diff --git a/scripts/spartan/World.py b/scripts/spartan/World.py
index 2bf3ad9..8be854a 100644
--- a/scripts/spartan/World.py
+++ b/scripts/spartan/World.py
@@ -409,6 +409,25 @@ class World:
             for job in realtime_jobs:
                 job.batch_size = job.batch_size + images_per_job
 
+        #######################
+        # remainder handling  #
+        #######################
+
+        # when total number of requested images was not cleanly divisible by world size then we tack the remainder on
+        remainder_images = self.total_batch_size - self.get_current_output_size()
+        if remainder_images >= 1:
+            logger.debug(f"The requested number of images({self.total_batch_size}) was not cleanly divisible by the number of realtime nodes({len(self.realtime_jobs())}) resulting in {remainder_images} that will be redistributed")
+
+            realtime_jobs = self.realtime_jobs()
+            realtime_jobs.sort(key=lambda x: x.batch_size)
+            # round-robin distribute the remaining images
+            while remainder_images >= 1:
+                for job in realtime_jobs:
+                    if remainder_images < 1:
+                        break
+                    job.batch_size += 1
+                    remainder_images -= 1
+
         #####################################
         # complementary worker distribution #
         #####################################
@@ -444,21 +463,7 @@ class World:
             logger.warning("Master couldn't keep up... defaulting to 1 image")
             master_job.batch_size = 1
 
-        # if the total number of requested images is not cleanly divisible by the world size then we tack that on here
-        # *if that hasn't already been filled by complementary fill or the requirement that master's batch size be >= 1
-        remainder_images = self.total_batch_size - self.get_current_output_size()
-        if remainder_images >= 1:
-            logger.debug(f"The requested number of images({self.total_batch_size}) was not cleanly divisible by the number of realtime nodes({len(self.realtime_jobs())}) resulting in {remainder_images} that will be redistributed")
 
-            realtime_jobs = self.realtime_jobs()
-            realtime_jobs.sort(key=lambda x: x.batch_size)
-            # round-robin distribute the remaining images
-            while remainder_images >= 1:
-                for job in realtime_jobs:
-                    if remainder_images < 1:
-                        break
-                    job.batch_size += 1
-                    remainder_images -= 1
 
         logger.info("Job distribution:")
         iterations = payload['n_iter']