GIGABYTE G893-SD1 NVIDIA HGX H200 Server (8U)

The GIGABYTE G893-SD1 is an 8U rack-mounted server built around the NVIDIA HGX H200 baseboard, housing eight NVIDIA H200 SXM5 Tensor Core GPUs interconnected via NVLink 4.0 at 900 GB/s bidirectional bandwidth per GPU. Each H200 GPU integrates 141 GB of HBM3e high-bandwidth memory operating at up to 4.8 TB/s, providing the memory capacity and bandwidth essential for loading and serving today's largest language models—including 70B to 405B parameter networks—entirely within GPU memory without partitioning across nodes. The platform supports dual fourth-generation Intel Xeon Scalable or AMD EPYC processors, pairing CPU compute with the GPU subsystem through PCIe Gen 5 host interfaces, while a dedicated NVSwitch fabric within the HGX baseboard enables all-to-all GPU communication at full bandwidth, a critical requirement for tensor-parallel and pipeline-parallel training regimes.

The G893-SD1 is engineered for the most demanding AI infrastructure deployments, including pre-training of foundation models, fine-tuning with reinforcement learning from human feedback (RLHF), and high-density multi-model inference serving. The chassis accommodates high-capacity NVMe storage for dataset staging, supports NVIDIA NVLink Switch System configurations for multi-node scaling, and integrates with InfiniBand NDR or Ethernet 400GbE networking fabrics to form tightly coupled GPU clusters. Thermal design centers on a direct liquid cooling (DLC) architecture with rear-door heat exchanger compatibility, enabling sustained full-TDP operation of all eight H200 GPUs simultaneously—each rated at 700 W SXM TDP—within the acoustic and thermal constraints of modern hyperscale and enterprise data centers.

From a systems integration perspective, the G893-SD1 supports NVIDIA AI Enterprise software stack, CUDA 12.x, cuDNN, TensorRT, and the full NGC container catalog out of the box. BMC-based remote management via Redfish and IPMI 2.0 allows integration into orchestration platforms such as Kubernetes with GPU Operator, SLURM, and OpenShift AI. The server's 8U form factor delivers one of the highest GPU-compute-per-rack-unit densities available, making it a strategic choice for operators building GPU clusters where floor space, power delivery, and cooling infrastructure are at a premium.

Ideal for

• Pre-training and continued pre-training of large language models with 70B–405B+ parameters using tensor and pipeline parallelism across all eight H200 GPUs
• High-throughput generative AI inference serving for enterprise LLM APIs, enabling multi-model deployment with large per-GPU memory headroom reducing KV-cache evictions
• Multimodal foundation model development combining vision transformers and large language models requiring sustained HBM3e bandwidth above 4 TB/s per GPU
• Scientific simulation and digital twin workloads in energy, genomics, and climate modeling that require both FP64 precision and extreme memory capacity per accelerator
• Fine-tuning of open-weight foundation models using full-parameter supervised fine-tuning or RLHF pipelines where gradient checkpointing overhead is eliminated by available HBM3e capacity
• AI-driven drug discovery and protein structure prediction at scale, leveraging transformer-based architectures that exceed 80 GB GPU memory bounds common on prior-generation hardware

Technical specifications

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