Inference throughout scales really well with larger batch sizes (at the cost of latency) due to rising arithmetic intensity and the fact that it's almost always memory BW limited.
One open secret is that batch mode generations often take much less than 24 hours. I've done a lot of generations where I get my results within 5ish minutes.
It can depend a lot on the shape of your batch to my understanding. A small batch job can be tasked out a lot quicker than a large batch job waiting for just the right moment where capacity fits.
No, 2.5 flash non-thinking was replaced with 2.5 flash lite, and 2.5 flash thinking had it's cost rebalanced (input price increased/output price decreased)
2.5 flash non-thinking doesn't exist anymore. People call it a price increase but it's just confusion about what Google did.
It's nice to see competition in this space. AI is getting cheaper and cheaper!