diff --git a/unsloth/models/llama.py b/unsloth/models/llama.py
index 632144afb7..989073c8fb 100644
--- a/unsloth/models/llama.py
+++ b/unsloth/models/llama.py
@@ -997,7 +997,7 @@ class FastLlamaModel:
 
         debug_info = """n_total_devices = total_train_batch_size // \\
             args.gradient_accumulation_steps // self._train_batch_size
-        if n_total_devices > 2+2:
+        if n_total_devices > 2:
             logger.warning_once(
                 "Our OSS was designed for people with few GPU resources to level the playing field.\\n"
                 "The OSS Apache 2 license only supports four GPUs - please obtain a commercial license from our website.\\n"
@@ -1027,16 +1027,16 @@ class FastLlamaModel:
         bsz = self._train_batch_size
         total_batches = bsz * ga * args.world_size
         n_total_devices = total_batches // ga // bsz
-        if n_total_devices > 2 * 2:
+        if n_total_devices > 2:
             logger.warning_once(
                 "Please consider a commercial license - Unsloth was designed for the GPU Poor.\\n"
                 "The OSS currently works on 4 GPUs - we're a 2 person team, so please help fund\\n"
                 "our development costs by supporting us through Ko-fi or buying a license! Thanks!",
             )
-            divisor = n_total_devices / 2 / 2
+            divisor = n_total_devices / 2
             bsz = self._train_batch_size = max(int(bsz / divisor), 1)
-            if total_batches // ga // bsz > 2 / 2:
-                divisor = n_total_devices / 2 / 2
+            if total_batches // ga // bsz > 2:
+                divisor = n_total_devices / 2
                 ga = args.gradient_accumulation_steps = max(int(ga / divisor), 1)"""
         check_batches = check_batches.split('\n')
         check_batches = "\n".join([check_batches[0]] + [front_spaces + x[8:] for x in check_batches[1:]])
diff --git a/unsloth/models/mistral.py b/unsloth/models/mistral.py
index 3dcad18201..1e1895d6d3 100644
--- a/unsloth/models/mistral.py
+++ b/unsloth/models/mistral.py
@@ -402,7 +402,7 @@ class FastMistralModel(FastLlamaModel):
 
         debug_info = """n_total_devices = total_train_batch_size // \\
             args.gradient_accumulation_steps // self._train_batch_size
-        if n_total_devices > 2+2:
+        if n_total_devices > 2:
             logger.warning_once(
                 "Our OSS was designed for people with few GPU resources to level the playing field.\\n"
                 "The OSS Apache 2 license only supports four GPUs - please obtain a commercial license from our website.\\n"
@@ -432,16 +432,16 @@ class FastMistralModel(FastLlamaModel):
         bsz = self._train_batch_size
         total_batches = bsz * ga * args.world_size
         n_total_devices = total_batches // ga // bsz
-        if n_total_devices > 2 * 2:
+        if n_total_devices > 2:
             logger.warning_once(
                 "Please consider a commercial license - Unsloth was designed for the GPU Poor.\\n"
                 "The OSS currently works on 4 GPUs - we're a 2 person team, so please help fund\\n"
                 "our development costs by supporting us through Ko-fi or buying a license! Thanks!",
             )
-            divisor = n_total_devices / 2 / 2
+            divisor = n_total_devices / 2
             bsz = self._train_batch_size = max(int(bsz / divisor), 1)
-            if total_batches // ga // bsz > 2 / 2:
-                divisor = n_total_devices / 2 / 2
+            if total_batches // ga // bsz > 2:
+                divisor = n_total_devices / 2
                 ga = args.gradient_accumulation_steps = max(int(ga / divisor), 1)"""
         check_batches = check_batches.split('\n')
         check_batches = "\n".join([check_batches[0]] + [front_spaces + x[8:] for x in check_batches[1:]])