What is AI model routing? Matching each request to the right model
AI model routing sends each request to a model capable enough for the task, not the largest. How LLM routers decide, the tradeoffs, and how EcoRouter does it.
7 min read
AI Efficiency
Most AI requests do not need the largest model available. A short factual question, a reformatting task and a multi-step analysis place very different demands on a model, yet many products send all three to the same frontier model by default. The difference shows up as cost, latency and inference compute spent on capability the task never used.
This section is about closing that gap. We cover how AI model routing works — classifying a request, choosing an appropriately capable model, and escalating when a lighter model is not enough — and the tradeoffs that come with it: answer quality, latency, and the risk of routing a hard question too low. We also look at how to evaluate a router honestly, what a sensible baseline for comparison is, and where routing stops helping.
Articles here explain the general techniques first and EcoRouter's own approach second, with figures labeled as measured or modeled and sources cited. For how EcoRouter routes a question today, see how EcoRouter works.
Smarter AI starts with a better route.
Explore a more efficient way to use artificial intelligence with EcoRouter: it reuses useful knowledge when possible and routes new questions to the most efficient AI capable of answering them.