A cluster is several GPUs wired together so tightly that they act as one giant GPU. Think of it as bolting several desks together into one massive workspace.
Both can add up to a big "GB" number on paper. Only one of them can actually run a single huge model.
| At a glance | Real cluster — DGX H100 | Pile of desktop cards — 6x RTX 6000 Ada |
|---|---|---|
| Total memory | 640GB | 288GB |
| Interconnect speed | ~900GB/s per GPU (NVLink) | Standard Ethernet/Wi-Fi — roughly 1,000x slower |
| Can run a single large model? | Yes | No |
| Support | One NVIDIA support contract | 6 individual card warranties |
| Approximate price | ~$200,000 | ~$40,800 |
The honest takeaway: 6 RTX 6000 Ada cards add up to 288GB on a spec sheet, which sounds like it beats a single H100. But that number is not honestly comparable to a real cluster's shared memory — the desktop pile can't act as one machine, so it can't run one model that's bigger than any single card in the pile.
A big model has to load as one piece in memory — you can't hand it half a brain. Qwen3 235B, one of the models this store advises on, needs about 282GB to load. Our pile of 6 RTX 6000 Ada cards adds up to 288GB on a spec sheet — technically more than enough. But that memory sits in 6 separate 48GB islands, and no single piece of it is bigger than 48GB. It's like having six half-full gas tanks instead of one full one: the total fuel is there, but no car can run on six disconnected tanks at once. A real cluster's NVLink wiring is what turns 8 separate 80GB tanks into one true 640GB tank — that's the only way the "GB" number on the spec sheet becomes a number you can actually use.
When a build combines multiple systems, we always show the combined memory, power, and price together.
At the very top end, a single GB200 NVL72 rack is 72 GPUs wired into one machine: 13,500GB shared memory, 120,000W, ~$6.5M. That's about 100 average homes running non-stop — for one rack.