I think the biggest issue in this code in the naive implementation of "powers". It runs in O(b) while it should take at most O(log(b)).
Also, the multiplication might be a bottleneck, there has been a lot of research in this area. (the original article mentions some)
It might be a good idea to use an arbitrary precision library like GMP, which provides super-fast multiplication and thus power() algorithms.
(It also has an implementation of Fib() which outperforms both approaches here, but that's not my point.)
I have not profiled the code, but I expect that the Newtonian approximation of sqrt is the slowest part.
It would surprise me if "powers" was a big problem relative to the rest. And no shortcuts: each of [1, b b², b³, b⁴, b⁵, …] (up to n) is used in the binomial expansion.
Hmm, I screwed up and wrote iterate instead of iterate' where I intended. Not that it really makes a difference.
In any case, the average time to print the first 20 Fibonacci numbers is 0.4157ms with matrix exponentiation and 1.707063s with exact integer math (yes, the units are different) on a T400.
It's straightforward (if messy) to calculate two rationals exactly, then approximate √5 to within certain error bounds.
I wrote some code which does this, just as an experiment... and it's unbearably slow. Just try it.