The test-time compute paradigm (allowing models to spend more computational resources 'thinking' before answering) is compute-intensive and justifies Stargate's $100B annual investment over 4 years because companies must build enormous clusters to deploy inference-time scaled models at scale while also continuing to train larger base models.