Short answer: use one OpenAI-compatible /v1/images/generations contract, keep the backend choice in model , and evaluate every provider with the same logistics candidate corpus. The winning integration is the one that preserves the request and response contract, respects model-specific limits, and produces an acceptable visual artifact without changing candidate facts. A gateway is useful when that substitution is the requirement; a direct specialist remains better when its native controls are the requirement.

That distinction matters in hiring operations. An image might illustrate a route planner candidate for an internal review card, but it must not silently turn “Class A CDL” into “Class B” or add an employment claim. The generated picture is presentation material. The structured candidate record remains authoritative.

What has to stay stable when the backend changes?

The stable boundary is small: model , prompt , size , and n .…