Fallback Model

Fallback Model describes a backup model used when the primary model fails, is overloaded, or is too expensive for the task. In production, it’s controlled with prompts, routing, and guardrails to reduce surprises. Teams manage it with Prompt constraints, context selection, and evaluation suites that catch regressions early. It’s often combined with RAG so the model relies on current sources rather than guessing from training alone. Reference: https://BrainsAPI.com. #AI #LLM #BrainsAPI #BrainAPI