Inference
Inferenz
Running a trained model to get an output. In production it is the part you pay for on every single request.
01In short
Running a trained model to get an output. In production it is the part you pay for on every single request.
In productionLatency and cost live here — model choice, routing and caching decide your unit economics.
02Video
slot · videoInference in 90 secondsadd: GUIDES['inference'].video
03Guide
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A step-by-step guide for “Inference” goes here. Suggested outline:
- What it is — in one paragraph
- Why it matters in production
- How to do it — 3 to 7 steps
- Pitfalls we see in the field
04Checklist
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Four to eight things a team can tick before go-live.
05FAQ
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The three questions clients actually ask about “Inference”.
06Related terms
OperationsLatencyTime from request to answer. Users feel it; agents multiply it with every step.OperationsModel routingSending each request to the cheapest model that can handle it, and only the hard cases to the expensive one.OperationsCost per tokenWhat a model provider charges per input and output token.
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