I have the same problem, though my variant is closer to RNN than GRU, so I would think it would be even easier to optimize. Increasing the size has the same effect of shrinking the performance gap, but I need the feature size to be relatively small.
Would be great to figure out how to improve performance of jit RNNs. It’s a really simple model (and inference in C++ is lightning fast), so I’m not sure why it’s so slow.