Code 
library(tidyverse)
library(targets)
library(brms)
library(glue)
library(tinytable)
library(lubridate)
library(here)

tar_config_set(
  store = here::here("_targets"),
  script = here::here("_targets.R")
)

# Models
tar_load(c(m_derogations, m_restrictions, m_hr))
Code 
model_times <- tribble(
  ~question, ~outcome, ~family, ~model,
  "Explaining derogations", "Derogation filed", "Logistic", m_derogations$m_derogations_panback,
  "Explaining derogations", "Other treaty action", "Logistic", m_derogations$m_other_panback,
  "Explaining restrictions", "Restricted movement", "Ordered logistic", m_restrictions$m_restrict_movement,
  "Explaining restrictions", "Close public transportation", "Ordered logistic", m_restrictions$m_restrict_pubtrans,
  "Explaining restrictions", "Stay at home", "Ordered logistic", m_restrictions$m_restrict_stayhome,
  "Explaining human rights violations", "Discriminatory policy", "Ordered logistic", m_hr$m_hr_discrim,
  "Explaining human rights violations", "Non-derogable rights", "Logistic", m_hr$m_hr_ndrights,
  "Explaining human rights violations", "Abusive enforcement", "Ordered logistic", m_hr$m_hr_abusive,
  "Explaining human rights violations", "No time limits", "Logistic", m_hr$m_hr_nolimit,
  "Explaining human rights violations", "Media restrictions", "Ordered logistic", m_hr$m_hr_media
) |>
  mutate(duration = map(model, ~{
    .$fit |>
      rstan::get_elapsed_time() |>
      as_tibble() |>
      summarize(total = as.duration(max(warmup + sample)))
  })) |>
  select(-model) |>
  unnest(duration)

dur <- as.period(as.duration(sum(model_times$total)))

total_run_time <- glue(
  "{hours} hours, {minutes} minutes, and {seconds} seconds",
  hours = hour(dur), minutes = minute(dur), seconds = round(second(dur), 0)
)

We ran these models on a 2021 M1 MacBook Pro with 32 GB of RAM, with 4 MCMC chains spread across 8 cores, with two CPU threads per chain, using Stan through {brms} through {cmdstanr}.

In total, it took 0 hours, 3 minutes, and 55 seconds to run everything.

Code 
total_time <- tibble(
  question = "Total", family = "—", outcome = "Total",
  total = as.duration(sum(model_times$total))
)

model_times_full <- model_times |>
  bind_rows(total_time)

group_labels_rle <- rle(model_times_full$question)
group_labels <- set_names(
  cumsum(group_labels_rle$lengths) - group_labels_rle$lengths + 1,
  group_labels_rle$values
) |> as.list()

model_times_full |>
  select(Outcome = outcome, Family = family, `Total time` = total) |>
  tt(width = c(0.4, 0.3, 0.3)) |>
  group_tt(i = group_labels) |>
  style_tt(
    i = as.numeric(group_labels) + 0:(length(group_labels) - 1),
    j = 1, bold = TRUE, background = "#e6e6e6", align = "l"
  ) |>
  style_tt(
    bootstrap_class = "table table-sm"
  )
Outcome Family Total time
Derogation filed Logistic 8.969s
Other treaty action Logistic 7.582s
Restricted movement Ordered logistic 16.767s
Close public transportation Ordered logistic 13.887s
Stay at home Ordered logistic 18.06s
Discriminatory policy Ordered logistic 81.565s (~1.36 minutes)
Non-derogable rights Logistic 9.58s
Abusive enforcement Ordered logistic 13.796s
No time limits Logistic 5.713s
Media restrictions Ordered logistic 58.946s
Total — 234.865s (~3.91 minutes)