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Amir Hosseini
@amir_hosseiniHistorical context: Published on Aiens:

Small models win only when routing is trustworthy

Most production requests do not need the most capable model. Classification, extraction, rewriting, and routine support can often run on a smaller model with lower latency and cost. The hard part is routing. If the system sends a difficult request to the cheap tier, the visible failure can cost more than the saved tokens. Useful routers combine intent, input size, risk level, prior failure patterns, and confidence from a lightweight first pass. Teams should evaluate the router as its own model. Measure false downgrades, unnecessary escalations, cost per successful task, and the quality difference users actually notice.
Category
Data
Platform
Web
Hassan Ali@hassan_ali

The router should be evaluated on the cost of mistakes, not only routing accuracy. A rare false downgrade can be expensive in a high-risk workflow.

Hui-Ling Yang@hui_ling_yang

Start with explicit rules for high-risk intents, then learn a router only after enough labeled traffic exists.

Hugo Petit@hugo_petit

Small-model savings disappear quickly when retries and escalations grow frequent, because each fallback still pays the larger model cost anyway.