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This guide details strategies for optimizing LLM deployment costs by routing routine support queries to smaller models while escalating complex cases to larger ones. It evaluates specific architectural patterns, including static rules and classifier-based triage, alongside key metrics like escalation rates and total latency. The analysis provides a practical framework for balancing budget efficiency with response quality in customer-facing AI applications.
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Model Routing for Support Bots: Cheap-First FAQ Handling

OpenRouter8 min de cititArticolul și perspectiva sunt în engleză.

Cheap-first routing sends routine support questions to a small, inexpensive model and escalates selected hard or uncertain requests to a stronger one. This guide compares the three application-side routing patterns, separates what your application owns from what OpenRouter's Auto Router and model fallbacks handle, walks through a support flow with a copyable request, and sets out how to measure escalation rate and cost per resolved ticket.

Cheap-first model routing sends routine support questions to a small, inexpensive model and escalates selected hard or uncertain requests to a stronger model. It can reduce the cost of using a capable model for every message, as long as the cheaper path meets your support requirements. The three application-side patterns are static rules, classifier-based triage, and answer checks with confidence thresholds. This guide compares the three patterns, shows which parts of the flow OpenRouter handles, walks through a support flow with a copyable request, and sets out what to measure before you add escalation. Use static rules for narrow, recognizable FAQs, classifier-based triage for stable categories expressed in varied wording, and answer checks when a cheap model should attempt the response first. Keep support-policy acceptance checks in your application. Our model fallbacks handle request errors. A successful but incorrect answer needs a separate escalation decision in your code. Compare cheap-first against cheap-only and…

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