The author is speaking about the general concept of threading, outside of Python (without using C extensions to help out as discussed in the article). In general, if you don't have a GIL, and you have 2 or more cores then if you run additional threads you will see a speedup for CPU-intensive code. The actual speedup will vary. A sibling comment mentions embarrassingly parallel problems, those are things like ray tracing, where each computation is independent of all the others. In those cases, you get near linear speedup with each additional core and thread. If there is more coordination between the threads (mutexes and semaphores, for instance, controlling access to a shared datum or resource) then you will get a less-than-linear speedup. And if there is too much contention for a common resource, you won't get any speedup and will see some slowdown due to the overhead introduced by threads.