ModelRefs / Fallback Chain — AI Glossary
Fallback Chain — AI Glossary
A sequence of LLMs tried in order — if the primary model fails or is unavailable, the next model in the chain handles the request.
Overview
Essential for production reliability. Typical pattern: try OpenAI → fallback to Anthropic → fallback to a self-hosted model. LiteLLM and model gateways implement fallback chains natively.
Reference details
| Topic | infrastructure |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
A fallback chain reacts to failure; model routing chooses by fit before anything fails. Both may sit in the same gateway, and conflating them hides a gap: the fallback model receives a prompt tuned for the primary, and rarely gets the same validation. If the second model in the chain has never been evaluated on your traffic, the chain converts an outage into a silent quality drop.
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Frequently asked questions
What is Fallback Chain?
A sequence of LLMs tried in order — if the primary model fails or is unavailable, the next model in the chain handles the request.
What concepts are related to Fallback Chain?
Closely related concepts include model gateway, model routing.