It actually wouldn't surprise me if they optimized for bar/qr code readability. I wrote something years ago that used industrial cameras to read QR codes as well as very precise metrology features. I had to optimize the optical/lighting setup for the feature measurement and then wrote some finely-tuned operations to identify the QR code, window down to the code only, clean up edges/features with expensive convolutions (mostly median filter) and then finally read the code. None of this was visible to the operator, but if you saw the final image of the QR code it was essentially binary color space and looked a bit cartoon-like.

Did you do your tests in good lighting?

Did you compare raw sensor output, or post-processed?

Big sensors capture more light and have more bokeh. With enough light, the first doesn't matter, and bokeh is not a thing for QR codes.

If you didn't have enough light, then it's probably the question of how denoising was done, and what details have been guessed by fancy algorithms. Geometrical shapes are easy to guess, but when I look at pictures of landscapes, they typically devolve into a painting after 1000×1000px if taken on a phone.