diff --git a/lmdeploy/turbomind/deploy/source_model/llama.py b/lmdeploy/turbomind/deploy/source_model/llama.py
index 08b8f214f..63d60908e 100644
--- a/lmdeploy/turbomind/deploy/source_model/llama.py
+++ b/lmdeploy/turbomind/deploy/source_model/llama.py
@@ -199,6 +199,7 @@ def model_info(self):
                 kv_head_num = model_arg['num_key_value_heads']
             else:
                 kv_head_num = model_arg['num_attention_heads']
+            tie_word_embeddings = model_arg.get('tie_word_embeddings', False)
             rope_theta = float(model_arg.get('rope_theta', 10000.0))
             max_position_embeddings = int(
                 model_arg.get('max_position_embeddings', 0))
@@ -233,6 +234,7 @@ def model_info(self):
             norm_eps=norm_eps,
             attn_head_num=attn_head_num,
             kv_head_num=kv_head_num,
+            tie_word_embeddings=tie_word_embeddings,
             rope_theta=rope_theta,
             max_position_embeddings=max_position_embeddings,
             original_max_position_embeddings=original_max_position_embeddings,
diff --git a/lmdeploy/turbomind/deploy/target_model/base.py b/lmdeploy/turbomind/deploy/target_model/base.py
index 2e54a9fa9..0c70f6464 100644
--- a/lmdeploy/turbomind/deploy/target_model/base.py
+++ b/lmdeploy/turbomind/deploy/target_model/base.py
@@ -79,6 +79,7 @@ class TurbomindModelConfig:
     lora_max_wo_r: int = 0
     lora_rank_pattern: str = ''
     lora_scale_pattern: str = ''
+    tie_word_embeddings: bool = False
 
     @classmethod
     def from_dict(cls, env, allow_none=False):
diff --git a/src/turbomind/models/llama/LlamaWeight.cc b/src/turbomind/models/llama/LlamaWeight.cc
index 78e36aaff..c59eaa684 100644
--- a/src/turbomind/models/llama/LlamaWeight.cc
+++ b/src/turbomind/models/llama/LlamaWeight.cc
@@ -33,6 +33,7 @@ LlamaWeight<T>::LlamaWeight(size_t     head_num,
                             WeightType weight_type,
                             int        group_size,
                             LoraParams lora_params,
+                            bool       tie_word_embeddings,
                             size_t     tensor_para_size,
                             size_t     tensor_para_rank):
     hidden_units_(head_num * size_per_head),
@@ -41,6 +42,7 @@ LlamaWeight<T>::LlamaWeight(size_t     head_num,
     vocab_size_padded_(vocab_size),
     num_layer_(num_layer),
     weight_type_(weight_type),
+    tie_word_embeddings_(tie_word_embeddings),
     tensor_para_size_(tensor_para_size),
     tensor_para_rank_(tensor_para_rank)
 {
@@ -71,7 +73,9 @@ LlamaWeight<T>::~LlamaWeight()
 {
     cudaFree((void*)pre_decoder_embedding_table);
     cudaFree((void*)output_norm_weight);
-    cudaFree((void*)post_decoder_embedding_kernel);
+    if (pre_decoder_embedding_table != post_decoder_embedding_kernel) {
+        cudaFree((void*)post_decoder_embedding_kernel);
+    }
 
     pre_decoder_embedding_table   = nullptr;
     post_decoder_embedding_kernel = nullptr;
@@ -87,7 +91,12 @@ void LlamaWeight<T>::mallocWeights()
     FT_CHECK(vocab_size_padded_ % tensor_para_size_ == 0);
     deviceMalloc((T**)&pre_decoder_embedding_table, vocab_size_padded_ * hidden_units_ / tensor_para_size_);
     deviceMalloc((T**)&output_norm_weight, hidden_units_);
-    deviceMalloc((T**)&post_decoder_embedding_kernel, hidden_units_ * vocab_size_padded_ / tensor_para_size_);
+    if (!tie_word_embeddings_) {
+        deviceMalloc((T**)&post_decoder_embedding_kernel, hidden_units_ * vocab_size_padded_ / tensor_para_size_);
+    }
+    else {
+        post_decoder_embedding_kernel = pre_decoder_embedding_table;
+    }
 }
 
 template<typename T>
diff --git a/src/turbomind/models/llama/LlamaWeight.h b/src/turbomind/models/llama/LlamaWeight.h
index 65eb986d8..dbd6d6685 100644
--- a/src/turbomind/models/llama/LlamaWeight.h
+++ b/src/turbomind/models/llama/LlamaWeight.h
@@ -39,6 +39,7 @@ struct LlamaWeight {
                 WeightType weight_type,
                 int        group_size,
                 LoraParams lora_params,
+                bool       tie_word_embeddings,
                 size_t     tensor_para_size,
                 size_t     tensor_para_rank);
 
@@ -59,6 +60,7 @@ struct LlamaWeight {
 private:
     void mallocWeights();
 
+    bool       tie_word_embeddings_{false};
     size_t     hidden_units_;
     size_t     inter_size_;
     size_t     vocab_size_;
diff --git a/src/turbomind/triton_backend/llama/LlamaTritonModel.cc b/src/turbomind/triton_backend/llama/LlamaTritonModel.cc
index 87fd2cdf5..b5bddb1d4 100644
--- a/src/turbomind/triton_backend/llama/LlamaTritonModel.cc
+++ b/src/turbomind/triton_backend/llama/LlamaTritonModel.cc
@@ -206,6 +206,7 @@ LlamaTritonModel<T>::LlamaTritonModel(size_t      tensor_para_size,
     end_id_              = reader.GetInteger("llama", "end_id");
     use_context_fmha_    = reader.GetInteger("llama", "use_context_fmha", 1);
     cache_block_seq_len_ = reader.GetInteger("llama", "cache_block_seq_len", 0);
+    tie_word_embeddings_ = reader.GetBoolean("llama", "tie_word_embeddings", false);
 
     attn_bias_    = reader.GetInteger("llama", "attn_bias", 0);
     quant_policy_ = reader.GetInteger("llama", "quant_policy", 0);
@@ -416,6 +417,7 @@ void LlamaTritonModel<T>::createSharedWeights(int device_id, int rank)
                                                                       weight_type_,
                                                                       group_size_,
                                                                       lora_params_,
+                                                                      tie_word_embeddings_,
                                                                       tensor_para_size_,
                                                                       tensor_para_rank);
     // model inited with model_dir
diff --git a/src/turbomind/triton_backend/llama/LlamaTritonModel.h b/src/turbomind/triton_backend/llama/LlamaTritonModel.h
index c0a0ebf3a..a1b934184 100644
--- a/src/turbomind/triton_backend/llama/LlamaTritonModel.h
+++ b/src/turbomind/triton_backend/llama/LlamaTritonModel.h
@@ -102,6 +102,7 @@ struct LlamaTritonModel: public AbstractTransformerModel {
     int                             quant_policy_;
     int                             group_size_;
     turbomind::LoraParams           lora_params_;
+    bool                            tie_word_embeddings_;
 
     // shared weights for each device
     std::vector<std::shared_ptr<ft::LlamaWeight<T>>> shared_weights_;