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Image Generation Model Guide: GPT Image vs FLUX vs Seedream

Prototype content preview. Figures, author details, product claims and API examples are pending verification; examples are not confirmed integration instructions.

Resolution, speed, style control, and cost per image compared across the three most-used image models on our platform.

The three most-used image models on Starsg differ far more from each other than the text models do. Picking wrongly is expensive, because image calls are priced per image and retries are common.

Resolution and speed

  • GPT Image 1 — up to 1920px, 6-9s per image, strongest at legible text and UI mockups
  • FLUX — up to 2048px, 3-5s, best photorealism per dollar, weakest at typography
  • Seedream — up to 1536px, 2-4s, the fastest option and the best style consistency across a batch

Style control

If you need twenty images that look like they came from the same art director, style consistency matters more than peak quality. Seedream holds a reference style across a batch with almost no drift. FLUX drifts noticeably after about eight images unless you pin a seed and repeat the style clause verbatim.

Any image containing words belongs on GPT Image. The other two will produce beautiful, confidently misspelled text.

Cost per accepted image

List price per call is misleading. Measure cost per accepted image instead: multiply price by your retry rate. In our marketing-asset workload FLUX was cheapest per call and second-cheapest per accepted image, because 1 in 3 outputs was rejected for text errors.

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