Take it into the measurable realm by doing some benchmarking and profiling. When it comes to programming in general, picking the right algorithm that keeps down the complexity gives several magnitudes more effect than trying to micro optimize in lower layers.

When it comes to the Python run-time, check how it's compiled. What optimization is used? How will it affect what Python does the most (whatever that might be)?

What's the aim? 1% faster? 10%? Depending on the goal, different methods might have to be combined. With a properly compiled Python runtime, good choice of algorithms and a reasonable memory footprint that doesn't cause too many cache misses, 1-5% might very well be possible.

And don't forget the Linux environment. What scheduling is used in the kernels delivered by Nokia and the community? Has anyone looked into backporting the new ones, like BrainF u c k scheduling, that's specifically aimed at making the desktop faster? This might make the N900 as a whole faster.

So, lots of variables.