Three central levers determine the broader economics of AI inference: overall system performance, efficient infrastructure scaling, and continuous software optimization. Gains in system performance lead directly to more tokens generated across computing environments. As token generation expands through these performance improvements, the process results in higher revenue.
Infrastructure scaling proves efficient when system throughput grows proportionally as hardware gets added. Achieving this balance requires fewer resources to serve users at scale. Alongside hardware expansion, continuous optimization allows operators to generate more value from their existing infrastructure investments.