The Hidden Costs of LLM Routing and Model Switching
Recent testing reveals that switching between different large language models mid-session can inadvertently erase the cost savings promised by cheaper inference. This matters because developers and enterprises relying on dynamic routing must carefully weigh latency, context loss, and API overhead against theoretical per-token savings to ensure true economic efficiency.
Source: Towards Data Science