When to use different Word2Vec training approaches?

Question

So I am learning Word2Vec for the first time and my question is quite basic: How to know what approach to use? I.e, Word2Vec in Tensorflow or Word2Vec trained with Gensim ?

In what cases would implementing it through the more manual first approach be useful vs. the second one? If there is already an easier way to train a word2vec model using gensim, why is that not used always?

Furthermore, what is the benefit in using a pre-trained model like the Google News dataset? What happens when there are words that are not included in the news dataset?

Sorry if this question is basic, I just want to get a clearer grasp of the overall picture.