NVIDIA H200 (SXM5)

A single NVIDIA H200 datacenter GPU. In the real world these are always sold and installed as a set inside a purpose-built server (typically 4 or 8 at a time on one board) — we list one individually here purely so you can see a single datacenter GPU's own specs. When you're actually buying, buy the whole server (like our DGX B200) rather than loose cards.

In Stock (17) Ships from United States

Specs & Fit Shipping & Returns

Price

$35,000

This is the price of the hardware itself, in US dollars. It does not include electricity, cooling, networking gear, or setup labor.

GPU count

This is how many separate GPU chips are inside the system. Multiple GPUs can be wired together (see "What's a cluster?") so their memory and computing power combine to run bigger models.

GPU memory (per GPU)

141 GB

GPU memory (also called VRAM) is the fast memory built into the graphics card itself. The AI model has to fit entirely (or almost entirely) inside this memory to run at a decent speed. This is usually the single most important number when you're buying hardware to run a specific AI model — if the model doesn't fit, it either won't load, or it runs painfully slowly.

GPU memory (total)

141 GB

CPU

Sold to be installed in a server with its own server-grade CPUs (see our DGX B200 below) — not a standalone desktop part.

The CPU ("central processing unit") is the traffic-controller chip: it loads data and hands work to the GPUs. For running AI models, the CPU matters far less than GPU memory — a modest CPU is fine as long as the GPUs are sized correctly for the model.

System RAM

512 GB

RAM is the computer's regular working memory (different from GPU memory). It holds data that isn't currently being crunched by the GPU. For running AI models, you mainly just need "enough that the CPU isn't waiting around" — it is not the number that decides whether a model fits.

What this power draw means

700 W

Power draw is how much electricity the hardware pulls when it's working hard, measured in watts (W). It affects your electricity bill, and at large scale, whether your building's power and cooling can even support the equipment.

0.6 average homes' worth of continuous power — To make a watt number feel real: we compare it to an average home, which draws roughly 1,200 watts around the clock (lights, fridge, HVAC, electronics, etc., averaged over a day). Dividing hardware wattage by 1,200 tells you how many average homes' worth of continuous power the hardware uses.
would drain a typical 90 kWh EV battery in about 128.6 hours — To make power draw feel real over time, we compare it to a typical electric car battery, which holds about 90 kWh (kilowatt-hours) of energy. That tells you roughly how many hours of running the hardware it would take to burn through one full EV battery's worth of energy.

Performance & fit

How this product actually measures up against the three big open models this store advises on — using the same memory math and build-cost numbers shown on each model's page, nothing new invented here.

Not sized for this Kimi K2.6 needs about 1320 GB of GPU memory — more than this product can reach on its own (and it isn't built to cluster with others for this).
Not sized for this GLM-5.2 needs about 904 GB of GPU memory — more than this product can reach on its own (and it isn't built to cluster with others for this).
Not sized for this DeepSeek V4 Flash needs about 341 GB of GPU memory — more than this product can reach on its own (and it isn't built to cluster with others for this).

Where these numbers come from

Specs from NVIDIA's official H200 product page.

Shipping information

Ships from United States. Standard orders typically leave our warehouse within 2–3 business days; exact delivery timelines still depend on your location and the size of the order — contact our team if you need a firm date.

Return policy

30-day satisfaction window from delivery for unopened or like-new condition. If something arrives damaged or not as described, contact us and we'll cover return shipping.

Warranty

Backed by the manufacturer's standard hardware warranty, with terms that vary by card and vendor. We can help coordinate a warranty claim directly with NVIDIA if you ever need one.