diff --git a/tests/models/test_modeling_common.py b/tests/models/test_modeling_common.py
index d8a93d40c8bf..d9e70c6dd784 100644
--- a/tests/models/test_modeling_common.py
+++ b/tests/models/test_modeling_common.py
@@ -691,6 +691,9 @@ def test_deprecated_kwargs(self):
     def test_cpu_offload(self):
         config, inputs_dict = self.prepare_init_args_and_inputs_for_common()
         model = self.model_class(**config).eval()
+        if model._no_split_modules is None:
+            return
+
         model = model.to(torch_device)
 
         torch.manual_seed(0)
@@ -718,6 +721,9 @@ def test_cpu_offload(self):
     def test_disk_offload_without_safetensors(self):
         config, inputs_dict = self.prepare_init_args_and_inputs_for_common()
         model = self.model_class(**config).eval()
+        if model._no_split_modules is None:
+            return
+
         model = model.to(torch_device)
 
         torch.manual_seed(0)
@@ -728,12 +734,12 @@ def test_disk_offload_without_safetensors(self):
             model.cpu().save_pretrained(tmp_dir, safe_serialization=False)
 
             with self.assertRaises(ValueError):
-                max_size = int(self.model_split_percents[1] * model_size)
+                max_size = int(self.model_split_percents[0] * model_size)
                 max_memory = {0: max_size, "cpu": max_size}
                 # This errors out because it's missing an offload folder
                 new_model = self.model_class.from_pretrained(tmp_dir, device_map="auto", max_memory=max_memory)
 
-            max_size = int(self.model_split_percents[1] * model_size)
+            max_size = int(self.model_split_percents[0] * model_size)
             max_memory = {0: max_size, "cpu": max_size}
             new_model = self.model_class.from_pretrained(
                 tmp_dir, device_map="auto", max_memory=max_memory, offload_folder=tmp_dir
@@ -749,6 +755,9 @@ def test_disk_offload_without_safetensors(self):
     def test_disk_offload_with_safetensors(self):
         config, inputs_dict = self.prepare_init_args_and_inputs_for_common()
         model = self.model_class(**config).eval()
+        if model._no_split_modules is None:
+            return
+
         model = model.to(torch_device)
 
         torch.manual_seed(0)
@@ -758,7 +767,7 @@ def test_disk_offload_with_safetensors(self):
         with tempfile.TemporaryDirectory() as tmp_dir:
             model.cpu().save_pretrained(tmp_dir)
 
-            max_size = int(self.model_split_percents[1] * model_size)
+            max_size = int(self.model_split_percents[0] * model_size)
             max_memory = {0: max_size, "cpu": max_size}
             new_model = self.model_class.from_pretrained(
                 tmp_dir, device_map="auto", offload_folder=tmp_dir, max_memory=max_memory
@@ -774,6 +783,9 @@ def test_disk_offload_with_safetensors(self):
     def test_model_parallelism(self):
         config, inputs_dict = self.prepare_init_args_and_inputs_for_common()
         model = self.model_class(**config).eval()
+        if model._no_split_modules is None:
+            return
+
         model = model.to(torch_device)
 
         torch.manual_seed(0)