diff --git a/fairscale/nn/data_parallel/fully_sharded_data_parallel.py b/fairscale/nn/data_parallel/fully_sharded_data_parallel.py
index fb4e2c5c5..13f1e5577 100644
--- a/fairscale/nn/data_parallel/fully_sharded_data_parallel.py
+++ b/fairscale/nn/data_parallel/fully_sharded_data_parallel.py
@@ -375,6 +375,7 @@ def __init__(
         gradient_predivide_factor: Optional[float] = None,
         limit_all_gather_events: bool = False,
         limit_reduce_scatter_events: bool = False,
+        cast_input: bool = True,
         optimize_backward_concat: bool = False,
     ):
         try:
@@ -426,6 +427,7 @@ def __init__(
         self.reshard_after_forward = self._orig_reshard_after_forward = reshard_after_forward
         self.disable_reshard_on_root = disable_reshard_on_root
         self.mixed_precision = mixed_precision
+        self.cast_input = cast_input
         self.fp32_reduce_scatter = fp32_reduce_scatter
         self.flatten_parameters = flatten_parameters
         self.move_params_to_cpu = move_params_to_cpu or cpu_offload
@@ -1450,7 +1452,7 @@ def forward(self, *args: Any, **kwargs: Any) -> torch.Tensor:
         # For root and mixed precision, we convert the input to FP16 (no_grad is needed for
         # the conversion).
         is_bf16 = self.compute_dtype == torch.bfloat16
-        if self._is_root and self.mixed_precision:
+        if self._is_root and self.mixed_precision and self.cast_input:
             args, kwargs = cast_floats_to_right_precision(True, True, is_bf16, *args, **kwargs)
 
         if self not in self._fsdp_forward_ordering: