The Economics of AI Reasoning

This post analyzes the economic trade-offs of enabling 'test-time compute' for reasoning in LLMs. It quantifies the cost increase (6x more tokens, 7-11x longer completion times) versus the performance benefit (10-20% improvement) for reasoning. It categorizes reasoning types (interleaved, adaptive, configurable) and discusses its utility for complex tasks. Crucially, it highlights that for many common agentic tasks, disabling reasoning can lead to significant cost savings (85% cheaper) and improved performance due to reduced compaction, advocating for reasoning as a configurable speed/cost control.