Model routing
Intelligently choosing which model to run for each request based on latency, cost, or accuracy needs.
Think of it like
A dispatcher choosing between a fast courier and a slow truck depending on urgency and package size.
Example
Simple questions go to a fast, cheap 7B model; complex ones go to a slower, smarter 70B model.
How it actually works
Model routing lets you optimize cost and quality per request instead of one-size-fits-all. You need a router (ML model, rule engine, or heuristic) that decides which model to use. Challenges: building the router, handling failures, and explaining choices to users.
For product teams
Model routing can cut costs by serving simple requests cheaply.
For engineers
Build a router; instrument request metadata so the router has signal; monitor outcomes.
Read anything AI without the jargon
Look up any term in plain English, or save terms as you read with the free Chrome extension.
Open DecoderAdd to Chrome