diff --git a/onnxscript/function_libs/torch_lib/ops/core.py b/onnxscript/function_libs/torch_lib/ops/core.py
index 67de7076fa..db02faa17e 100644
--- a/onnxscript/function_libs/torch_lib/ops/core.py
+++ b/onnxscript/function_libs/torch_lib/ops/core.py
@@ -4348,6 +4348,11 @@ def aten_gru(
         # Extract hidden_size from hx shape: [num_layers * num_directions, batch, hidden_size]
         hidden_size_attr = hx.shape[2]
 
+        # linear_before_reset=1 matches PyTorch's GRU formulation where the linear
+        # transformation is applied before multiplying by the reset gate:
+        #   ht = g(Xt*(Wh^T) + rt (.) (Ht-1*(Rh^T) + Rbh) + Wbh)
+        # The ONNX default (linear_before_reset=0) uses a different equation and
+        # would produce numerically incorrect results.
         if B is not None:
             Y, Y_h = op.GRU(
                 current_input,
@@ -4357,6 +4362,7 @@ def aten_gru(
                 initial_h=layer_h,
                 direction=direction,
                 hidden_size=hidden_size_attr,
+                linear_before_reset=1,
             )
         else:
             Y, Y_h = op.GRU(
@@ -4366,6 +4372,7 @@ def aten_gru(
                 initial_h=layer_h,
                 direction=direction,
                 hidden_size=hidden_size_attr,
+                linear_before_reset=1,
             )
 
         # Y shape: [seq_length, num_directions, batch_size, hidden_size]