Cascade Models

Multi-stage ranking pushes every candidate through each stage, gradually narrowing the set. Cascade models work differently. They handle the obvious cases with lightweight models and only escalate to more complex ones when confidence is low.

The key idea is simple: most inputs are easy to classify. You do not need a large model for every decision. A spam filter can confidently block an email with phrases like “you’ve won a lottery” or “claim your prize now” using simple rules or a lightweight classifier. A content moderation system can flag images that match known banned hashes without running a deep neural network.

By reserving expensive models for the small fraction of ambiguous cases, cascade models significantly reduce latency and cost while maintaining high accuracy.