NVIDIA

NVIDIA DGX H200 AI System (8x H200 SXM5, 1,128GB)

Model: DGX H200

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The complete, turnkey high-memory DGX system: NVIDIA's DGX H200 integrates eight H200 SXM5 GPUs (1,128GB total, 141GB per GPU) with dual Xeon processors, system memory, storage, and networking into a finished, tested machine, the high-memory Hopper DGX, structurally the DGX H100 with H200 GPUs for the largest memory-bound models, and a DGX SuperPOD and BasePOD building block. Ready to deploy, not a bare baseboard. Shipped worldwide DDP by MillionMiner.

Full Specifications

Model DGX H200
GPU NVIDIA H200 Tensor Core
System Type AI Server
Architecture DGX SuperPOD
Performance Leadership-class accelerated infrastructure
Workload Support AI training and inference
Scalability Configurable with any DGX system
Use Cases Enterprise AI data centers
Optimization Business innovation

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Get a Quote for the NVIDIA DGX H200 AI System (8x H200 SXM5, 1,128GB)

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Product Details

NVIDIA DGX H200 AI System: The High-Memory Advantage, the DGX-vs-HGX Choice, and Where It Fits

The DGX H200 is NVIDIA's complete, turnkey AI system in the high-memory H200 configuration, the company's reference platform, and it is genuine flagship AI training and inference infrastructure. Like the DGX H100 and DGX B200, it is a finished machine, not a bare baseboard, so there is no component-versus-system caveat. Placing it well means three things: what it is, the H200 memory advantage over the DGX H100, and how a DGX differs from the OEM HGX servers that use the same GPUs.What the DGX H200 is. It is a fully integrated 8x H200 system. Eight H200 SXM5 Tensor Core GPUs provide 1,128GB of total GPU memory (141GB per GPU), interconnected by NVLink and NVSwitch, and the system pairs them with dual Xeon processors, system memory, NVMe storage, and high-speed networking. It ships with NVIDIA's AI Enterprise and DGX OS software stack, as a complete, tested, ready-to-deploy machine, and it is a building block of NVIDIA's DGX SuperPOD and BasePOD reference cluster architectures.The high-memory advantage over the DGX H100. The DGX H200 is, structurally, the DGX H100 built with H200 GPUs in place of H100s. The H200 is the high-memory member of the Hopper generation: each carries 141GB of HBM3e with more bandwidth than the H100's 80GB, so across the eight-GPU system the DGX H200 holds 1,128GB of GPU memory versus the DGX H100's 640GB. For the largest models and memory-bound training and inference, that extra capacity and bandwidth per GPU is the reason to choose the DGX H200 over the DGX H100, more of the model and data fits in high-bandwidth memory per GPU. The two share the same Hopper generation and DGX system design; the H200 variant is the high-memory option.What a DGX is, versus an HGX server. As with the other DGX systems, this is a key acquisition choice. HGX is NVIDIA's GPU baseboard platform that OEMs build their own servers around; DGX is NVIDIA's own complete system on that same GPU technology. They use the same H200 GPUs, so raw GPU performance is comparable. What differs is integration and support: the DGX is engineered, validated, and supported by NVIDIA as a single reference platform with its own software stack, support program, and SuperPOD/BasePOD cluster architectures, while an OEM HGX H200 server is that vendor's integration at a different price and support model. Choose the DGX for NVIDIA's reference design, validation, and cluster path; an OEM HGX H200 server for a different integration and price point.Genuine flagship AI infrastructure. The DGX H200 is real, top-tier AI training and inference hardware, eight high-memory Hopper GPUs with 1,128GB of memory is frontier-class compute for the largest models, and the DGX is the system NVIDIA itself positions as its AI infrastructure standard. There is no overstatement to qualify; it is exactly what it claims to be.Where it fits, and how to buy it. The DGX H200 sits at the top of the complete-systems lineup in the high-memory Hopper configuration, NVIDIA's own turnkey 8x H200 machine, above the bare HGX baseboards (components, not systems), beside the OEM HGX H200 servers as the premium fully-NVIDIA-integrated option, alongside the DGX H100 (its standard-memory Hopper sibling) and below the DGX B200 (the current-generation Blackwell flagship). It is for organizations that want a complete, validated, supported high-memory Hopper system, with a clear path to SuperPOD-scale clusters. As flagship hardware in a regulated category, MillionMiner confirms the configuration, export eligibility for Hopper-class systems by destination, the site power and cooling fit, and the unit's condition before sale. Every system is tested and shipped worldwide DDP with duties handled, with hosting in MillionMiner's own data centers available. If you want NVIDIA's high-memory reference Hopper system turnkey, the DGX H200 is it; if you want the same GPUs at a different integration or price, MillionMiner will weigh the OEM HGX H200 servers with you.

NVIDIA DGX H200 1,128GB: The High-Memory Hopper DGX

The DGX H200 is NVIDIA's complete AI system in the high-memory H200 configuration, the company's reference platform built with the Hopper generation's large-memory GPU, delivered as a finished, tested machine rather than components to integrate.What it is. A complete 8x H200 SXM5 system: 1,128GB of total GPU memory (141GB per GPU), dual Xeon processors, system memory, NVMe storage, and high-speed networking, in one integrated, tested chassis, with NVIDIA's AI Enterprise and DGX OS software stack.What distinguishes it. Three things. The H200 memory: each H200 carries 141GB of HBM3e, more memory and bandwidth than the H100, so the DGX H200 holds the largest models and memory-bound workloads better than a DGX H100. Completeness: unlike a bare HGX baseboard, the DGX is the entire machine, ready to power on. And it is NVIDIA's reference design, a DGX SuperPOD and BasePOD building block that scales from one system to large clusters. The trade-off versus OEM HGX H200 servers is integration and support against price. MillionMiner confirms the configuration, export compliance, and condition in the quote, and ships worldwide DDP.

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NVIDIA DGX H200: The Complete, High-Memory DGX System

The DGX H200 is NVIDIA's complete, turnkey AI system in the high-memory H200 configuration, the finished machine, not a baseboard or a build-it-yourself kit. It integrates eight H200 SXM5 Tensor Core GPUs with 1,128GB of total GPU memory (141GB per GPU), dual Xeon processors, system memory, NVMe storage, and high-speed networking into a single tested system, ready to deploy with NVIDIA's software stack. It is structurally the DGX H100 built with H200 GPUs: the H200 is the high-memory member of the Hopper generation, with more memory and bandwidth per GPU than the H100, for the largest models and memory-bound training and inference. As a DGX SuperPOD and BasePOD building block, it scales from a single system to large clusters. Genuine flagship AI training and inference infrastructure, NVIDIA's reference platform. Shipped worldwide DDP by MillionMiner.

A Complete, Turnkey System

Not a baseboard, the finished machine. 8x H200, dual Xeon, system memory, storage, networking, and NVIDIA's software, integrated, tested, and ready to deploy.

1,128GB, the High-Memory Hopper DGX

Eight H200 GPUs, 141GB each, versus the DGX H100's 640GB total. The high-memory Hopper system for the largest, most memory-bound models.

A SuperPOD Building Block

NVIDIA's reference DGX platform, scaling from one system to DGX SuperPOD and BasePOD clusters. The validated path to large-scale AI infrastructure.

FAQ

Frequently Asked Questions

A complete, turnkey system. Unlike the bare HGX baseboards in this catalog, the DGX H200 is the entire finished machine: eight H200 SXM5 GPUs, dual Xeon processors, system memory, NVMe storage, high-speed networking, and NVIDIA's software stack, integrated, tested, and ready to power on. There is nothing to integrate yourself.

Memory. The DGX H200 is structurally the DGX H100 built with H200 GPUs instead of H100s. The H200 is the high-memory Hopper part, 141GB of HBM3e per GPU with more bandwidth than the H100's 80GB, so the DGX H200 has 1,128GB of total GPU memory versus the DGX H100's 640GB. For the largest models and memory-bound training and inference, the DGX H200 holds more in high-bandwidth memory; the two are otherwise the same Hopper generation and DGX design. MillionMiner will weigh them for your workload.

It is the key choice for acquiring an 8x H200 system. HGX is NVIDIA's GPU baseboard that OEMs build their own servers around; DGX is NVIDIA's own complete system on that same GPU technology. They use the same H200 GPUs, so raw GPU performance is comparable. The difference is integration and support: the DGX is NVIDIA's validated reference platform with its own software, support program, and SuperPOD/BasePOD cluster architectures; an OEM HGX server is that vendor's integration at a different price and support model.

They are NVIDIA's reference architectures for building clusters of DGX systems. BasePOD is a smaller-scale reference design, SuperPOD a larger one, both letting organizations scale from individual DGX systems to large, validated AI supercomputing clusters with NVIDIA's networking and software. The DGX H200 is a building block of these, so a buyer can start with one system and scale on a supported path. MillionMiner advises on the cluster configuration in the quote.

The H200 is the high-memory member of the Hopper generation. Each H200 carries 141GB of HBM3e with more memory bandwidth than the H100's 80GB. The two share the Hopper architecture, FP8, and the Transformer Engine; the H200's advantage is memory capacity and bandwidth, which directly benefits the largest models and memory-bound training and inference.

Eight H200 SXM5 GPUs with 1,128GB of total GPU memory (141GB per GPU), interconnected by NVLink and NVSwitch, with dual Xeon processors, system memory, NVMe storage, and high-speed networking, in a complete DGX chassis. MillionMiner confirms the exact CPU, system memory, storage, networking, performance figures, and software entitlement in the quote, since the live listing's specifics should be verified rather than assumed.

A DGX H200 draws several kilowatts under load (comparable to the DGX H100's ~10.2kW) and requires data center power delivery and cooling appropriate to that density. This is data center infrastructure, not an office machine. MillionMiner confirms the exact power and cooling requirements for your site in the quote, and offers hosting in its own data centers if you lack suitable facilities.

Yes, unreservedly. Eight high-memory Hopper H200 GPUs with 1,128GB of memory is top-tier AI training and inference infrastructure, and the DGX is the system NVIDIA itself positions as its AI infrastructure reference standard. Unlike the workstation and display cards elsewhere in this catalog, there is no overstatement to qualify.

Confirmed for the specific unit in the quote. As flagship Hopper-class hardware, condition and provenance matter, and MillionMiner verifies each system and states its condition and warranty clearly. The DGX H200 is also export-regulated, so MillionMiner confirms destination eligibility and the compliance position before sale.

Submit your workload, large-model training, fine-tuning, or inference, and scale through the quote form. A MillionMiner specialist confirms the configuration, the software entitlement, power and cooling requirements, export eligibility for Hopper-class systems, any SuperPOD/BasePOD cluster needs, and whether the DGX H200, the DGX H100, the DGX B200, or an OEM HGX server best fits your needs, then delivery. Every system is tested before shipment and shipped worldwide DDP with duties handled, with hosting in MillionMiner's own data centers available.