diff --git a/tests/pipelines/stable_unclip/test_stable_unclip.py b/tests/pipelines/stable_unclip/test_stable_unclip.py
index 7bc351ad76..4b69a03fc5 100644
--- a/tests/pipelines/stable_unclip/test_stable_unclip.py
+++ b/tests/pipelines/stable_unclip/test_stable_unclip.py
@@ -189,6 +189,10 @@ class StableUnCLIPPipelineIntegrationTests(unittest.TestCase):
         pipe = StableUnCLIPPipeline.from_pretrained("fusing/stable-unclip-2-1-l", torch_dtype=torch.float16)
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
+        # stable unclip will oom when integration tests are run on a V100,
+        # so turn on memory savings
+        pipe.enable_attention_slicing()
+        pipe.enable_sequential_cpu_offload()
 
         generator = torch.Generator(device="cpu").manual_seed(0)
         output = pipe("anime turle", generator=generator, output_type="np")
diff --git a/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py b/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py
index adbf3b2727..539e0dcebe 100644
--- a/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py
+++ b/tests/pipelines/stable_unclip/test_stable_unclip_img2img.py
@@ -185,6 +185,10 @@ class StableUnCLIPImg2ImgPipelineIntegrationTests(unittest.TestCase):
         )
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
+        # stable unclip will oom when integration tests are run on a V100,
+        # so turn on memory savings
+        pipe.enable_attention_slicing()
+        pipe.enable_sequential_cpu_offload()
 
         generator = torch.Generator(device="cpu").manual_seed(0)
         output = pipe("anime turle", image=input_image, generator=generator, output_type="np")
@@ -209,6 +213,10 @@ class StableUnCLIPImg2ImgPipelineIntegrationTests(unittest.TestCase):
         )
         pipe.to(torch_device)
         pipe.set_progress_bar_config(disable=None)
+        # stable unclip will oom when integration tests are run on a V100,
+        # so turn on memory savings
+        pipe.enable_attention_slicing()
+        pipe.enable_sequential_cpu_offload()
 
         generator = torch.Generator(device="cpu").manual_seed(0)
         output = pipe("anime turle", image=input_image, generator=generator, output_type="np")