Nebius is the part of Yandex's international business that spun out in 2024 and now trades independently on Nasdaq, headquartered in Amsterdam and selling GPU compute plus a managed inference layer called AI Studio. The positioning is sensible. It undercuts the hyperscalers substantially, published rates start around a dollar an hour and run up through H100, H200 and newer Blackwell configurations, with commitment discounts on longer terms, while offering more operational assurance than a peer-to-peer marketplace where your instance is somebody's spare gaming card. For a team that wants predictable capacity without an enterprise contract negotiation, that middle ground is genuinely useful.
The documentation reflects a company that has done this properly for the main paths. Provisioning instances, attaching storage, setting up managed Kubernetes, calling the inference endpoints, deploying the turnkey applications like vLLM and Open WebUI. The AI Studio side is the more interesting half for most people, since it exposes hosted open models behind an OpenAI-compatible API. That compatibility decision is worth more than it sounds.
It means an existing application can be repointed at Nebius by changing a base URL and a key, which removes essentially all of the switching friction and makes it practical to actually compare providers on cost and latency rather than committing on a spreadsheet. More vendors should do this and the ones that insist on a bespoke SDK are making a choice against their own adoption. Where it gets thinner is the advanced end. Multi-node training, interconnect topology, the specifics of getting a large distributed run to behave, cluster-level tuning.
The documentation acknowledges these paths exist more than it walks you through them, and the practical answer becomes a conversation with their sales or support engineers. That is a normal shape for infrastructure companies and it does mean the self-service story degrades exactly at the point where the difficulty rises, which is unfortunate since that is where documentation earns its keep. There is no learning programme here at all. No academy, no certification, no structured tutorial series.
Reference docs and a console. I am marking that as a limitation rather than a failure, because a compute provider is not an education company and inventing a fake academy would be worse. It does mean that what you learn here is Nebius, and almost none of it transfers, beyond the general shape of provisioning GPUs which is broadly similar everywhere. One factor worth naming plainly because organisations will weigh it.
Nebius came out of Yandex, a Russian company, through a restructuring that separated the international business. The entity today is Dutch, publicly listed and operating under European rules, and the lineage is a matter of record and some procurement processes will ask about it. That is not an accusation of anything, it is a note that the question will come up and you should know the answer before you present the option internally. Search interest in Nebius AI Studio has fallen considerably over the past year, which likely reflects the initial launch attention fading rather than the platform declining, and it is worth knowing that the surrounding third-party tutorial ecosystem is small.
When you get stuck, you will be reading these docs or talking to their support, not finding a blog post from someone who hit the same wall. Three point eight. Solid documentation, fair pricing, genuine compliance advantages for some, and no educational ambition whatsoever.