In classical test theory, reliability of a test is not a property of a test, it's a property of a test in a population.
If the mean is higher, you've either changed the test, or you've changed the population. In which case the reliability is different.
In more modern test theory (item response theory) reliability is a property of a score - a person's ability is measured with a certain reliability, which depends on their answers. But we can also talk about the reliability of a test at a particular ability level.
A test where the mean score is 70/80 (0.875) would probably have greater ability to distinguish between low and average ability (because these people can have a score from 0-70) than between average and high ability (because these people can have a score from 70-80).
A plot that shows the relationship between reliability and ability is called an item information curve. These curves are not necessarily smooth - here are some examples: https://www.researchgate.net/figure/Item-Information-Curves-Left-Panel-Test-Information-Curve-Upper-Right-Panel-and_fig3_261513596