You might be waiting a while because Rokicki has stated in the past that it would take more computing power to optimally solve a single 4x4 state than it took to solve the entire set of 3x3s. As computers become more and more powerful this becomes more feasible without borrowing Google's supercomputers but I'm not aware of any serious attempts to optimally solve a hard 4x4 scramble. 5x5 is totally out of the question and 6x6, 7x7, 8x8 etc get more and more absurd unless some new technique is devised to reduce the workload.
I had the idea to take the paper's approach of finding optimal solutions for every possible 3-cycle of pieces (doing this on the 5x5 suffices for every piece on every cube size) and multiplying out the worst-case scenario for the amount of pieces present per cube but it's already been done:
I even read and upvoted this 7 years ago apparently. This gives a very high upper bound but it's still one that can be generalised to any
N no matter how large.
The bound could be improved by applying the general principal that the fewer & larger the subsets you divide the puzzle into, the shorter the total solution
should end up being. You could even take this to the limit of its absurdity and find optimal solutions for every state for corners, edges, midges, edge-centres, corner-centres, etc. then multiply these out by the amount of edge types present in the cube, but I doubt the upper bound would be close to the actual value of God's number.