GIGABYTE MZ73-LM1 Motherboard-9005/9004 Series Processors–E-ATX DP–400W

The GIGABYTE MZ73-LM1 is a dual-socket E-ATX server motherboard engineered for the latest AMD EPYC™ 9005 (Turin) and 9004 (Genoa/Bergamo) Series Processors. Designed to deliver extreme compute density, high memory bandwidth, and next-generation expansion, it supports DDR5 memory, PCIe Gen5 connectivity, and advanced remote management. With a 400W CPU TDP envelope per socket, it is optimized for HPC, AI/ML, virtualization, and enterprise-class workloads.

Key Features

• Processor Support
  • Dual-socket AMD EPYC™ 9005 / 9004 Series (SP5)
  • Scales up to 192 cores / 384 threads in a 2P configuration.
  • High performance-per-watt architecture designed for demanding compute environments.
• Form Factor
  • E-ATX (305 x 330mm) dual-processor board.
  • Rackmount-ready for enterprise and cloud data centers.
• Memory
  • 12-channel DDR5 architecture per CPU.
  • Supports large memory capacity (4TB+ depending on DIMMs).
  • ECC RDIMM/LRDIMM support for mission-critical error correction and stability.
• Expansion Capability
  • Multiple PCIe Gen5 slots for accelerators, GPUs, DPUs, FPGAs, or high-speed storage adapters.
  • Ideal for AI training, HPC simulation, and virtualization clusters.
• Storage Options
  • SATA 6Gb/s ports for traditional storage devices.
  • 2 NVMe Gen4/Gen5 slots for high-speed SSDs.
  • RAID support for enterprise-class data protection and redundancy.
• Networking
  • Integrated dual LAN ports (1GbE/10GbE depending on SKU).
  • Expandable up to 100/200GbE with PCIe NICs for hyperscale networking.
• Power & Efficiency
  • Optimized for 400W TDP per socket, providing a balance of compute power and energy efficiency.
  • Enhanced thermal and power design for 24/7 data center workloads.
• System Management
  • Equipped with AST2600 BMC, IPMI 2.0 & Redfish API.
  • Full remote monitoring of CPU, memory, storage, thermals, and power usage.

Applications

• High-Performance Computing (HPC) – Large-scale simulations, scientific modeling, and research clusters.
• Artificial Intelligence & Machine Learning – Multi-GPU AI training, inference, and deep learning workloads.
• Cloud Computing & Virtualization – Designed for scale-out SaaS, PaaS, and IaaS infrastructures.
• Enterprise Databases & Storage – High-capacity memory and storage support for mission-critical databases.
• Telecom & Edge Computing – Ready for NFV, 5G, and distributed real-time compute applications.