How to Learn About NVIDIA DGX H100 Price and Specs for Enterprise Users

As of 2025, the global artificial intelligence market is projected to surpass $500 billion, according to Statista, with enterprise AI applications driving the majority of this growth. From generative AI to advanced analytics, businesses are rapidly shifting toward high-performance computing environments. At the center of this transformation lies NVIDIA’s DGX H100 system, the latest powerhouse purpose-built for enterprise-grade AI and machine learning workloads.

The DGX H100 is engineered to meet the rising compute demands of deep learning models and large-scale neural networks. It features eight NVIDIA H100 Tensor Core GPUs interconnected via the NVLink Switch System, delivering up to 32 petaflops of AI performance. These specifications make it one of the most powerful AI server systems available in the market.

But with great performance comes a key question from IT leaders and data teams alike:
“How can we accurately find the NVIDIA DGX H100 price and specifications tailored for enterprise environments?”

Whether you’re planning a purchase, considering DGX-as-a-Service, or exploring co-locations for infrastructure deployment, this guide will walk you through everything you need to know about DGX H100 specs, pricing, and how to make the best enterprise-level investment.

NVIDIA DGX H100: Technical Overview

Understanding the specifications of the DGX H100 is essential before exploring pricing. This server system is purpose-built for multi-GPU workloads and offers the highest density and performance available today for AI training and inference.

Key Hardware Specs:

GPU: 8x NVIDIA H100 Tensor Core GPUs (80 GB HBM3 each)

Total GPU Memory: 640 GB

CPU: Dual AMD EPYC 9654, 96 cores each

System RAM: 2 TB DDR5

Storage: 30.72 TB NVMe Gen4 SSD

Networking: 8x 400 Gbps InfiniBand/Ethernet ports

Power Consumption: ~10kW per unit

Cooling Support: Enterprise-grade airflow and thermal design

These features make it suitable for workloads such as LLM training, scientific simulations, high-frequency trading, autonomous systems, and cloud infrastructure backbones.

How to Learn About DGX H100 Pricing Effectively

The price of the NVIDIA DGX H100 isn’t typically listed publicly due to the custom nature of enterprise deployment, but here’s how to approach it:

1. Get Pricing from Authorized Resellers

NVIDIA sells the DGX H100 through its authorized channel partners like HPE, Dell, Lenovo, and other cloud service integrators. Prices often start around $300,000 to $400,000 USD per unit, depending on:

Support and warranty package

Rack or data center integration

Software stacks and pre-installed frameworks

2. Consider DGX-as-a-Service Models

Many cloud and hosting providers are now offering DGX systems on a rental basis—ideal for organizations looking to avoid CapEx:

Pay-as-you-go or subscription-based access

Managed co-locations with pre-configured DGX racks

Access to clusters instead of individual units

This model is particularly beneficial for research labs, AI startups, and enterprises testing large-scale models before making a full investment.

3. Calculate Total Cost of Ownership (TCO)

Beyond the base hardware price, enterprise users must consider:

Rack space or co-location facility cost

Network configuration and uplink speeds

Licensing fees for software like NVIDIA AI Enterprise

Energy and cooling requirements

Factoring in these operational costs helps avoid under-budgeting and gives a clearer view of ROI.

Hosting & Co-Locations: Infrastructure Requirements

The DGX H100 system has demanding infrastructure needs. Deploying this system requires a data center or hosting provider capable of supporting:

High Power Density: Systems require up to 10kW per node.

Advanced Cooling: Liquid cooling or high-efficiency HVAC systems.

Redundant Networking: At least 400 Gbps fabric per DGX unit for cluster performance.

Security & Compliance: Ideal facilities offer ISO, SOC 2, or Tier III certifications for secure AI workloads.

Why DGX H100 Is the Go-To AI Server for Enterprises

With its robust architecture and industry-leading specs, the DGX H100 is not just another server—it’s the foundation for enterprise-grade AI. Companies investing in these systems are preparing for the next wave of innovation across:

Healthcare and genomics

Financial modeling and fraud detection

Smart manufacturing and automation

Language models and generative AI systems

The DGX H100 aligns with the future of distributed cloud computing, enabling AI at the edge, in hybrid environments, or through centralized data centers.

Conclusion: 

As enterprise demand for scalable AI infrastructure accelerates, the NVIDIA DGX H100 emerges as a cornerstone technology for organizations aiming to unlock high-performance, future-ready computing. With its unmatched GPU capabilities, vast memory bandwidth, and robust system architecture, the DGX H100 isn’t just a server it’s an AI supercomputer engineered for the modern enterprise.

However, selecting the right deployment model whether through direct purchase, co-location, or managed cloud hosting requires careful analysis of pricing, infrastructure compatibility, and operational overhead.

We’re committed to making cutting-edge AI infrastructure more accessible through our purpose-built hosting environments and enterprise-ready co-location facilities. Whether you’re looking to deploy DGX H100 systems on-premises, offload them to a high-density data center, or explore AI workloads in the cloud, Cyfuture Cloud offers scalable, secure, and cost-optimized solutions tailored for your business goals.

Partner with us to harness the full potential of NVIDIA DGX H100 without the complexity. From infrastructure to innovation, Cyfuture Cloud is your trusted AI enablement partner.