GPU clouds & neoclouds
Companies that own huge GPU clusters and rent slices of them by the hour, from big general clouds to specialist GPU-only providers.
Read first: GPU clusters & orchestration.
D1 · StoryFor young children and total beginners
Most people building AI don't own the giant computers it runs on. They rent them, a bit like hiring a car instead of buying one.
Some rental companies sell every kind of computer service. Others, called neoclouds, mostly rent out powerful AI chips.
Like: Hiring a car instead of buying one.
D2 · PictureFor curious beginners
Hyperscalers are the big general clouds: GPUs sit beside storage, databases, identity and networking you may already use, with many regions and compliance certifications.
Neoclouds are specialist GPU clouds. They focus on accelerators, often offer newer chips sooner or simpler pricing, and run fewer other services.
You can rent on demand (pay by the hour, may be unavailable), reserve capacity for a fixed period (cheaper per hour, you pay even when idle), or own hardware. Renting suits bursty or uncertain workloads; owning pays off only if the GPUs stay busy for years.
Like: Hiring a car by the day, leasing one, or buying one outright.
Where it breaks: Hire cars are interchangeable and plentiful. The newest GPUs are scarce, can sell out in a region, and large training jobs need thousands of them networked together in one place, which a rental counter can't promise.
D5 · FrontierFor experts
Where it gets harder: capacity for the newest chips often has to be reserved weeks or months ahead, so availability can matter more than price.
Specialist GPU clouds depend heavily on a few chip suppliers and large customers, and nobody yet knows how fast today's GPUs will lose their value as newer generations arrive.