diff --git a/benchmarks/profile_linear_float8.py b/benchmarks/profile_linear_float8.py
index d8447e3..c5d7c44 100644
--- a/benchmarks/profile_linear_float8.py
+++ b/benchmarks/profile_linear_float8.py
@@ -19,7 +19,7 @@
 import torch.nn as nn
 import torch.nn.functional as F
 from float8_experimental.float8_dynamic_linear import Float8DynamicLinear
-from float8_experimental.float8_linear import Float8Linear
+from float8_experimental.float8_linear import Float8Linear, TensorScalingType
 from float8_experimental.float8_linear_utils import (
     linear_requires_sync,
     LinearType,
@@ -207,6 +207,9 @@ def main(
     profile_path_prefix: Path,
     compile: bool = True,
     linear_type: str = "dynamic",
+    scaling_type_x: str = "delayed",
+    scaling_type_w: str = "delayed",
+    scaling_type_dL_dY: str = "delayed",
     model_type: str = "linear",
     dtype_filter: str = "both",
 ):
@@ -250,9 +253,17 @@ def main(
     linear_cls = (
         Float8Linear if linear_type is LinearType.DELAYED else Float8DynamicLinear
     )
+    extra_kwargs = {}
+    scaling_type_x = TensorScalingType(scaling_type_x)
+    scaling_type_w = TensorScalingType(scaling_type_w)
+    scaling_type_dL_dY = TensorScalingType(scaling_type_dL_dY)
+    if linear_type is LinearType.DELAYED:
+        extra_kwargs["scaling_type_x"] = scaling_type_x
+        extra_kwargs["scaling_type_w"] = scaling_type_w
+        extra_kwargs["scaling_type_dL_dY"] = scaling_type_dL_dY
 
     m_float8 = copy.deepcopy(m_ref)
-    swap_linear_with_float8_linear(m_float8, linear_cls)
+    swap_linear_with_float8_linear(m_float8, linear_cls, **extra_kwargs)
 
     def ref_forw_backward(x):
         out = m_ref(x)
@@ -270,7 +281,9 @@ def float8_forw_backward_wrapper(x):
         # inspection of the fw+bw torch.compile without the scale
         # syncing code
         # TODO(future): make this better
-        if linear_requires_sync(linear_type):
+        if linear_requires_sync(
+            linear_type, scaling_type_x, scaling_type_w, scaling_type_dL_dY
+        ):
             with record_function("scale_amax_and_scales"):
                 sync_amax_history(m_float8)
         out = float8_forw(x)