Bayes factor = 0.00

Modeling
1

Hello,

I am using brms to run Multilevel models. I am comparing two models, with the same random structure and prior, using bayes_factor, as below


prior_rt = c(set_prior("normal(475, 100)", class = "Intercept"),
               set_prior("normal(0, 10)", class = "b"),
               set_prior("normal(0, 10)", class = "sd"),             
               set_prior("normal(0, 10)", class = "sigma"))

model1= brm(RT  ~  factor1* factor2+ (factor1* factor2| num_part)
                         , data = data_go_correct_seq
                         , family = exgaussian(link = "identity")
                         , warmup = 500
                         , iter = 3000                         
                         , chains = 2
                         , init = "0"
                         , cores = 2
                         , seed = 123
                         , prior = prior_rt
                         , save_pars = save_pars(all = TRUE)
                         )

model2= brm(RT  ~ factor2+ (factor1* factor2| num_part)
                         , data = data_go_correct_seq
                         , family = exgaussian(link = "identity")
                         , warmup = 500
                         , iter = 3000                         
                         , chains = 2
                         , init = "0"
                         , cores = 2
                         , seed = 123
                         , prior = prior_rt
                         , save_pars = save_pars(all = TRUE)
)


bayes_factor(model1, model2)

# Estimated Bayes factor in favor of model2 over model1: 0.00000

The result is 0.000. Is there an error? Because by looking at the summary of the models is clear that model 1 is better than model 2. I am confronting them because I am interested in the effect of factor 1

Thank you,