diff --git a/torchaudio/prototype/rnnt_loss.py b/torchaudio/prototype/rnnt_loss.py
index 2bce60835b..ca48353ff5 100644
--- a/torchaudio/prototype/rnnt_loss.py
+++ b/torchaudio/prototype/rnnt_loss.py
@@ -15,7 +15,6 @@ def rnnt_loss(
     blank: int = -1,
     clamp: float = -1,
     fused_log_softmax: bool = True,
-    reuse_logits_for_grads: bool = True,
 ):
     """
     Compute the RNN Transducer Loss.
@@ -33,13 +32,9 @@ def rnnt_loss(
         clamp (float): clamp for gradients (Default: ``-1``)
         runtime_check (bool): whether to do sanity check during runtime. (Default: ``False``)
         fused_log_softmax (bool): set to False if calling log_softmax outside loss (Default: ``True``)
-        reuse_logits_for_grads (bool): whether to save memory by reusing logits memory for grads (Default: ``True``)
     """
     if not fused_log_softmax:
         logits = torch.nn.functional.log_softmax(logits, dim=-1)
-        reuse_logits_for_grads = (
-            False  # softmax needs the original logits value
-        )
 
     if blank < 0:  # reinterpret blank index if blank < 0.
         blank = logits.shape[-1] + blank
@@ -52,7 +47,7 @@ def rnnt_loss(
         blank=blank,
         clamp=clamp,
         fused_log_smax=fused_log_softmax,
-        reuse_logits_for_grads=reuse_logits_for_grads,)
+        reuse_logits_for_grads=False,)
 
     return costs
 
@@ -69,7 +64,6 @@ class RNNTLoss(torch.nn.Module):
         blank (int, opt): blank label (Default: ``-1``)
         clamp (float): clamp for gradients (Default: ``-1``)
         fused_log_softmax (bool): set to False if calling log_softmax outside loss (Default: ``True``)
-        reuse_logits_for_grads (bool): whether to save memory by reusing logits memory for grads (Default: ``True``)
     """
 
     def __init__(
@@ -77,13 +71,11 @@ def __init__(
         blank: int = -1,
         clamp: float = -1.,
         fused_log_softmax: bool = True,
-        reuse_logits_for_grads: bool = True,
     ):
         super().__init__()
         self.blank = blank
         self.clamp = clamp
         self.fused_log_softmax = fused_log_softmax
-        self.reuse_logits_for_grads = reuse_logits_for_grads
 
     def forward(
         self,
@@ -107,5 +99,4 @@ def forward(
             self.blank,
             self.clamp,
             self.fused_log_softmax,
-            self.reuse_logits_for_grads,
         )