diff --git a/optimum/onnxruntime/base.py b/optimum/onnxruntime/base.py
index f9091650b20..bbf7421a86a 100644
--- a/optimum/onnxruntime/base.py
+++ b/optimum/onnxruntime/base.py
@@ -326,6 +326,7 @@ def forward(
         self,
         input_ids: torch.LongTensor,
         attention_mask: Optional[torch.LongTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
         past_key_values: Optional[Tuple[Tuple[torch.FloatTensor]]] = None,
         labels: Optional[torch.LongTensor] = None,
         use_cache_branch: None = None,
@@ -365,6 +366,9 @@ def forward(
             if "attention_mask" in self.input_names:
                 model_inputs.append(attention_mask)
 
+            if "position_ids" in self.input_names:
+                model_inputs.append(position_ids)
+
             if past_key_values is not None:
                 model_inputs += past_key_values
 
@@ -413,6 +417,9 @@ def forward(
                     "attention_mask": attention_mask.cpu().detach().numpy(),
                 }
 
+                if "position_ids" in self.input_names:
+                    onnx_inputs["position_ids"] = position_ids.cpu().detach().numpy()
+
                 if self.parent_model.use_merged is True:
                     onnx_inputs["use_cache_branch"] = use_cache_branch_tensor.cpu().detach().numpy()
 
@@ -429,6 +436,9 @@ def forward(
                     "attention_mask": attention_mask,
                 }
 
+                if "position_ids" in self.input_names:
+                    onnx_inputs["position_ids"] = position_ids
+
                 if self.parent_model.use_merged is True:
                     onnx_inputs["use_cache_branch"] = use_cache_branch_tensor
 
diff --git a/optimum/onnxruntime/modeling_decoder.py b/optimum/onnxruntime/modeling_decoder.py
index 1ffc81d8832..91f65153b40 100644
--- a/optimum/onnxruntime/modeling_decoder.py
+++ b/optimum/onnxruntime/modeling_decoder.py
@@ -642,6 +642,7 @@ def forward(
         self,
         input_ids: torch.LongTensor = None,
         attention_mask: Optional[torch.FloatTensor] = None,
+        position_ids: Optional[torch.LongTensor] = None,
         past_key_values: Optional[Tuple[Tuple[torch.Tensor]]] = None,
         labels: Optional[torch.LongTensor] = None,
         **kwargs,
@@ -650,6 +651,7 @@ def forward(
             outputs = self.decoder(
                 input_ids=input_ids,
                 attention_mask=attention_mask,
+                position_ids=position_ids,
                 past_key_values=past_key_values,
                 labels=labels,
             )
@@ -658,6 +660,7 @@ def forward(
                 input_ids=input_ids[:, -1:],
                 past_key_values=past_key_values,
                 attention_mask=attention_mask,
+                position_ids=position_ids,
             )
         else:
             outputs = self.decoder_with_past(
@@ -665,6 +668,7 @@ def forward(
                 past_key_values=past_key_values,
                 attention_mask=attention_mask,
                 labels=labels,
+                position_ids=position_ids,
             )
 
         return CausalLMOutputWithCrossAttentions(