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What is LLM model routing and how does an LLM cascade work?

For AI / LLM Engineer MLOps Engineer ML Engineer

The short answer

Model routing sends each query to the most appropriate model based on difficulty, cost, or capability, instead of always using the largest model. A cascade is a sequential form: try the cheapest or smallest model first and only escalate to a larger model if the answer fails a quality or confidence check, reducing average cost while preserving quality on hard queries.

How to think about it

Model routing sends each query to the most appropriate model based on difficulty, cost, or capability, instead of always using the largest model. A cascade is a sequential form: try the cheapest or smallest model first and only escalate to a larger model if the answer fails a quality or confidence check, reducing average cost while preserving quality on hard queries.

Learn it properly Model routing & cascades

Keep practising

How would you reduce the cost of serving an ML or LLM model in production without hurting quality? What techniques reduce LLM cost and latency in production? How does LLMOps differ from classical MLOps, and what new operational challenges do LLMs introduce? What is Mixture of Experts (MoE) and how does it improve LLM scalability? What causes LLM hallucinations and how can they be reduced?

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