diff --git a/torchao/float8/float8_linear.py b/torchao/float8/float8_linear.py
index b7a344927..4b3f271e2 100644
--- a/torchao/float8/float8_linear.py
+++ b/torchao/float8/float8_linear.py
@@ -312,13 +312,16 @@ def cast_input_to_float8(self, input: torch.Tensor) -> torch.Tensor:
             autocast_dtype = torch.get_autocast_gpu_dtype()
             input = input.to(autocast_dtype)
 
-        assert self.scaling_type_input is ScalingType.DYNAMIC
-        input_fp8 = hp_tensor_to_float8_dynamic(
-            input,
-            self.config.cast_config_input.target_dtype,
-            self.linear_mm_config,
-            gemm_input_role=GemmInputRole.INPUT,
-        )
+        if tensor_already_casted_to_fp8(input):
+            input_fp8 = input
+        else:
+            assert self.scaling_type_input is ScalingType.DYNAMIC
+            input_fp8 = hp_tensor_to_float8_dynamic(
+                input,
+                self.config.cast_config_input.target_dtype,
+                self.linear_mm_config,
+                gemm_input_role=GemmInputRole.INPUT,
+            )
         return input_fp8
 
     def get_weight_scale(self, weight: torch.Tensor) -> Optional[torch.Tensor]:
diff --git a/torchao/float8/float8_scaling_utils.py b/torchao/float8/float8_scaling_utils.py
index 3a9841e62..0c27e4f3f 100644
--- a/torchao/float8/float8_scaling_utils.py
+++ b/torchao/float8/float8_scaling_utils.py
@@ -52,8 +52,6 @@ def hp_tensor_to_float8_dynamic(
         scaling_granularity: Defines the scaling granularity
         axiswise_dim: if axiswise granularity is used, defines the dim to scale across
     """
-    if tensor_already_casted_to_fp8(hp_tensor):
-        return hp_tensor
     scale = tensor_to_scale(
         hp_tensor,
         float8_dtype,
diff --git a/torchao/float8/float8_tensor_parallel.py b/torchao/float8/float8_tensor_parallel.py
index 37cb67c7e..9d45196cf 100644
--- a/torchao/float8/float8_tensor_parallel.py
+++ b/torchao/float8/float8_tensor_parallel.py
@@ -9,6 +9,7 @@
 )
 
 from torchao.float8.config import ScalingType, e4m3_dtype
+from torchao.float8.distributed_utils import tensor_already_casted_to_fp8
 from torchao.float8.float8_scaling_utils import (
     NoopFwToFloat8BwDynamic,
     hp_tensor_to_float8_dynamic,
@@ -46,12 +47,13 @@ def _prepare_input_fn(
                 input_tensor, device_mesh, input_layouts, run_check=False
             )
 
-        input_tensor = hp_tensor_to_float8_dynamic(
-            input_tensor,
-            mod.config.cast_config_input.target_dtype,
-            mod.linear_mm_config,
-            gemm_input_role=GemmInputRole.INPUT,
-        )  # DTensor(Float8Tensor)
+        if not tensor_already_casted_to_fp8(input_tensor):
+            input_tensor = hp_tensor_to_float8_dynamic(
+                input_tensor,
+                mod.config.cast_config_input.target_dtype,
+                mod.linear_mm_config,
+                gemm_input_role=GemmInputRole.INPUT,
+            )  # DTensor(Float8Tensor)
 
         # transform the input layouts to the desired layouts of ColwiseParallel
         if input_layouts != desired_input_layouts:
@@ -104,12 +106,13 @@ def _prepare_input_fn(
                 input_tensor, device_mesh, input_layouts, run_check=False
             )
 
-        input_tensor = hp_tensor_to_float8_dynamic(
-            input_tensor,
-            mod.config.cast_config_input.target_dtype,
-            mod.linear_mm_config,
-            gemm_input_role=GemmInputRole.INPUT,
-        )  # DTensor(Float8Tensor)
+        if not tensor_already_casted_to_fp8(input_tensor):
+            input_tensor = hp_tensor_to_float8_dynamic(
+                input_tensor,
+                mod.config.cast_config_input.target_dtype,
+                mod.linear_mm_config,
+                gemm_input_role=GemmInputRole.INPUT,
+            )  # DTensor(Float8Tensor)
 
         if input_layouts != desired_input_layouts:
             input_tensor = input_tensor.redistribute(
diff --git a/torchao/float8/stateful_float8_linear.py b/torchao/float8/stateful_float8_linear.py
index 94851511b..7db72b993 100644
--- a/torchao/float8/stateful_float8_linear.py
+++ b/torchao/float8/stateful_float8_linear.py
@@ -153,7 +153,9 @@ def cast_input_to_float8(self, input: torch.Tensor) -> torch.Tensor:
             autocast_dtype = torch.get_autocast_gpu_dtype()
             input = input.to(autocast_dtype)
 
-        if self.scaling_type_input is ScalingType.DELAYED:
+        if tensor_already_casted_to_fp8(input):
+            input_fp8 = input
+        elif self.scaling_type_input is ScalingType.DELAYED:
             scale_fn_name = self.config.delayed_scaling_config.scale_fn_name
             _maybe_initialize_amaxes_scales_for_float8_cast(
                 input,