GPT-image-1-mini: evaluating a lower-cost image workflow

The model update

OpenAI released gpt-image-1-mini on October 6, 2025 as a cost-efficient image model.

Separate drafts from final assets

A team may need many rough composition options but only a few finished images. Evaluate those jobs separately. A draft needs to communicate a direction; a final product image may need accurate lettering, materials, and small details.

Set an acceptance threshold for each stage before running a comparison. If you change the threshold after seeing the output, it becomes difficult to explain the budget decision to another team.

Compare the complete production loop

Record the cost of all candidates used to reach an approved result. Include unsuccessful variations and any follow-up edits. Use the same source material and review rubric when comparing models.

For example, suppose one workflow spends $4 across candidates and produces eight approved assets. Its API cost per approved asset is $0.50. That is an illustrative calculation, not a model price or a measured benchmark.

Keep a quality escape route

A production system should make it possible to send a difficult brief for additional review or a different available model. Do not silently lower the review standard just to keep every request on a cheaper option. Check current model availability before adopting this historical release.