sume/auto for images: no model named, no seed, so pin ids for brand

sume/auto picks an image family and never says which, and there is no seed. When Auto is fine, and when to pin an id like GPT Image 2.5.

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model: "sume/auto" lets Image Router choose the family, and Sume never discloses which one ran: it is not listed in GET /v1/images/models, and job.model stays sume/auto. The Image API also does not serve seed today. Together that means you cannot reproduce an Auto result or tell your design team which model made it. Use Auto to explore; pin an id such as openai/gpt-image-2.5 for anything brand-facing.

What the docs say

The Image API page lists Auto as a Sume-only value, notes that model echoes what you requested, and says output_compression and seed are in the schema but advertised by no model, so sending one returns 400 unsupported_parameter. It also says Auto routing continues to use Flare for the GPT Image 2.5 family. The legacy Image 1.0 URLs are compatibility aliases for the same Auto pipe.

Auto versus a pinned id on the Sume image route (read 2026-10-04)
Questionsume/autoPinned id such as openai/gpt-image-2.5
Which family ran?Not disclosedThe id you sent
Listed in GET /v1/images/models?NoYes
Parameters you can check beforehandNone published for Autosupported_parameters on the catalog record
Seed for repeatable outputNot servedNot served
Best forExplorationBrand and repeat work

Why pinning helps without a seed

A pinned id does not make two generations identical, since there is no seed. It does make them comparable: same family, same limits, same price line. With Auto, a style that worked last week may come from a different family next week and you will not see the change.

Pin the id in config, log it with the job metadata, which Sume stores on the job and does not send to the provider, and record the prompt and the reference URLs. That gives you a lineage you can audit.

{
  "model": "openai/gpt-image-2.5",
  "prompt": "Product on seamless white, soft shadow, centred",
  "quality": "high",
  "metadata": { "campaign": "autumn-launch", "variant": "v3" }
}

When Auto is the right call

  • First look at a new idea, where any decent result will do.
  • Throwaway visuals such as internal mockups.
  • A pipeline step where you check the output yourself every time.
  • Never as the only record of what made a hero image.

Moving from Auto to a pinned id

Run your usual prompt on a pinned id with n: 2, compare, and read supported_parameters for ratios and the reference range before you change anything else. A parameter the pinned model does not list is rejected, not ignored. See Jobs and results for storing the job record.

Sources

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