Google and Amazon have proprietary datasets for important sub-tasks (e.g. recognizing "consumer good" entities, or more accurate sentiment recognition, or supporting other languages better) that are not available to the public.

In other words, if your problem looks like one of the benchmarking tasks in NLP research (e.g. recognizing persons and locations in fluent text) you can expect good performance out of open source tools. If you go beyond that, you have to concoct your own dataset and/or use proprietary cloud services.

I recently tried out flair and deployed it myself on aws. Works nice. However, if you need heavy duty batch inference i guess you need to use a gpu instance or so ...