Written by the BetterPic team. Disclosure: BetterPic does not publish this number either. That is the point of the piece.
Every comparison of AI headshot tools ranks on the same four things: price, image count, turnaround time and style count. All four are published, all four are easy to measure, and none of them predicts whether you will use the result.
The number that does is yield: of the images that arrive, how many would you actually put on a profile. Nobody publishes it. Here is why, and what to do instead.
Image count is inflated by near-duplicates. A hundred and twenty images sounds like four times sixty until you notice that they arrive in clusters of near-identical frames. What you want is the number of genuinely distinct usable options, and that is closer to style count than to image count.
Style count is inflated by styles you will never pick. A hundred and fifty styles and forty styles are the same product if you use one. Count the ones you would plausibly choose. For most people it is two: something plain for professional use and something slightly warmer.
Turnaround is real and almost irrelevant. The gap between twenty minutes and two hours matters for one afternoon and then never again, for a photograph you will use for two years. It gets marketed heavily because it is easy to improve and easy to put a number on.
Price barely varies. Entry points cluster between roughly $29 and $49 across the whole category. A $29 tool and a $35 tool are the same purchase.
Not because vendors are hiding it. Because it is not a property of the product.
Yield depends on your face, and these models fail unevenly across faces in ways that are consistent and well known: strong prescription glasses, tightly curled hair, darker skin tones, unusual face shapes, facial hair at certain lengths. It also depends heavily on what you uploaded, which the vendor does not control either.
So a single yield figure would be dishonest, and a per-face figure is not something a pricing page can carry. The result is that the category competes on the metrics it can publish, which are the ones that matter least.
Buy the smallest package on two tools. Upload an identical set to both — this is the step people skip, and it is the step that makes the comparison mean anything, because roughly half the variance comes from the input rather than the model.
Then count. Not "which batch looks better", but literally: how many of these would I put on a profile. That integer, divided by what you paid, is the only cost-per-outcome number in this category that is about you rather than about marketing.
In practice the answer is usually a lot lower than the sample galleries imply, across every tool. Galleries are curated from best results; they show the ceiling and never the median, and the median is what arrives in your inbox.
The failures are consistent across the whole category, so check the same five regions whatever you bought: hands if any are visible, ears, the arm of your glasses where it meets the temple, the boundary between hair and background, and any text on clothing or badges, which comes back as convincing gibberish.
Then check the two things that make a photograph unusable rather than merely flawed: whether your teeth are yours, and whether the model has taken a decade off you. Both are common, both flatter, and both reduce the recognition the photograph exists to create.
If you want to run the test with no money at risk on one side of it, a free tier of up to 10 images gives you a yield sample before you buy anything. And the side-by-side comparisons are worth reading for the published specs, as long as you remember what they cannot tell you.