
Two portrait photos beside a similarity percentage gauge showing how a face similarity checker scores a match
You generated twelve portrait variants. Three match your reference. Nine look like strangers. Eyeballing thumbnails at midnight is slow, and you second-guess yourself every time, especially when you're batch-checking AI art or storybook pages before you ship.
A face similarity checker fixes that. You upload a reference photo, it scores your test images, and it tells you how close two faces are without the guessing. This guide is for AI artists, founders, and parents doing QA on personalized books. It's not for law-enforcement ID checks. TheFluxTrain's free AI Face Score runs face-api.js in your browser. Photos aren't sent to our servers for scoring, there's no account, and no credits.
Quick answer: A face similarity checker compares two photos and returns a match score. Open TheFluxTrain's free AI Face Score tool, upload a reference photo, add test images, and read the similarity percentage for each. Processing stays in your browser with no account required.
Anyone asking "do these two photos look like the same person?" The tool handles creative QA, not biometric enrollment.
Typical users:
You need a clear reference face, decent lighting on the tests, and about two minutes. No ML background required.
What you need: one reference photo (front-facing, face unobstructed) and one or more test images, which can be AI portraits, storybook exports, or extra real photos. A modern browser. The face-api models download on your first visit, a few MB.
Steps:

The tool spells out the flow: upload real photos plus your AI images, run the analysis in your browser, then read a sorted similarity list. Everything happens on your device.
Note- you can upload several real photos to compare candid shots against the same reference, not only AI output.
A good match reads as the same person at the size you'll actually ship, whether that's a thumbnail, a storybook spread, or a video still. The highest number isn't always the right pick.
Trust the result when the eyes, nose, and jawline line up as you flip between the two images. The hairline and face shape should stay in the family. Skin tone can feel consistent even when the hairstyle or wardrobe changed.
Regenerate when the score is high but the face looks uncanny. Same when the profile or the ears are wrong even though the front view scored well. In a group shot the tool may lock onto the wrong face, so crop to a single face before uploading if you need a precise read.
A batch-QA walkthrough across a full character set is coming soon.
Each 0–100% value comes from face-api.js face descriptors, which are numerical fingerprints of facial geometry. TheFluxTrain converts the Euclidean distance between two descriptors into a percentage. Lower distance means higher similarity.
Rough guide:
Scores are relative within a batch. A 72% winner among five variants is useful even when the right threshold shifts with art style. Deeper rules on the percentage itself are planned in a follow-up guide.
Example: one reference headshot plus six AI portraits come back at 81%, 76%, 68%, 54%, 41%, 38%. Keep the top two for retouching or video. Regenerate the bottom four with the same reference attached to your image model, rather than accepting "close enough."
A face similarity checker ranks how alike your two photos look and returns a percentage, and the processing stays local in the browser. Facial recognition, the enterprise or government kind, matches faces against enrolled databases to answer "who is this?" TheFluxTrain's tool uses face-api.js on your device only. It's not ID verification. If you prefer the phrase "face comparison," it's the same workflow, and a dedicated guide is coming soon.
Use it as a gate before the expensive steps: video generation, print orders, or publishing a character bible.
When I was batch-checking character stills for motion work, I used to open every thumbnail at full size and move on. A sorted score list is faster and a lot more consistent than gut feel.
It pairs well with character bibles, since the similarity score confirms the model actually honored the face you attached. Storybook makers run each illustrated page the same way.
When a score surprises you, swap in a cleaner frontal reference and run it again.
A face similarity checker compares two photos and returns a match score showing how closely the faces resemble each other. It is a creative QA tool, not a legal identity verifier.
Yes. AI Face Score runs in your browser at no cost with no account required. Images are scored locally, so they are not uploaded to a server for analysis.
TheFluxTrain uses face-api.js descriptor models. Scores reliably rank variants from one batch, but lighting, angle, and illustrated styles shift the numbers. Use scores to sort options, not as legal proof.
Yes. Upload one reference under Real Photos, then add several test images under AI Images, or several real photos. Results sort by highest similarity first.
No. Detection and scoring run in your browser via face-api.js. Images stay on your device unless you export results as JSON for your own records.
In everyday use, yes. Both mean checking whether two photos look like the same person. Searchers just use different phrases; the workflow is the same. A dedicated face comparison guide is coming soon.
There is no universal cutoff. Photoreal AI headshots often pass around 70–80%, while cartoon art scores lower but can still look right. Rank within your own batch and confirm by eye at full size.
Open AI Face Score, upload your reference, and score your next portrait batch in under two minutes. Keep the highest matches, regenerate the rest, and move on to storybook pages, ad creatives, or Flow Studio scenes.
More depth is on the way: batch QA for AI art, face-checking every storybook page, and face comparison terminology. They all use the same free tool.