Even in that case, you have the same problem:

you train on a corpus with context (e.g. sentences). The representation of a word will differ depending its context in the sentence
then you want to get representations by using a single word as input. There is no context. So the representation might be suboptimal because it was never trained to “have meaning” for a word without context

But as said before many times: the best way to be sure is just try it and compare with something as word2vec on your downstream task.