How is the rise of reasoning models and test-time compute altering data center capacity planning?

Historical inference was a single fast forward pass that returned a token sequence immediately. Advanced reasoning models execute extensive chain-of-thought deliberation, tool calls, and recursive self-verification before responding. This dynamic shifts computational demand from training clusters toward sustained, continuous inference capacity distributed across edge and regional data centers.