Model Cascading

An architecture where a fast, cheap model handles the first pass on every request, and only routes complex or low-confidence cases to a larger, more expensive model. Unlike a simple model router that picks one model upfront, cascading tries the small model first, evaluates the output quality, and escalates if needed. This pattern typically reduces inference costs by 50–70% while maintaining the quality ceiling of the most capable model.