GPU economics split buy, rent camps

This is the kind of AI infra question that matters more than benchmark chest-thumping, because bad compute economics can quietly kill side projects and small teams. For bursty workloads, the default answer is usually rent first, buy later.

• –Buying a GPU starts to make sense when usage is frequent enough that idle time stays low and having instant local access meaningfully speeds up experimentation
• –Renting wins when workloads come in bursts, because it avoids upfront hardware spend, depreciation, power draw, cooling, and the risk of buying into the wrong generation
• –Smaller GPU clouds can offer better pricing than hyperscalers, but developers still need to factor in availability, storage, setup friction, and egress costs
• –The real break-even rule is monthly total cost of ownership versus expected rented GPU hours, not just sticker price versus hourly rate