diff --git a/llm_bench/python/llm_bench_utils/metrics_print.py b/llm_bench/python/llm_bench_utils/metrics_print.py
index c172060d8b..f1e8b3ddc3 100644
--- a/llm_bench/python/llm_bench_utils/metrics_print.py
+++ b/llm_bench/python/llm_bench_utils/metrics_print.py
@@ -153,8 +153,8 @@ def output_avg_statis_tokens(prompt_dict, prompt_idx_list, iter_data_list, batch
             avg_2nd_tokens_latency = 'NA' if avg_2nd_tokens_latency < 0 else f'{avg_2nd_tokens_latency:.2f} ms/{latency_unit}'
             avg_2nd_token_tput = 'NA' if avg_2nd_tokens_latency == 'NA' else f'{avg_2nd_token_tput:.2f} {latency_unit}s/s'
             if is_text_gen is True:
-                prompt_dict[p_idx] = '\n[ INFO ] [Average] Prompt[{}] Input token size: {}, 1st token lantency: {}, ' \
-                    '2nd token lantency: {}, 2nd tokens throughput: {}' \
+                prompt_dict[p_idx] = '\n[ INFO ] [Average] Prompt[{}] Input token size: {}, 1st token latency: {}, ' \
+                    '2nd token latency: {}, 2nd tokens throughput: {}' \
                     .format(p_idx, avg_input_size, avg_1st_token_latency, avg_2nd_tokens_latency, avg_2nd_token_tput)
             else:
                 prompt_dict[p_idx] = '\n[ INFO ] [Average] Prompt[{}] 1st step of unet latency: {}, ' \
diff --git a/llm_bench/python/llm_bench_utils/output_csv.py b/llm_bench/python/llm_bench_utils/output_csv.py
index e01628f098..82bfb6bb7f 100644
--- a/llm_bench/python/llm_bench_utils/output_csv.py
+++ b/llm_bench/python/llm_bench_utils/output_csv.py
@@ -26,15 +26,15 @@ def output_comments(result, use_case, writer):
         comment_list.append('prompt_idx: Index of prompts')
     elif use_case == 'image_gen':
         comment_list.append("infer_count: Tex2Image models' Inference(or Sampling) step size")
-        comment_list.append('1st_latency: First step lantency of unet')
+        comment_list.append('1st_latency: First step latency of unet')
         comment_list.append('2nd_avg_latency: Other steps latency of unet(exclude first step)')
         comment_list.append('1st_infer_latency: Same as 1st_latency')
         comment_list.append('2nd_infer_avg_latency: Same as 2nd_avg_latency')
         comment_list.append('prompt_idx: Index of prompts')
     elif use_case == 'ldm_super_resolution':
         comment_list.append("infer_count: Tex2Image models' Inference(or Sampling) step size")
-        comment_list.append('1st_latency: First step lantency of unet')
-        comment_list.append('2nd_avg_latency: Other steps lantency of unet(exclude first step)')
+        comment_list.append('1st_latency: First step latency of unet')
+        comment_list.append('2nd_avg_latency: Other steps latency of unet(exclude first step)')
         comment_list.append('1st_infer_latency: Same as 1st_latency')
         comment_list.append('2nd_infer_avg_latency: Same as 2nd_avg_latency')
         comment_list.append('prompt_idx: Image Index')