Lasso regression coefficient inperpretation

Hi,

I got my data (predictors) and my response variable (Y_MOTOR) and I want to interpret the results when I build a Lasso model.

load('predictors.mat')
load('Y_MOTOR.mat')
[b,Stats] = lasso(predictors,Y_MOTOR,'Lambda', [0.001 0.01 0.1 1 10],'Standardize', true);

The b is a 41x5 matrix, each column represent a value for lamba. Lets say the best model is provided by lambda = 0.001 since is has the lowest value of MSE.

I got b values 0, some very close to zeor (4E-4 or E-3) and then I got 0.1 or 2 or 3 values.

My question is how to rank the regression coefficients in order to say X1 is the more important variable, after X4, etc can i just rank the absolute value of the regressors since they are at the same level because they were calculated with standardized data. Or is there any better metric or methodology?

Thanks for your time