AI Product Fidelity Benchmark
Compare controlled AI product-image tests with a weighted fidelity score, identity gate, retry count, product category, and private evidence report.
A reproducible approval method
- Lock one product briefKeep the same reference image, non-negotiable traits, prompt, aspect ratio, output count, and settings across every candidate.
- Score product identity firstWeight shape and proportions at 30%, packaging, logo, and text at 30%, materials and color at 20%, composition at 10%, and artifact-free usability at 10%.
- Apply the approval gateRequire at least 80% overall fidelity plus a minimum score of 4 out of 5 for both shape and packaging accuracy.
- Compare approved-result economicsDivide total credits by deliverable outputs only after the quality gate clears. A cheap rejected image is not an economical result.
- Keep portable evidenceCopy a readable methodology report or download versioned JSON for your records. Detailed briefs and candidate names stay in the browser unless you export them.
- Publish only credible aggregatesCommunity rows require explicit consent, a signed-in contributor, successful QuestStudio image runs from the last 90 days, a controlled model ID, and at least five distinct contributors for the same category and model.
AI Product Fidelity Benchmark FAQ
What counts as an approved product image?
This scorecard requires at least 80% overall fidelity, at least 4 out of 5 for both shape and packaging accuracy, and at least one output that you would actually deliver. Change the rule for your own client only if you document it before testing.
Why compare cost per approved result instead of price per generation?
A cheap generation is not economical when packaging errors or product drift force repeated attempts. Cost per approved result divides the total credits spent by the number of outputs that cleared the locked quality bar.
Does this benchmark upload my product images?
No. This public benchmark is a manual scorecard and does not request or upload product files. Keep the same reference, prompt, aspect ratio, and approval rule open beside every candidate while scoring.
Can the same model score differently on another product?
Yes. Transparent glass, small label text, unusual closures, reflective packaging, and multi-object scenes create different failure modes. Treat the winner as specific to the locked product brief, not a universal model ranking.
Is my benchmark evidence report public?
No. The detailed brief, candidate names, and exported report stay in your browser unless you copy or download them. If you explicitly opt in while signed in, QuestStudio stores only category, controlled model IDs, scores, attempts, credits, and deliverable counts for thresholded aggregates.
When does community benchmark data become public?
A category and model combination appears only after at least five distinct signed-in contributors opt in and each reported attempt matches a successful QuestStudio image run from the last 90 days. Repeat submissions from one account update that account's contribution instead of increasing the sample size.