Your example of "functional programming" is a pretty poor one. For starters, it is not functional because it uses state (it stores something in
words and behind the scenes
set(words) is doing stateful stuff as well). To actually learn what functional programming is about, you should look outside an imperative language such as Python. Python often uses imperative features dressed up as functional programming. Have a look at Ocaml or Haskell.
As for your question, people have thought about just how efficiently one can implement functional programs on standard hardware (which I think is what you're asking). At LICS 2015 the following paper has been accepted:
B. Accattoli, C. Sacerdoti Coen. On the Relative Usefulness of Fireballs. LICS 2015.
In it the authors show that a RAM machine (standard hardware) can simulate $\lambda$-calculus (functional programming) with a linear-time overhead with respect to the number of computation steps ($\beta$-reductions) of the functional program. This shows that functional programs can be efficiently implemented on existing hardware and will not in general consume a lot more resources.
Let me also point out that you cannot make the comparison you're trying to make in a sensible way. You are comparing two different algorithms that compute the same function. Instead, you should be comparing two implementations of the same algorithm in an imperative and a functional style. For instance sorting algorithms would do. And you should use a language that supports both imperative and functional programming. For instance, we could take merge sort and use the rosettacode.org functional implementation of merge srot in OCaml. Perhaps someone has the time to play with this and post some comparisons.