# Model Cascade

> A model cascade sends each query to a cheaper model first and escalates it to progressively more capable and expensive models only when a scoring function judges the cheaper model's answer unreliable.

- Identifier: PTL-0155
- Category: Prompt Optimization
- Canonical URL: https://protologue.com/t/model-cascade/
- Also known as: LLM cascade, FrugalGPT, cascading
- Introduced: 2023

## Description

Because many queries are easy, most are answered cheaply, and only hard ones pay for the strongest model. FrugalGPT reported matching the best single model's performance at a large reduction in cost. The design depends on a reliable way to judge when an answer is good enough. Routing, by contrast, chooses a model before any answer is generated.

## Related terms

- [Routing](https://protologue.com/t/routing/)
- [Confidence Calibration](https://protologue.com/t/confidence-calibration/)
- [LLM-as-a-Judge](https://protologue.com/t/llm-as-a-judge/)

## Sources

- Chen et al. (2023). FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance. https://arxiv.org/abs/2305.05176

## Cite this entry

Protologue. (2026). Model Cascade. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0155). https://protologue.com/t/model-cascade/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)