Ideogram 4.5 high ($0.275) vs GPT Image 2.5 high ($0.0405)

For a 16:9 thumbnail at high quality, Ideogram 4.5 bills $0.275 on Sume and ChatGPT Image 2.5 at 1536x864 bills $0.0405, so Ideogram costs about 6.8 times more. Ideogram's page highlights text rendering. Test your headline on the cheaper one first, and pay for Ideogram's high tier only if it fixes a text problem you can see.

The numbers

Where the figures come from

Ideogram's list prices are $0.03, $0.06 and $0.22 per image for low, medium and high, with no change by image size, per fal's Ideogram V4.5 page (read 2026-10-07). ChatGPT Image 2.5's rate is fal's $30 per million output tokens applied to OpenAI's size and quality calculator, as the repo's estimator implements it; the 1536x864 values are that estimate for output tokens only.

A text test that costs cents

Write the exact headline and render it at each row's low tier first: $0.0375 on Ideogram and $0.0045 on GPT. Zoom in at the size a viewer sees, a small tile on a phone. Then raise quality only on the row and the prompt that need it. Ten prompts at low cost $0.375 on Ideogram and $0.045 on GPT 2.5.

What the guides say about format

YouTube asks for 16:9 for video thumbnails and accepts JPG and PNG (YouTube Help, read 2026-10-07). OpenAI documents custom GPT image sizes as multiples of 16, which 1536x864 satisfies (OpenAI guide, read 2026-10-07). On Sume, request 16:9 with output_format: "png" where the row lists it; Ideogram 4.5 chooses its own output format and does not take that field.

Region fixes instead of re-rolls

A text error in one corner does not need a whole new image. On ChatGPT Image 2.5, mask_url is listed for that row only, so a masked edit is the way to target one region. On other rows, plan on a re-run.

Compare the cost of fixing against the cost of re-rolling: three re-rolls at Ideogram high cost 3 x $0.275 = $0.825 billed, and the same three on GPT 2.5 at high cost 3 x $0.065875 = $0.197625. The cheap row gives you many more tries per dollar, which matters when text is the thing that fails.

Rule of thumb

Start on the cheap row at medium. Move to a dearer tier only when a specific word or letter is wrong in the output, and fix single regions with a mask_url edit on GPT 2.5 rather than re-rolling the whole image. Read usage.cost per call to keep your sheet honest. Parameters and prices are listed on the Image API page.