You quote a target of 200ms per embedding, not sure if it's one type of embedding in particular. I am using Infersent (a sentence embedding from FAIR https://github.com/facebookresearch/InferSent) for filtering and they quote a number of 1000/sentences per second on generic GPU. That's 200 times faster than your number, but it is a local API so I am comparing apples to oranges. Yet it's hard to imagine you are spending 1ms embedding and 199 on API overhead. I am sure I have missed a 0 here or there, but I don't see where, other than theirs is a batch number (batch size 128) and maybe yours is a single embedding number. Can you please clarify? Thanks