# Timeseries VAR vs VARMA model: issue in time to fit model

I want to use VARMA model on a data of about 80000 samples with 10 features. I tried using VARMA model from statsmodels with p=50 and q=10 but it is taking too much time to build the model. I tested the model was running even after 12 hours. Then I tested VARMA using p=50 and q=0, this also was running even after an hour with maxiter=1. The code I am using is:

from statsmodels.tsa.statespace.varmax import VARMAX
modelVARMA = VARMAX(dff, order=(50,0))
resultsVARMA=modelVARMA.fit(maxiter=1)


I also tested VAR model with p=50 and it gave the model quickly. Is there any way to run VARMA model fast as it is in case of VAR.