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MATLAB's 'parfor' loops can be significantly faster than 'for' loops, especially when dealing with large datasets or complex computations that can be parallelized. 'parfor' loops use multiple processors to execute iterations simultaneously, which can lead to significant speedups. However, the performance gains will depend on the specific application and hardware being used, and it is always recommended to benchmark and profile code to identify bottlenecks and optimize performance. Additionally, writing code that can be effectively parallelized requires careful consideration of dependencies and synchronization, and may require additional overhead compared to serial code.