NVIDIA H200 SXM Servers

Power Your AI Workloads with Next-Gen GPU Infrastructure

Experience unprecedented performance with Cyfuture Cloud's NVIDIA H200 SXM Servers—engineered for large language models, generative AI, and high-performance computing. Built on the cutting-edge Hopper architecture with enhanced HBM3e memory, our H200 SXM servers deliver the computational power your enterprise needs to stay ahead.

Why Choose NVIDIA H200 SXM Servers from Cyfuture Cloud?

Unmatched AI Performance

The NVIDIA H200 Tensor Core GPU delivers breakthrough performance for AI training and inference. With 141GB of HBM3e memory and 4.8TB/s memory bandwidth, handle the most complex neural networks and largest datasets with ease.

Enterprise-Grade Hardware Architecture

Our UCS C885A M8 Rack servers combine AMD EPYC 9554 processors with NVIDIA H200 GPUs in an optimized configuration. With 1.5TB system memory, 8x 400G networking, and enterprise-class storage, you get a complete solution ready for production workloads.

Seamless Scalability

Scale your AI infrastructure without compromise. Our H200 SXM servers feature high-speed interconnects and advanced networking capabilities designed for distributed training and multi-node AI clusters.

Battle-Tested Reliability

Every server includes comprehensive support with 24x7 TAC assistance and next calendar day hardware replacement. Focus on innovation while we ensure your infrastructure stays operational.

Hardware Specifications Overview

GPU Configuration

◾ NVIDIA H200 SXM with HBM3e memory

◾ GPU Memory: 141GB HBM3e per GPU

◾ Memory Bandwidth: 4.8 TB/s

◾ GPU Interconnect: NVLink for ultra-fast GPU-to-GPU communication

◾ Compute Architecture: NVIDIA Hopper with 4th Gen Tensor Cores

Processor & Memory

◾ CPU: 2x AMD EPYC 9554 Processors (128 cores total)

◾ System Memory: 1.5TB DDR5 RAM (24x 64GB modules @ 5600 MT/s)

◾ Memory Channels: High-bandwidth multi-channel architecture

◾ PCIe Generation: Gen 5.0 for maximum I/O throughput

Storage Capabilities

◾ Boot Drives: 2x 960GB enterprise-grade SSDs in RAID configuration

◾ Primary Storage: 8x 7.6TB Kioxia CD8 High-Performance Gen5 NVMe drives

◾ Total Storage Capacity: 61TB+ of ultra-fast NVMe storage

◾ Storage Protocol: NVMe over PCIe Gen5 for maximum IOPS

Networking Infrastructure

◾ High-Speed Fabric: 8x 400G QSFP112 DR4 transceivers (3.2Tbps aggregate)

◾ Cluster Networking: 2x 100G SR1.2 BiDi QSFP transceivers

◾ Management Network: 4x 25GbE with NVIDIA ConnectX-7 NIC

◾ Network Architecture: RDMA-capable for distributed AI workloads

◾ Redundancy: Multiple network paths for high availability

Physical & Power

◾ Form Factor: UCS C885A M8 Rack Server

◾ Power Supply: Redundant hot-swappable PSUs

◾ Power Connectors: 8x C19/C20 power cords for redundant power distribution

◾ Cooling: Advanced thermal management for sustained GPU performance

◾ Rack Units: Dense GPU configuration optimized for data center deployment

Management & Support

◾ Management Platform: Cisco Intersight SaaS with Infrastructure Services

◾ Remote Management: UCS Central with virtual adoption sessions

◾ Support Level: CX Level 1 with 24x7 TAC access

◾ Hardware Warranty: Next Calendar Day replacement service

◾ Contract Options: 24-month and 36-month support tiers available

Technical Specifications

NVIDIA H200 SXM Servers - Complete Hardware Configuration

Ideal Use Cases

Large Language Model Training

Train foundation models with billions of parameters. The H200's massive HBM3e memory enables larger batch sizes and faster training cycles for transformer-based architectures.

Generative AI Applications

Power text-to-image, text-to-video, and multimodal AI applications. Our H200 servers deliver the throughput needed for real-time generative AI inference at scale.

High-Performance Computing

Accelerate scientific simulations, computational fluid dynamics, and molecular modeling. The H200's double-precision performance excels in research and engineering workloads.

AI Inference at Scale

Deploy production AI models with exceptional throughput. The H200's transformer engine and TensorRT-LLM optimization deliver industry-leading tokens-per-second for LLM inference.

Data Analytics & MLOps

Process massive datasets and run complex analytics pipelines. Combined with 61TB of NVMe storage, handle data-intensive machine learning workflows efficiently.

Why Cyfuture Cloud?

Proven Data Center Excellence

With years of experience in enterprise infrastructure, Cyfuture Cloud delivers reliable, high-performance GPU solutions backed by India's leading data center facilities.

Expert Technical Support

Our certified engineers understand AI workloads. Get architectural guidance, optimization recommendations, and rapid troubleshooting when you need it.

Flexible Deployment Options

Choose from dedicated servers, private clusters, or hybrid configurations. We customize solutions to match your specific AI infrastructure requirements.

Competitive Pricing

Enterprise-grade hardware without enterprise overhead. Our transparent pricing and flexible contracts ensure you get maximum value for your AI investment.

Frequently Asked Questions

What makes the NVIDIA H200 SXM superior to previous generations?

The H200 represents a significant leap forward with 141GB of HBM3e memory (nearly 2x the H100's capacity) and 4.8TB/s memory bandwidth. This expanded memory is crucial for large language models and generative AI applications that require massive parameter sets. The H200 also features enhanced Tensor Cores optimized for FP8 precision, delivering superior performance per watt for both training and inference workloads. The SXM form factor ensures maximum GPU-to-GPU bandwidth through NVLink, essential for distributed training scenarios.

What is the total system memory and why is 1.5TB necessary?

Our H200 servers include 1.5TB of DDR5 system RAM (24x 64GB modules @ 5600 MT/s). This massive system memory is critical for AI workloads that involve large dataset preprocessing, data augmentation, and maintaining multiple data pipelines in memory. When training large models, CPU memory acts as a staging area for data feeding into GPUs, and insufficient system memory creates bottlenecks that throttle GPU utilization. The 1.5TB configuration ensures your GPUs remain fully utilized even with the most demanding data pipelines.

Can I scale this configuration for multi-node AI clusters?

Absolutely. The hardware architecture is designed for seamless clustering. Each server includes 8x 400G QSFP112 transceivers providing 3.2Tbps of aggregate networking bandwidth, specifically engineered for GPU-to-GPU communication across nodes. The 2x 100G transceivers handle storage and management traffic. Our networking infrastructure supports RDMA (Remote Direct Memory Access) for ultra-low latency inter-node communication, essential for distributed training frameworks like PyTorch FSDP and DeepSpeed. We can help design and deploy multi-rack GPU clusters with optimized fabric topology.

What type of support is included with the hardware?

Every H200 server includes comprehensive enterprise support. The base configuration comes with 24x7 TAC (Technical Assistance Center) access with next calendar day hardware replacement. This means if a component fails, a replacement is dispatched the next business day. You also get Cisco Intersight SaaS management tools for remote monitoring, firmware updates, and health diagnostics. Our team provides tier-2 support for hardware issues, OS-level troubleshooting, and configuration assistance. For customers running mission-critical AI workloads, we offer enhanced SLA options with 4-hour response times.

What is the total NVMe storage capacity and performance characteristics?

The system includes 8x 7.6TB Kioxia CD8 High-Performance NVMe drives, delivering 61TB of total usable storage. These are enterprise-class, Gen5 NVMe drives with exceptional endurance ratings and consistent performance. Running across PCIe Gen5 lanes, the aggregate storage system can deliver multi-million IOPS and tens of GB/s sequential throughput—critical for feeding data to GPUs during training. This capacity supports large datasets, model checkpoints, and staging areas for data preprocessing. The drives can be configured in various RAID levels or used as individual volumes depending on your workflow requirements.

What are the power and cooling requirements for deployment?

The UCS C885A M8 with H200 GPUs is a high-density system requiring appropriate data center infrastructure. Total system power draw under full load typically ranges from 8-10kW per server, depending on workload characteristics. Each server requires 8x C19/C20 power connections for redundant power distribution across multiple PSUs. From a cooling perspective, plan for significant BTU output—these systems require hot aisle/cold aisle configurations with adequate CFM and ideally operate in environments with 18-27°C ambient temperatures. We recommend rack-level power distribution units (PDUs) with at least 15kW capacity per rack and high-efficiency cooling infrastructure. Our team can assist with power and cooling assessments during deployment planning.