What's a cluster, really?
Any time a recommended build uses more than one GPU or machine, we call it a cluster. Here's what that word actually means — and doesn't.
The part that actually makes a cluster work
The word doing all the work in that definition is wired together. Real datacenter GPU clusters use dedicated high-speed interconnects — NVIDIA's NVLink between GPUs inside a machine (up to 130 TB/s across a full NVL72 rack), NVSwitch fabric tying 8 GPUs in a DGX system into one coherent pool, and InfiniBand networking linking whole racks together. That hardware is what lets one model's memory and computation span multiple GPUs without the GPUs constantly waiting on each other over a slow link. The software stack (schedulers, parallelism libraries) is built assuming that fast interconnect exists.
How our builds add up
When a build in this store spans multiple units, we always show the same three combined numbers:
- Combined GPU memory — the sum of every unit's memory, which is what determines whether the model fits.
- Combined power — the sum of every unit's power draw, in watts, with the everyday comparison alongside it.
- Combined price — the sum of every unit's price, so you see the real total cost of the build.
We do not make speed or performance claims from these totals — memory, power, and price add up arithmetically; real-world throughput depends on the interconnect and software, which is exactly the point above.