It takes hours to run tSNE on 100k+ samples. 

But I ran it on 1M+ data points in minutes.

The biggest pain point of using tSNE is that its run-time is quadratically related to the number of data points.

openTSNE is an optimized Python implementation of tSNE, which provides massive speed improvements.

What's more, it can scale tSNE to millions of data points — a place where Sklearn implementation may never reach.

The effectiveness is evident from the image below. On a dataset of 70k images, the openTSNE implementation:
- is 20 times faster than the Sklearn implementation.
- produces similar quality clustering as the Sklearn implementation.