The outcome

Pin a model and fallback that meet documented quality, safety, privacy, latency, and cost limits.

Step by step

A workflow you can repeat.

  1. 01

    Define task, users, languages, modality, data class, quality, safety, schema, context, latency, throughput, region, retention, commercial use, cost, and rollback thresholds.

  2. 02

    Query the current catalog and record exact model IDs, providers, capabilities, licenses and terms, context, prices, limits, supported parameters, and lifecycle state.

  3. 03

    Run a frozen representative set with a server-side key, identical prompts and settings, bounded output, captured usage, errors, latency, and repeated trials where variance matters.

  4. 04

    Score correctness, grounding, safety, refusals, bias, schema validity, hallucination, tail latency, failure rate, privacy path, and total task cost.

  5. 05

    Pin the winner and an evaluated fallback, enforce allowlists, rate and budget limits, canary it, monitor model changes, and rerun tests before migration.

Working standard

What good use looks like.

  • Record exact model IDs and terms.
  • Measure tail latency and task cost.
  • Retest before every model change.

Official references

Check the current product documentation.