diff --git a/fastvideo/eval/metrics/common/optical_flow/metric.py b/fastvideo/eval/metrics/common/optical_flow/metric.py
index 9b158463e..6e74cf3d3 100644
--- a/fastvideo/eval/metrics/common/optical_flow/metric.py
+++ b/fastvideo/eval/metrics/common/optical_flow/metric.py
@@ -251,7 +251,6 @@ class OpticalFlowMetric(BaseMetric):
     needs_gpu = True
     backbone = "optical_flow"
     dependencies = ["ptlflow"]
-    batch_unit = "frame_pair"
 
     def __init__(
         self,
@@ -284,22 +283,6 @@ class OpticalFlowMetric(BaseMetric):
         self._model.eval()
         self._model = self._model.to(self.device)
 
-    def trial_forward(self, batch_size, *, height, width, num_frames):
-        from ptlflow.utils.io_adapter import IOAdapter
-        io_adapter = IOAdapter(
-            output_stride=self._model.output_stride,
-            input_size=(height, width),
-            cuda=(self.device.type == "cuda"),
-        )
-        dummy_bgr = np.random.randint(0, 255, (height, width, 3), dtype=np.uint8)
-        pair_tensors = []
-        for _ in range(batch_size):
-            inputs = io_adapter.prepare_inputs([dummy_bgr, dummy_bgr])
-            pair_tensors.append(inputs["images"])
-        batched = torch.cat(pair_tensors, dim=0)
-        with torch.no_grad():
-            self._model({"images": batched})
-
     def _compute_flows_batched(
         self, pair_frames: list[tuple[np.ndarray, np.ndarray]], io_adapter,
     ) -> list[np.ndarray]:
diff --git a/fastvideo/eval/metrics/vbench/color/metric.py b/fastvideo/eval/metrics/vbench/color/metric.py
index 58618c5d6..6c7a9a246 100644
--- a/fastvideo/eval/metrics/vbench/color/metric.py
+++ b/fastvideo/eval/metrics/vbench/color/metric.py
@@ -26,7 +26,6 @@ class ColorMetric(BaseMetric):
     requires_reference = False
     higher_is_better = True
     needs_gpu = True
-    batch_unit = "video"
     dependencies = ["detectron2"]
 
     def __init__(self) -> None:
diff --git a/fastvideo/eval/metrics/vbench/multiple_objects/metric.py b/fastvideo/eval/metrics/vbench/multiple_objects/metric.py
index 78e854e44..ac8bdac83 100644
--- a/fastvideo/eval/metrics/vbench/multiple_objects/metric.py
+++ b/fastvideo/eval/metrics/vbench/multiple_objects/metric.py
@@ -20,7 +20,6 @@ class MultipleObjectsMetric(BaseMetric):
     requires_reference = False
     higher_is_better = True
     needs_gpu = True
-    batch_unit = "video"
     dependencies = ["detectron2"]
 
     def __init__(self) -> None:
diff --git a/fastvideo/eval/metrics/vbench/object_class/metric.py b/fastvideo/eval/metrics/vbench/object_class/metric.py
index aa8eba8a6..7fb092c21 100644
--- a/fastvideo/eval/metrics/vbench/object_class/metric.py
+++ b/fastvideo/eval/metrics/vbench/object_class/metric.py
@@ -20,7 +20,6 @@ class ObjectClassMetric(BaseMetric):
     requires_reference = False
     higher_is_better = True
     needs_gpu = True
-    batch_unit = "video"
     dependencies = ["detectron2"]
 
     def __init__(self) -> None:
diff --git a/fastvideo/eval/metrics/vbench/spatial_relationship/metric.py b/fastvideo/eval/metrics/vbench/spatial_relationship/metric.py
index 7fd119bc3..4b6ab8572 100644
--- a/fastvideo/eval/metrics/vbench/spatial_relationship/metric.py
+++ b/fastvideo/eval/metrics/vbench/spatial_relationship/metric.py
@@ -57,7 +57,6 @@ class SpatialRelationshipMetric(BaseMetric):
     requires_reference = False
     higher_is_better = True
     needs_gpu = True
-    batch_unit = "video"
     dependencies = ["detectron2"]
 
     def __init__(self) -> None: