diff --git a/tools/llm_bench/task/speech_to_text_generation.py b/tools/llm_bench/task/speech_to_text_generation.py
index f1e7ac54a0..15a47a8b6a 100644
--- a/tools/llm_bench/task/speech_to_text_generation.py
+++ b/tools/llm_bench/task/speech_to_text_generation.py
@@ -57,7 +57,7 @@ def run_speech_2_txt_generation(input_param, args, md5_list, iter_data_list):
             - np.array(perf_metrics.raw_metrics.m_new_token_times[:-1])
         ).tolist()
         tm_list = (np.array([first_token_time] + second_tokens_durations) / 1000).tolist()
-        tm_infer_list = None
+        tm_infer_list = (np.array(perf_metrics.raw_metrics.token_infer_durations) / 1000 / 1000).tolist()
         result_text = result_text.texts[0]
     else:
         start = time.perf_counter()
diff --git a/tools/llm_bench/task/text_generation.py b/tools/llm_bench/task/text_generation.py
index 5fbf950d2c..200a8da6f2 100644
--- a/tools/llm_bench/task/text_generation.py
+++ b/tools/llm_bench/task/text_generation.py
@@ -294,6 +294,7 @@ def token_printer():
         np.mean(perf_metrics.raw_metrics.tokenization_durations) / 1000,
         np.mean(perf_metrics.raw_metrics.detokenization_durations) / 1000
     )
+    inference_durations = np.array(perf_metrics.raw_metrics.token_infer_durations) / 1000 / 1000
     iter_data = gen_output_data.gen_iterate_data(
         iter_idx=num,
         in_size=num_input_tokens * args['batch_size'],
@@ -313,7 +314,7 @@ def token_printer():
         num,
         iter_data,
         tm_list.tolist(),
-        None,
+        inference_durations.tolist(),
         warm_up=(num == 0),
         max_rss_mem=max_rss_mem_consumption,
         max_shared_mem=max_shared_mem_consumption,