diff --git a/src/turbomind/models/llama/LlamaBatch.cc b/src/turbomind/models/llama/LlamaBatch.cc
index 995f15b710..5d8d7d0411 100644
--- a/src/turbomind/models/llama/LlamaBatch.cc
+++ b/src/turbomind/models/llama/LlamaBatch.cc
@@ -30,6 +30,9 @@ void LlamaBatch<T>::verifyRequests(std::vector<std::shared_ptr<Request>>& stop_r
 
     auto invalidate = [](const char* type, std::shared_ptr<Request>& req, int ec) {
         TM_LOG_WARNING("[verifyRequests] Skipping invalid %s request for id %ld, code = %d", type, (long)req->id, ec);
+        // We don't need a barrier there because
+        // this lambda is called only for new requests
+        // which are visible only for rank = 0 thread.
         req->signal.set_value(ec);
         req.reset();
     };
@@ -139,6 +142,12 @@ void LlamaBatch<T>::handleStopRequests(const std::vector<std::shared_ptr<Request
             check_cuda_error(cudaMemsetAsync(sequence_length.getPtr<int>(), 0, sizeof(int), stream_));
             check_cuda_error(cudaStreamSynchronize(stream_));
         }
+
+        // When the signal is set threads from LlamaV2::forward can exit
+        // and free inputs/outputs tensors.
+        // Therefore we need to make sure that no threads from LlamaV2::internalThreadEntry
+        // are accessing the tensors.
+        llama_->shared_state_->barrier->wait();
         if (rank_ == 0) {
             r->signal.set_value(ec);
         }
@@ -1112,6 +1121,11 @@ void LlamaBatch<T>::finishRequest(int index, bool force_end)
         llama_->kv_cache_mgr_->update(cached_seq_[index], stream_);
     }
 
+    // When the signal is set threads from LlamaV2::forward can exit
+    // and free inputs/outputs tensors.
+    // Therefore we need to make sure that no threads from LlamaV2::internalThreadEntry
+    // are accessing the tensors.
+    llama_->shared_state_->barrier->wait();
     if (rank_ == 0) {
         requests_[index]->signal.set_value(0);
     }