The outcome

Choose a model and fallback that satisfy measured quality, safety, latency, privacy, and cost requirements.

Step by step

A workflow you can repeat.

  1. 01

    Define the task, users, data class, success metrics, failure thresholds, latency, context, output schema, region, license, budget, and prohibited behavior.

  2. 02

    Shortlist current models and record provider, version, deprecation state, context, tool and structured-output support, pricing, moderation, and data-routing exceptions.

  3. 03

    Run a frozen representative set with server-side tokens, equal prompts and parameters, seeded runs where available, and captured usage, latency, errors, and outputs.

  4. 04

    Score correctness, citations, refusals, bias, injection resistance, schema validity, tail latency, failure rate, and total task cost with blinded human review where useful.

  5. 05

    Pin the winner, preserve the evaluation and license record, configure a tested fallback and cost ceiling, and schedule drift, deprecation, and policy checks.

Working standard

What good use looks like.

  • Freeze the evaluation set.
  • Measure total task cost.
  • Pin a model and test its fallback.

Official references

Check the current product documentation.