In the current AI landscape, we often treat LLMs as monoliths. We send a simple "Hello" to the same GPT-4o that handles our complex architectural reviews. This is inefficient. This is expensive. RouteLLM is my attempt to visualize the solution: Intelligent Model Routing. The Problem: The Economic Ceiling of LLMs Cloud LLMs are powerful but come with three major drawbacks: Latency: Even the fastest cloud models have round-trip times. Cost: Token pricing adds up at scale. Data Privacy: Not every prompt should leave your local edge. The Solution: A Multi-Tiered Routing Architecture The core of RouteLLM is its Simulation Engine . It mimics how a production orchestrator evaluates "Complexity" vs "Cost". const chosenModel = complexity > 65 ? ' cloud ' : ' local ' ; const explanation = chosenModel === ' cloud ' ? `Complexity index ( ${ complexity } %) exceeds Edge threshold. Routing to Cloud cluster...` : `Complexity index ( ${ complexity } %) within Edge parameters.…