diff --git a/tensorrt_llm/models/commandr/config.py b/tensorrt_llm/models/commandr/config.py
index a2edca61fb78..7685d6188a32 100644
--- a/tensorrt_llm/models/commandr/config.py
+++ b/tensorrt_llm/models/commandr/config.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2022-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
@@ -60,7 +60,8 @@ def from_hugging_face(
 
         dtype = infer_dtype(dtype, getattr(hf_config, 'torch_dtype', None))
 
-        if hf_config.tie_word_embeddings:
+        tie_word_embeddings = getattr(hf_config, 'tie_word_embeddings', False)
+        if tie_word_embeddings:
             kwargs['use_parallel_embedding'] = True
             kwargs['embedding_sharding_dim'] = 0
 
@@ -82,6 +83,7 @@ def from_hugging_face(
             rotary_base=hf_config.rope_theta,
             attn_bias=hf_config.attention_bias,
             qk_layernorm=hf_config.use_qk_norm,
+            tie_word_embeddings=tie_word_embeddings,
             mapping=mapping,
             quantization=quant_config,
             **kwargs)
diff --git a/tensorrt_llm/models/model_weights_loader.py b/tensorrt_llm/models/model_weights_loader.py
index a130883e95c7..bd8ca87bf8a3 100644
--- a/tensorrt_llm/models/model_weights_loader.py
+++ b/tensorrt_llm/models/model_weights_loader.py
@@ -335,7 +335,8 @@ def update_key_mapping(self, model):
             if self.tllm_to_externel_key_dict['layers'] != 'layers':
                 del self.tllm_to_externel_key_dict['layers']
 
-        # Share embedding; only applies to standard structure with lm_head and transformer.vocab_embedding
+        # Share embedding when config.tie_word_embeddings is set; only applies
+        # to the standard lm_head + transformer.vocab_embedding structure.
         if hasattr(self.model, 'lm_head') and hasattr(
                 self.model, 'transformer') and hasattr(self.model.transformer,
                                                        'vocab_embedding'):
@@ -344,12 +345,16 @@ def update_key_mapping(self, model):
             vocab_embed_weights = self.load_tensor(
                 self.translate_to_external_key(
                     'transformer.vocab_embedding.weight'))
-            if lm_head_weights is None and vocab_embed_weights is not None:
+            tie_word_embeddings = getattr(model.config, 'tie_word_embeddings',
+                                          False)
+            if (tie_word_embeddings and lm_head_weights is None
+                    and vocab_embed_weights is not None):
                 self.tllm_to_externel_key_dict[
                     'lm_head'] = self.tllm_to_externel_key_dict[
                         'transformer'] + '.' + self.tllm_to_externel_key_dict[
                             'vocab_embedding']
-            elif lm_head_weights is not None and vocab_embed_weights is None:
+            elif (tie_word_embeddings and lm_head_weights is not None
+                  and vocab_embed_weights is None):
                 self.tllm_to_externel_key_dict[
                     'vocab_embedding'] = self.tllm_to_externel_key_dict[
                         'lm_head']