Regions and where your data sits

A provider’s map shows every place it has a building. The GPU you want may be in two of them. The newest cards arrive at a few sites first and can stay there for months.

So a review should record location for each GPU model: this card, these places, on this date.

There are three reasons. A law or a contract may fix where your data is processed. Distance adds delay to every request an inference service answers. And moving a large dataset to a far region takes time and may be billed as transfer.

For training with no fixed data location, the region matters least. Take the one with stock.

A region name is a label. Read what it commits to: a country, a city or a named facility. Read whether backups, logs and support access stay in the same place. The terms and the order form hold the answer, not the map.

Open the console and filter by the GPU you want. Note which regions offer it and which of those can start one today. Stock differs between regions of one provider, and so can price.

If the location must be proven, ask the provider in writing for the facility and the country. Keep the reply with its date.

Per GPU, not per provider: the places that list the card, which of them started one on the day, and whether the provider commits to a location in its terms. A count of regions on a map is not a review finding.

Availability is local. A card can be free at one site and gone at the next, and a quota granted in one region does not carry to another. A review that says a GPU can be started should say where.

If the region you need differs from the one a review checked, run the check again there before you plan around it.

Runcrate’s live feed lists the places each GPU model is offered. The feed gives one price per GPU, not one per place. Confirm the region on runcrate.ai on the day you start, because a feed moves.

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