Contrasts coding in MixedModels

Hi guys,
I have implemented my SAS Mixed Model on Julia.
However, currently there are differences in estimates between SAS and Julia for fixed and random effects.
I tried changing the contrasts - maybe this can help to achieve more similar estimates to SAS .
I do it in this way:

const HC = HelmertCoding()
const contrasts = Dict(:var1 => HC, :var2 => HC, :var3=> HC, :subject=> Grouping())
model = fit(MixedModel, fm, data, contrasts=contrasts, REML=true)

Thus, I got three models (with different types of contrasts):


but my estimates are completely identical:

What am I doing wrong?
Are there any ways to get FE and RE estimates in Julia fully identical to SAS?

I would be grateful for any help!

Welcome to the community. Would you be able to provide a minimum working example with simulated data that replicates the behavior? That would help us diagnose the problem.