[mvanaltvorst]

In my experience, PyMC leads to models that are orders of magnitudes slower than equivalent models written in JAGS. Profiling is also extremely tedious, and there is no section in the PyMC docs that touches upon model performance.

I really like PyMC's API, but as soon as you move towards bigger datasets JAGS or Stan seem to be the only practical options.

[canyon289]

PyMC has a pretty active community where we help people with questions like these. Its hard to come up with one doc as folks have different hardware, datasets, models etc. I hope though you'll the devs and community to be friendly though!

https://discourse.pymc.io/t/how-to-increase-sampling-speed-w...

[ckrapu]

For models with >100 parameters, there are theoretical reasons for why JAGS can fail badly. It has to do with the mixing time of Gibbs samplers versus Hamiltonian Monte Carlo.