Model Tiering and Mixing

Model tiering and mixing is an inference optimization strategy that routes requests to models of different sizes according to task difficulty: lightweight models handle simple tasks and large models handle complex reasoning, with cascading escalation for review, in order to control cost and limit error propagation.