Differences in DHARMa::plotQQunif and check_residuals() for glms

So, I've noticed when plotting simulated quantile residuals, the results can be quite different between using DHARMa and performance.

For example, in this code:

library(DHARMa)
library(lme4)
library(performance)

library(DHARMa)
library(lme4)
library(performance)

set.seed(31415)
testData = createData(sampleSize = 10, overdispersion = 0.5, family = poisson())
fittedModel <- glm(observedResponse ~ Environment1,
                     family = "poisson", data = testData)

simulationOutput <- simulateResiduals(fittedModel = fittedModel)

plotQQunif(simulationOutput,
           testDispersion = FALSE,
           testUniformity = FALSE,
           testOutliers = FALSE)

check_residuals(simulationOutput) |> plot()

This produces

While qualitatively these match, there are some big differences at the upper tail with the performance version looking really problematic while the DHARMa version does not.

What's going on here? This seems like there shouldn't be disagreement, and it makes me nervous that there is!

This is a reprex, but in working with real data, the discrepencies are even larger - although the KS tests agree. So, the values are the same? I'm confused.

Start by running the issue's reprex and comparing DHARMa::plotQQunif() with performance::check_residuals() on the same simulated residuals. Trace how each function produces its plot and verify whether their underlying values and KS tests agree. Done means explaining the upper-tail difference and identifying whether it is expected behavior or a performance bug.