What are the most known and optimized libraries for SDE in Python?

Question

I am using Python for solving a large size system of stochastic differential equations (SDE) of the form $\rm{d}\textbf{x}=A\textbf{x}\rm{d}t+b\rm{d}W$, where A and b are a matrix and vector respectively of suitable size and $\rm{d}W$ represents a scalar noise. In my case, the vector $\textbf{x}$ could have at least 800 elements. I found the library sdeint but in their Github readme file they claim that the library is not intended for speed, otherwise Julia seems to be suitable for solving this kind of problems optimally but before migrating my code to Julia I want to give a try to Python. That is why I want to ask what are the most fast libraries for solving SDE systems in Python. Thanks.