The outcome

Select and integrate a pinned model using evidence from a reproducible evaluation rather than a playground impression.

Step by step

A workflow you can repeat.

  1. 01

    Define the use case, data classification, region, model eligibility, output schema, evaluation set, quality thresholds, latency, and budget.

  2. 02

    Create an isolated Google Cloud project and service account with least-privilege Vertex AI permissions, quotas, billing alerts, and approved networking.

  3. 03

    Call candidate models through the current Gen AI SDK with pinned IDs, explicit system rules, bounded generation settings, and non-sensitive fixtures.

  4. 04

    Evaluate factuality, grounding, safety, multilingual behavior, structured output, long context, streaming, errors, latency, and token use consistently.

  5. 05

    Record model and configuration versions, deploy behind application validation and monitoring, and require regression review before any model change.

Working standard

What good use looks like.

  • Use one benchmark across models.
  • Pin model and generation settings.
  • Set quotas and billing alerts early.

Official references

Check the current product documentation.