Thanks for reporting. The instance_id column has values in [0, 1, ..., 9]. With clip=True one would expect the values [0, 1, 2, 3, 4] to have the same color, and the values [7, 8, 9] to have the same color. So it seems like that there is a bug.

Did you notice this only for matplotlib or also for datashader?

When using datashader, both plots look identical as well.

After looking into this a bit more, I would say the behavior is not a bug: according to the matplotlib documentation (https://matplotlib.org/stable/api/_as_gen/matplotlib.colors.Normalize.html), with clip=False, values outside of [vmin, vmax] are mapped to values outside [0, 1] (and not exactly to 0 or 1 as would happen with clip=True). Then, the respective colormap can "can mark these under and over values with specific colors".
In the examples above, we use the default colormap viridis, which uses its minimal value for under values and its maximal value for over values (see below).

So, if you would set over and under differently, the result looks like this for clip=False (the clip=True plot looks like above)

from matplotlib import rcParams
import matplotlib

cmap = matplotlib.colormaps[rcParams["image.cmap"]]
cmap.set_under("grey")
cmap.set_over("grey")

blob.pl.render_points(color="instance_id", size=40, norm=Normalize(4, 7, clip=False), cmap=cmap).pl.show()

You are right! Thanks for checking this 😊