Twirrim 14 hours ago | next [–] For what it's worth, I ported the sum example to pure python. def sum(depth, x): if depth == 0: return x else: fst = sum(depth-1, x*2+0) # adds the fst half snd = sum(depth-1, x*2+1) # adds the snd half return fst + snd print(sum(30, 0)) under pypy3 it executes in 0m4.478s, single threaded. Under python 3.12, it executed in 1m42.148s, again single threaded. I mention that because you include benchmark information: CPU, Apple M3 Max, 1 thread: 3.5 minutes CPU, Apple M3 Max, 16 threads: 10.26 seconds GPU, NVIDIA RTX 4090, 32k threads: 1.88 seconds The bend single-threaded version has been running for 42 minutes on my laptop, is consuming 6GB of memory, and still hasn't finished (12th Gen Intel(R) Core(TM) i7-1270P, Ubuntu 24.04). That seems to be an incredibly slow interpreter. Has this been tested or developed on anything other than Macs / aarch64? I appreciate this is early days, but it's hard to get excited about what seems to be incredibly slow performance from a really simple example you give. If the simple stuff is slow, what does that mean for the complicated stuff? If I get a chance tonight, I'll re-run it with -s argument, see if I get anything helpful.