24MP Educate me.

Is the Z6III better for video, or faster than the Z8 in other ways? Where exactly is the post?

I got it wrong from memory, but here it is with the Z9 , rather than Z8 against the Z6iii.

I was just curious about cameras with 24MP compared to higher MP sensors.

Interesting (and long) thread. I only read the first page, but that's enough to see the OP's motivations are that he doesn't personally need the Z9's resolution or a lot of its other features and '... the motive here is that trading in the Z9 for the Z6iii will increase the odds I'll carry the camera and use it.'

So I guess it makes sense to him.

For me, the only problem with a 20Mp camera, like my Canon R6, is that I need to pair it with a lens of the optimum focal length for the shot. So often that is the one I left at home for the day!

Alan’s observation about cropping is even truer with the 60Mp sensor of the Leica Q3...

David

I had an occasion where I cropped a picture from my Z7 to get this almost usable picture of a frog in full mating call mode. It was shot with my 24-200. It really needed a 600mm lens

It was just something I had never seen before.

The important metrics are how many photons are captured by area and how much noise there is per area as opposed to your pixel centric metrics above.
I think you will find no advantage to smaller pixels using per area measurements. Particularly if noise reduction is applied before resampling the images to a common size.
Sensor technology also plays a role. Sony a9iii is an example of a camera with large pixels and low photon capacity.

Maybe it’s time to remove Danno instead of providing a thousand warnings.

If that's important for you then you should know that monochrome sensors far surpass any CFA sensors in that metric. The CFA easily eats up half the photons.
Quantum efficiency and fill factor are of course important for different sensor technologies, but are irrelevant when just comparing pixel size.

That only applies to photon shot noise, but not for e.g. read noise.

What does noise reduction have to do with pixel size??
If your claim was true then people would just upsample their photos before attempting noise reduction, a simple algo like nearest neighbour and error diffusion would do.

But that isn't directly related to pixel size.

Actually the a9.3 pixel cells are about half the size of a conventional rolling shutter sensor. This cuts its FWC in about half, look at its spec'd native ISO.

At crop 3 (600mm/200mm) you got an effective aperture of f/30, far into diffraction territory.
An 1" sensor would have more pixels on the frog.
(e.g. a 18 MP Nikon 1V3 or 20 MP 1J5, and with the 1Nikkor 70-300 even more reach, up to 810mm equivalent)

I know, that is why I use monochrome sensors for most of my professional work

Even if the per area read noise is a bit higher with smaller pixels, detail can be traded for noise and you will still be better off with smaller pixels

In the end what matters is how much detail and noise is present in the developed image in standardized viewing conditions. Smaller pixels allow better noise reduction giving more detail with less noise even with higher read noise. As demonstrated by Jim Kasson here: Noise reduction with nonlinear tools and downsampling

Nope, upsampling does not produce anything else than a guess. But otherwise I agree: you don't have to downsample high res images to the lowest common denominator. You might as well try to upsample low res images to discover how inferior they are.

Don't try to mangle physical sensor pixel properties with computational postprocessing, debayering methods, AI noise reduction, etc.
Recent high-end smartphones already give a glimpse of what's possible with computational photography, that's another can of worms.

If you need higher resolution then more pixels sure help.
Hope you got an adequate lens, IS, storage media, etc.
There is no free lunch.

But upsizing involves interpolation which is much less of a guess than in any data manipulation involving extrapolation.

In my experience with today's modern AI driven upsizing any guessing is just about undetectable, especially under normal viewing conditions provided the upsizing is done within the limitations of the AI.

To compare image quality paired images should be analyzed at the same size. Resampling of one or both images is thus required if they were produced with different numbers of pixels. Smaller pixels provide more real data about the image projected by the lens, how you decide to use that additional information is obviously up to you, but I see no good reason not to trade resolution for noise if the end result is more detailed with less noise at the common image size.
As an example, I downloaded a1 and a9ii ISO25800 studio files from dpreview, examples where I expect read noise to be significant. They are supposed to have received the same exposure. I imported both in LR, applied luminance NR on the a1 file (20) before exporting a 6000px wide jpeg. The a9ii file was left to Adobe default and exported as a jpeg.
Here are a few screen dumps, a1 to the right.

I think the a1 file has more detail and less noise.

I think most lenses can produce aliasing in all current systems.

So you used your choice of different NR on the a1 only?!
🙈🙉🙊
Have a nice day.

You missed the point.
I traded detail for noise taking advantage of the higher resolution of the a1. The result when downsampled to a9ii dimension showed more detail with less noise as predicted by Jim Kasson.
No amount of noise reduction on the a9ii file will bring more detail.

But it could be interesting if you make a test of your own liking showing the benefit of large pixels.