Skip to main content
A model review should cover the intended task, capabilities, data handling, quality criteria, and cost evidence. Keep those decisions separate from whether a model appears in a catalog response.
The model catalog applies published availability and workspace entitlement rules. There is no released workspace approval-request queue or self-service model allowlist editor. Reading an eligible model does not grant permission to change catalog policy or prove runtime availability.

​
Review available models

You need access to the workspace and its model catalog.
1

Read the workspace catalog

Use List available AI models, optionally filtered by family. Inspect one model using its model_id. Record catalog_release_id and published_at with your review.
2

Document the decision

Record the use case, reviewer, acceptable data categories, expected output, and the evidence required for approval. Include backup models and any custom endpoint in the review scope.
3

Validate the proposed configuration

Follow models and voices and inspect the saved agent configuration. Publication still applies compatibility checks. Voice and custom-model publication remain unavailable, and execution has its own gate.
A model absent from your response may be unavailable to the workspace or excluded by the catalog query. Do not bypass that result with an invented model ID. Request an availability review through the Help Center.
No. Catalog listing and detail operations are reads.
No. Data-handling requirements need separately verified provider and execution behavior.