIMM slots, and PCIe Gen 4 connectivity throughout the platform. The OAM module standard allows for high-bandwidth inter-GPU communication fabrics, supporting coherent data movement between accelerators and the host CPU complex with minimal latency. The chassis incorporates enterprise-grade hot-swap storage bays, redundant high-wattage power supplies, and a managed cooling subsystem calibrated for sustained full-load GPU operation in dense rack environments.

Targeted at hyperscale operators, national research laboratories, cloud service providers, and enterprise AI teams deploying GPU clusters across UAE, GCC, EMEA, and APAC regions, the G492-Z54-AAX1 from Gigabyte represents a mature, rack-optimized solution for organizations requiring dense GPU compute without compromise. Its OAM-compliant design ensures forward compatibility with next-generation accelerator modules, protecting infrastructure investment as GPU generations evolve. Omnixon Global supplies this platform to enterprise and datacenter buyers across worldwide markets.

Ideal for

• Large language model (LLM) and foundation model training requiring sustained multi-GPU parallelism across eight OAM accelerators
• High-throughput AI inference serving for real-time applications such as recommendation engines, NLP pipelines, and computer vision at scale
• High-performance computing (HPC) workloads including molecular dynamics, computational fluid dynamics, and climate modeling benefiting from dense GPU memory bandwidth
• Generative AI and diffusion model workloads requiring large aggregate GPU VRAM to hold multi-billion parameter models in active memory
• GPU-accelerated data analytics and in-memory processing pipelines for financial modeling, genomics, and large-scale scientific datasets
• Datacenter AI cluster deployment as a building block node within a high-bandwidth interconnect fabric for distributed multi-node training environments

Technical specifications

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