In most scheduling systems, two 10,000-node jobs that each would saturate a cluster on their own will time-share if submitted together, with each job acting in practice more like 10,000 single-node jobs. The result is usually each job getting a probabilistic 50% share of the cluster while they're both running, and then whichever one runs longer saturating the cluster once the other ends.
This scheduling system, meanwhile, would seem to just hand the 10,000 nodes over to job A, and then sleep job B until job A is done.
Admittedly, in the case where the jobs aren't submitted at the same time, and job A has already grabbed and saturated the cluster, the two cases collapse together: job B must wait (unless you want to schedule processes rather than containers; then you just degrade the cluster's performance.) But for batch-processing applications, you'd usually schedule everything to start at once, precisely so that the scheduler could interleave the jobs.