diff --git a/python/tvm/relay/frontend/pytorch.py b/python/tvm/relay/frontend/pytorch.py
index a0a837f92df9..76cd0455661b 100644
--- a/python/tvm/relay/frontend/pytorch.py
+++ b/python/tvm/relay/frontend/pytorch.py
@@ -1469,7 +1469,7 @@ def linear(self, inputs, input_types):
         if isinstance(bias, _expr.Expr):
             bias_ndims = len(self.infer_shape_with_prelude(bias))
             if bias_ndims == 1:
-                return _op.nn.bias_add(mm_out, bias)
+                return _op.nn.bias_add(mm_out, bias, axis=-1)
             mm_dtype = self.infer_type_with_prelude(mm_out).dtype
             return self.add([mm_out, bias], [mm_dtype, input_types[2]])
         return mm_out
diff --git a/tests/python/frontend/pytorch/test_forward.py b/tests/python/frontend/pytorch/test_forward.py
index 6f5eb1825dfc..3a3889d5cfb7 100644
--- a/tests/python/frontend/pytorch/test_forward.py
+++ b/tests/python/frontend/pytorch/test_forward.py
@@ -1602,6 +1602,8 @@ def forward(self, x, y, z):
     verify_model(LinearNoBias(), input_data=[input2d, weight1d])
     # 3D input, 2D weight, no bias
     verify_model(LinearNoBias(), input_data=[input3d, weight3x2])
+    # 3D input, 2D weight, 1D bias
+    verify_model(Linear(), input_data=[input3d, weight2d, bias1d])
 
     verify_model(LinearNested(), input_data=[torch.randn(10, 10) for _ in range(3)])