Why Reasoning Models Just Broke On-Chain Agent Math Reasoning LLMs are slower per query and bill at a premium rate. The on-chain agent meta assumed cheap infere
On-chain agent systems are encountering issues with the performance and cost of advanced reasoning Large Language Models (LLMs). The underlying assumption that inference would be cheap and fast no longer holds true, as these models are slower and more expensive per query. This discrepancy is causing problems for the mathematical reasoning capabilities of on-chain agents, potentially undermining their effectiveness. AI
IMPACT The increased cost and latency of reasoning LLMs may require a re-evaluation of current on-chain agent designs and economic assumptions.