FFT on a Raspberry Pi
Since you care about the time it takes, you'll want to use an optimized FFT implementation. That would be FFTw or FFTS, realistically. Historically, FFTw is way dominant in software (I mean, even Matlab uses that), but FFTS works really well on ARM, so might be the better choice for your Pi.
Then you'd just write a minimal C++ program that

creates an fftw_plan  / ffts_plan_t
generates random data (std::uniform_real_distribution is your friend in generating real and imaginary parts of numbers)
uses using sc = std::chrono; auto start = sc::steady_clock::now(); as a &quot;start&quot; timer,
fftw_execute/ffts_execute the plan on your random data
auto finished = sc::steady_clock::now();, and auto ms = sc::duration_cast&lt;sc::duration&lt;double&gt;&gt;(finished-start).count()*1000; to get the execution time in milliseconds.

You might want to run the actual plan multiple times (maybe even modifying the data in between) and divide the total time by the number of executions, to reduce the measurement error.

A note on the raspberry Pi: If you're using a modern RPi, don't use 32 bit operating systems, but go for an Aarch64 OS. In my experience, not having the SIMD instructions available in 64 bit mode really really hurts numeric throughput performance. (For an FFT, the better loop performance of aarch64 compilers might also help significantly; haven't benchmarked that.)