The same integer-counting move can be exact while the value register changes from hand-enumerated toy cells to captured-scale cells.
highlighted = computed this step
The toy side is enumerable
A toy table with 4 rows and 2 features has 8 cells. Those cells can be listed, inspected, and recomputed by hand.
4×2=8
The larger side changes register
The captured-scale row has 1000000 rows and 768 features, so the count is 768000000. The count is exact; the values are named as captured cells, not hand-recomputed one by one.
1000000×768=768000000
What this comparison says
This is the toy-method boundary. It is NOT training, NOT learning, NOT generalization, NOT a scaling proof, NOT accuracy, NOT calibration, NOT probability truth, NOT model quality, and NOT real training cost.