diff --git a/tests/models/tvp/test_image_processing_tvp.py b/tests/models/tvp/test_image_processing_tvp.py
index 0b5d4e3bcb99..28581290e9d1 100644
--- a/tests/models/tvp/test_image_processing_tvp.py
+++ b/tests/models/tvp/test_image_processing_tvp.py
@@ -19,7 +19,7 @@
 import numpy as np
 
 from transformers.image_transforms import PaddingMode
-from transformers.testing_utils import is_flaky, require_torch, require_vision
+from transformers.testing_utils import require_torch, require_vision
 from transformers.utils import is_torch_available, is_torchvision_available, is_vision_available
 
 from ...test_image_processing_common import ImageProcessingTestMixin, prepare_video_inputs
@@ -349,16 +349,16 @@ def test_call_pytorch(self):
 
     @require_vision
     @require_torch
-    @is_flaky(
-        description="FIXME: @yoni probably because of an extra 'time' dimension and since image processors don't handle it well?"
+    @unittest.skip(
+        reason="FIXME: @yoni probably because of an extra 'time' dimension and since image processors don't handle it well?"
     )
     def test_slow_fast_equivalence(self):
         super().test_slow_fast_equivalence()
 
     @require_vision
     @require_torch
-    @is_flaky(
-        description="FIXME: @yoni probably because of an extra 'time' dimension and since image processors don't handle it well?"
+    @unittest.skip(
+        reason="FIXME: @yoni probably because of an extra 'time' dimension and since image processors don't handle it well?"
     )
     def test_slow_fast_equivalence_batched(self):
         if not self.test_slow_image_processor or not self.test_fast_image_processor: