Assuming decent data, it won't be stochastic sampling for many math operations/input combinations. When people suggest LLMs with tokenization could learn math, they aren't suggesting a small undertrained model trained on crappy data.

I mean, this depends on your sampler. With temp=1 and sampling from the raw output distribution, setting aside numerics issues, these models output nonzero probability of every token at each position

A large model well trained on good data will have logits so negative for something like "1+1=" -> 3 that they won't come up in practice unless you sample in a way to deliberately misuse the model.