diff --git a/lmdeploy/turbomind/turbomind.py b/lmdeploy/turbomind/turbomind.py
index cffb502c4..f31345db2 100644
--- a/lmdeploy/turbomind/turbomind.py
+++ b/lmdeploy/turbomind/turbomind.py
@@ -565,6 +565,8 @@ def _broadcast_np(data, dtype, shape=(batch_size, )):
             bad_words.append(self.eos_id)
         else:
             stop_words = gen_config.stop_token_ids
+            if self.eos_id not in stop_words:
+                stop_words.append(self.eos_id)
         stop_words = _construct_stop_or_bad_words(stop_words)
         bad_words = _construct_stop_or_bad_words(bad_words)
 
diff --git a/src/turbomind/kernels/sampling_kernels.cu b/src/turbomind/kernels/sampling_kernels.cu
index 427b9a4aa..7263cfcf8 100644
--- a/src/turbomind/kernels/sampling_kernels.cu
+++ b/src/turbomind/kernels/sampling_kernels.cu
@@ -17,8 +17,6 @@ __global__ void sampling(T*             logits,
                          int*           indices,
                          int*           kept,
                          curandState_t* curandstate,
-                         bool*          finished,
-                         const int*     end_ids,
                          int*           output_ids,
                          int*           sequence_length,
                          float*         sampled_logprobs,
@@ -55,10 +53,8 @@ __global__ void sampling(T*             logits,
                 selected             = min(i, n - 1);
                 output_ids[batch_id] = indices[selected];
 
-                if (sequence_length != nullptr && finished != nullptr) {
-                    sequence_length[batch_id] =
-                        finished[batch_id] ? sequence_length[batch_id] : sequence_length[batch_id] + 1;
-                    finished[batch_id] = output_ids[batch_id] == end_ids[batch_id] ? 1 : 0;
+                if (sequence_length != nullptr) {
+                    sequence_length[batch_id] += 1;
                 }
             }
             break;
@@ -94,8 +90,6 @@ void invokeSampling(SamplingParams& params, cudaStream_t stream)
                                                    params.indices,
                                                    params.kept,
                                                    params.curandstate,
-                                                   params.finished,
-                                                   params.end_ids,
                                                    params.output_ids,
                                                    params.sequence_length,
                                                    params.sampled_logprobs,
diff --git a/src/turbomind/kernels/sampling_kernels.h b/src/turbomind/kernels/sampling_kernels.h
index a3cd8fa02..954817e14 100644
--- a/src/turbomind/kernels/sampling_kernels.h
+++ b/src/turbomind/kernels/sampling_kernels.h
@@ -29,8 +29,6 @@ struct SamplingParams {
     int*           kept;
     curandState_t* curandstate;
     size_t         batch_size;
-    bool*          finished;
-    int*           end_ids;
     int*           output_ids;
     int*           sequence_length;
     float*         sampled_logprobs;
diff --git a/src/turbomind/layers/sampling_layers/SamplingLayer.cc b/src/turbomind/layers/sampling_layers/SamplingLayer.cc
index 1d1b18cdc..6040402af 100644
--- a/src/turbomind/layers/sampling_layers/SamplingLayer.cc
+++ b/src/turbomind/layers/sampling_layers/SamplingLayer.cc
@@ -220,9 +220,7 @@ void SamplingLayer<T>::forward(TensorMap* output_tensors, TensorMap* input_tenso
         params.kept        = kept_;
         params.curandstate = output_tensors->at("curand_state").getPtr<curandState_t>();
         params.batch_size  = batch_size;
-        params.finished = output_tensors->at("finished", Tensor{MEMORY_GPU, TYPE_INVALID, {}, nullptr}).getPtr<bool>();
-        params.end_ids  = input_tensors->at("end_id").getPtr<int>();
-        params.output_ids = output_tensors->at("output_ids").getPtrWithOffset<int>(step * batch_size);
+        params.output_ids  = output_tensors->at("output_ids").getPtrWithOffset<int>(step * batch_size);
         params.sequence_length =
             output_tensors->at("sequence_length", Tensor{MEMORY_GPU, TYPE_INVALID, {}, nullptr}).getPtr<int>();
         params.sampled_logprobs =