NVIDIA DGX H100
- Condition
- New
- Manufacturer
- NVIDIA
- Form factor
- 8U
- CPU
- 2x Intel Xeon Platinum 8480C (56c/112t, 2GHz-3.8GHz, 350W)
- RAM
- 2000GB (DDR5 ECC REG)
- NIC card
- 8x ConnectX-7 via 4x OSFP
- GPU
- 8 x NVIDIA H100
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Submit a requestNVIDIA DGX H100 is an integrated accelerated computing system designed for enterprise artificial intelligence, machine learning, generative AI, analytics, and high-performance computing (HPC) workloads. Built around eight NVIDIA H100 Tensor Core GPUs, the platform provides a unified architecture for AI training, inference, and large-scale data processing in modern data centers.
Unlike a traditional GPU server assembled from individual components, NVIDIA DGX H100 combines GPU acceleration, high-speed interconnects, storage, networking, and a validated NVIDIA software stack in a single enterprise-ready platform. It can operate as a standalone AI compute node or serve as a building block for scalable DGX-based clusters.
GPU architecture for AI training and inference
NVIDIA DGX H100 is equipped with eight NVIDIA H100 Tensor Core GPUs based on the NVIDIA Hopper architecture. The system provides 640GB of total GPU memory, giving enterprises the capacity required for large AI models, generative AI workloads, accelerated analytics, and HPC applications.
The NVIDIA H100 Tensor Core GPU is designed for demanding AI workloads, including large language model training, fine-tuning, inference, recommendation systems, computer vision, analytics, and scientific computing. Tensor Cores with support for advanced mixed-precision computing help accelerate neural network operations while maintaining the accuracy required for production workloads.
The eight GPUs are connected through fourth-generation NVIDIA NVLink and four fourth-generation NVIDIA NVSwitch devices, creating a high-bandwidth GPU communication fabric. This architecture provides up to 900GB/s of GPU-to-GPU bandwidth and allows multiple accelerators to efficiently operate together as a single computing domain for demanding distributed workloads.
The system is powered by two Intel Xeon 8480C processors with 56 cores each, providing 112 CPU cores in total. The factory configuration includes 2TB of system memory, enabling efficient data preparation, containerized workloads, and CPU-side processing tasks required by AI pipelines.
Primary use cases
- AI model training and fine-tuning. DGX H100 accelerates development and optimization of large-scale AI models, including generative AI, natural language processing, computer vision, recommendation systems, and enterprise AI applications.
- Large-scale inference workloads. The platform is designed for deploying production AI services, intelligent applications, automated decision systems, chatbots, and real-time model execution.
- Data analytics and accelerated computing. DGX H100 supports GPU-accelerated analytics, scientific computing, simulations, and workloads that combine traditional HPC methods with machine learning.
- Multi-user AI environments. NVIDIA Multi-Instance GPU (MIG) technology allows each H100 GPU to be partitioned into up to seven isolated GPU instances with dedicated memory and compute resources, improving resource utilization for multiple teams and applications.
- Enterprise AI infrastructure. DGX H100 provides a standardized foundation for organizations building internal AI platforms, research environments, scalable machine learning operations, and private generative AI infrastructure.
NVIDIA DGX H100 in enterprise infrastructure
NVIDIA DGX H100 is designed for organizations that require dedicated AI computing resources for continuous development, testing, and production deployment. The platform enables data science teams, AI engineers, and enterprise developers to work within a consistent hardware and software environment instead of managing separate accelerator servers and integration layers.
The system can be deployed as an individual AI node or integrated into larger NVIDIA-based environments. When planning an enterprise deployment, organizations should evaluate not only GPU performance but also network architecture, external storage requirements, workload distribution, power availability, cooling capacity, and data center readiness.
With its integrated hardware design, NVIDIA software ecosystem, and support for scalable AI deployments, DGX H100 helps enterprises shorten the path from AI experimentation to production use. The platform provides a reliable foundation for organizations developing generative AI services, machine learning platforms, analytics solutions, and HPC applications that require predictable performance and simplified infrastructure management.
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