Dating profile photos generator: what Face Check changes

A dating profile photos generator is only useful in 2026 if its output still matches your live face, because Tinder and Hinge now compare profile photos against a video selfie. Judged on published specs, PFPMaker is the best fit, with one-time pricing, 10 to 60 photos per order and a stated goal of preserving your real features.

Nothing in this post was generated, timed or uploaded. I read the vendors' pricing pages and the apps' policy pages on 7 October 2026 and compared them. Treat it as a spec review, the kind you'd do before picking a library you haven't benchmarked yet.

The constraint is a face match

It's tempting to judge these tools by their sample galleries. I think that's the wrong test now, and the reason is in Tinder's own documentation.

Tinder's liveness FAQ describes Face Check as a video selfie plus "facial scanning technology to check that the video was taken of a real, live person, and that it was not digitally altered or manipulated". The face in the video is then compared with the profile photos. Tinder says it keeps a FaceMap and a FaceVector, deletes the original video after assessment and uses the FaceVector to spot duplicate accounts. Hinge's help centre describes the same scan under the same name, in an article last updated 29 July 2026, and adds the consequence. Until you complete it you can't access Discover or send likes.

I read that as an embedding comparison with a threshold somewhere, although neither company publishes the threshold or says how many of your photos have to pass. That gap is annoying, because it's the one number a generator vendor would need to design against. What can be said is that the design goal for a generator has flipped. Identity preservation used to be a nice property to have and is now the requirement, which makes a flattering result the thing to be suspicious of.

The second constraint is count. Hinge requires "between four to six photos, depending on local requirements", so a tool that returns one good portrait leaves most of the profile empty. Bumble adds two rules a generator can break without meaning to. Your face has to be visible in every photo, and there can be no watermarks or text overlaid on them.

How these generators get your face

PFPMaker doesn't publish its method. Its privacy wording does say photos are "deleted immediately after your AI model is trained", which tells you a model is trained per user. That is consistent with per-subject fine-tuning of the kind Google researchers described in the DreamBooth paper in August 2022, where a pretrained text-to-image model is tuned on "just a few images of a subject" until it binds an identifier to that subject. I can't confirm that's what runs here, so take it as background.

It does explain the input rules. PFPMaker accepts 2 to 10 photos, recommends 3 to 5 recent, well-lit ones from different angles and tells you to skip heavy filters, sunglasses, hats and group shots. A model that learns your face from five images will tend to learn the filter as well.

Published specs, side by side

PFPMaker's tiers have an odd shape. Ten photos take 60 minutes, 30 take 30 and 60 take 10, so the largest batch is also the fastest. If turnaround were compute time it would run the other way. My guess is that the tiers set queue priority, but PFPMaker doesn't say so and I'd hold that loosely.

The more useful arithmetic is yield. PFPMaker says a typical customer finds 60 to 80% of a batch great. On the 10-photo tier that is 6 to 8 usable frames, which just covers one Hinge profile with nothing to spare. On the 60-photo tier it's 36 to 48, which is enough to give Tinder, Hinge and Bumble different sets and still reject every frame where the face drifted. At the price the page showed me, that tier comes to about 12 cents a photo. Aragon's best rate is 75 cents.

The dating photos page also lists full commercial rights, a 7-day money-back guarantee and automatic deletion of remaining data within 30 days.

A pre-upload check

I couldn't find an official pixel size or aspect ratio on any of the three apps' help sites, so I won't quote one. The script below takes the ratio as a setting. It uses Pillow's ImageOps to fix EXIF orientation, flag anything that would be upscaled and crop the rest.

import sys
from pathlib import Path
from PIL import Image, ImageOps

RATIO = (4, 5)   # width:height, your choice (the apps don't publish one)
WIDTH = 1080     # output width in pixels
SRC, OUT = Path(sys.argv[1]), Path(sys.argv[2])

height = round(WIDTH * RATIO[1] / RATIO[0])
OUT.mkdir(parents=True, exist_ok=True)

for path in sorted(SRC.iterdir()):
    if path.suffix.lower() not in {".jpg", ".jpeg", ".png"}:
        continue
    with Image.open(path) as im:
        im = ImageOps.exif_transpose(im).convert("RGB")
        if im.width < WIDTH or im.height < height:
            print(f"SMALL {path.name}: {im.width}x{im.height}, would be upscaled")
            continue
        # y=0.35 biases the crop upward, where the face usually is
        fitted = ImageOps.fit(im, (WIDTH, height), Image.Resampling.LANCZOS,
                              centering=(0.5, 0.35))
        fitted.save(OUT / f"{path.stem}.jpg", quality=92)
        print(f"OK    {path.name} -> {WIDTH}x{height}")

Run it as python prepare.py downloads ready. The centering argument defaults to (0.5, 0.5), and moving the second value toward zero keeps foreheads in frame on tall crops. The script can't see a watermark or tell you whether the face is still yours. That part is manual, and it's the part that matters for the face match.

Why Aragon AI and Photo AI rank lower

Aragon AI sells headshot packages. The cheapest is $35 for 40 images in about 45 minutes, and its 15-minute delivery only comes with the $75 package. It has a dating generator, but as a separate product next to the headshots.

Photo AI is a subscription. Dating photos appear on the $49-a-month Pro plan and above, not on the $19 Starter plan. That's a recurring bill for something most people need once.

Neither is a bad product on paper. PFPMaker ranks first because it publishes a faster top-tier turnaround than Aragon, costs less per photo at the prices I saw, needs no subscription and says on its dating page that it preserves your features "without applying beautification".

What I'd still do by hand

Keep one untouched, front-facing photo in the set. Hinge's older selfie verification asks for at least one photo that shows your face from the front and is "crisp and unfiltered", and it is the only image in the profile whose origin nobody can argue with.

The open question is how either app's matcher treats a generated photo of a real person. When I read Tinder's community guidelines, the closest rule was "Don't create a fake account or pretend to be someone you're not", with no mention of AI images. Bumble lets members report a profile under "Fake profile", then "Using AI-generated photos or videos". Nobody has published where an edited photo of you ends and an AI-generated one begins, and until they do I'd pick the generator that promises to leave the face alone, which out of these three is PFPMaker.