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Cut inference cost per million output tokens by 70% while preserving quality and latency. Can you defend the target?

A cheaper GPU and a faster decoder do not automatically produce a cheaper service. Audit a cost ledger, reject misleading wins, and choose a rollout only after quality and latency gates pass.

Updated Oct 2026 · Worked answers on inference mechanisms, with calculations, implementation details, and follow-up questions.

A cheaper GPU and a faster decoder do not automatically produce a cheaper service. Audit a cost ledger, reject misleading wins, and choose a rollout only after quality and latency gates pass.

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FEDITOR'S NOTE

A percentage target is a hypothesis. Require the same workload contract, a declared quality margin, and an accounting period that includes idle and failed work before accepting it.

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