diff --git a/autofit/mapper/prior_model/abstract.py b/autofit/mapper/prior_model/abstract.py
index 2e1f9f3ce..f36ddbb28 100644
--- a/autofit/mapper/prior_model/abstract.py
+++ b/autofit/mapper/prior_model/abstract.py
@@ -1778,11 +1778,6 @@ def info(self) -> str:
         parameter of the overall model.
         This information is extracted from each priors *model_info* property.
         """
-        from autofit.non_linear.test_mode import test_mode_level
-
-        if test_mode_level() >= 2:
-            return f"Total Free Parameters = {self.prior_count}\n\n[test mode — info skipped]"
-
         formatter = TextFormatter(line_length=info_whitespace())
 
         for t in find_groups(
diff --git a/autofit/non_linear/search/abstract_search.py b/autofit/non_linear/search/abstract_search.py
index 8e9f0a43b..afc8ea5e5 100644
--- a/autofit/non_linear/search/abstract_search.py
+++ b/autofit/non_linear/search/abstract_search.py
@@ -504,6 +504,9 @@ class represented by model M and gives a score for their fitness.
                 model=model,
                 info=info,
             )
+        else:
+            if hasattr(self.paths, '_save_model_info'):
+                self.paths._save_model_info(model=model)
 
         if not self.paths.is_complete:
             result = self.start_resume_fit(