Compare AI image models against the job you need to complete. An attractive landscape does not tell you whether a model can preserve a specific bottle shape or leave enough space for campaign copy. A useful comparison controls the input, gives each candidate a similar opportunity, and scores the qualities that matter for your output.
Write the decision before the prompt
Choose a concrete question: “Which candidate produces the most usable studio product images from this reference?” List acceptance criteria before seeing results. For a bottle campaign, those might be silhouette, cap shape, surface material, lighting, and usable headline space.
Keep aesthetic preference separate from pass-or-fail requirements. A beautiful image with the wrong packaging cannot become the winner merely because reviewers like its mood. Also decide whether the comparison is about first-attempt quality, best result within a budget, or a fully edited final asset. Those are different tests.
Make the first round comparable
Explore the model catalogue on the Nova Creative canvas to identify candidates for the test. Start with a creative brief with visible review criteria so each candidate receives the same task.
- Give each model the same brief and the same permitted references.
- Request equivalent framing and aspect ratios where supported.
- Use the same number of initial attempts, or set an equal spending limit.
- Record model names, settings, run dates, and any unsupported inputs.
- Keep all results, including rejected candidates.
Identical numerical settings do not always mean equivalent behaviour across models. A seed in one model is not a matching scene seed in another. If one candidate lacks a required capability, record that limitation rather than quietly changing the task.
Use a small review sheet
For each output, mark factual requirements as pass or fail. Then score composition, realism, and editability on a consistent scale, such as one to five. Ask reviewers to explain low scores with visible evidence: “cap became metallic” is more actionable than “looks wrong.”
An illustrative test might compare two models on a blue ceramic mug, a transparent glass bottle, and a matte cardboard box. These examples probe different material and shape problems. Do not present this sample as a universal benchmark; it represents the tasks you selected.
Allow a second, documented round
A fixed prompt tests common-input performance. A second round can test each model with a prompt adapted to its documented input conventions. Report those rounds separately. Otherwise you may describe an optimized result as though it came from the original shared prompt.
In Nova Creative, use branches to organize alternatives from a common brief. Inspect each generator's actual supported inputs before connecting references. Keep the comparison small until you know which failure you are trying to solve.
Choose on usable output
Calculate spending across all attempts, then divide by the number of accepted assets. Include review and cleanup effort in the decision even if you track that separately from provider charges. The most useful model for this brief is the one that meets your requirements reliably within the resources available; it may change when the subject or delivery format changes.