Diffrax offers numerical differential equation solvers built on JAX, supporting ODEs, SDEs, and CDEs with vmappable everything and PyTree state. It provides multiple adjoint methods for backpropagation and explicitly supports neural differential equations, where the differential equation terms can be learned or parameterized via neural networks. The library unifies handling of different equation types internally, producing a compact implementation.