No one outside google really knows how the translation system works. It’s obviously based on machine learning but we do not know the parameters or the architecture they use exactly.
They updated their Google’s Neural Machine Translation System GNMT in 2016, to reduce the gap between Human and machine translation by including the context.
[…] Google has been able to continually improve quality of translations by enabling their systems to take into consideration not only source words and phrases, but also broader contexts of where they appear in sentences, and what are the other words and phrases around them. (How does Google translate work?)
Like all machine learning systems, it is not perfect. That is why you can find a certified translation for more easier -> plus facile even if it is not correct in English. They may have used some corpus, speeches to determine that. Or someone added manually the translation via community tab.
And because DeepL uses different architecture, different sources, they have not got the same result.
Machine learning is really complicated, it is pure mathematical and it depends on word vectorization, number of queries,…