diff --git a/python/llm/test/benchmark/csv_to_html.py b/python/llm/test/benchmark/csv_to_html.py
index 75b48884..cfbb2dc5 100644
--- a/python/llm/test/benchmark/csv_to_html.py
+++ b/python/llm/test/benchmark/csv_to_html.py
@@ -21,12 +21,12 @@ import sys
 import argparse
 import pandas as pd
 
-def highlight_vals(val, max=3.0):
+def highlight_vals(val, max=3.0, color1='red', color2='green'):
     if isinstance(val, float):
         if val > max:
-            return 'background-color: %s' % 'green'
+            return 'background-color: %s' % color2
         elif val <= -max:
-            return 'background-color: %s' % 'red'
+            return 'background-color: %s' % color1
     else:
         return ''
 
@@ -153,14 +153,18 @@ def main():
 
         diffs_within_normal_range = is_diffs_within_normal_range(diff1, diff2, threshold=highlight_threshold)
 
-        subset=['diff1(%)','diff2(%)','best diff1(%)','best diff2(%)']
+        subset1=['diff1(%)','diff2(%)']
+        subset2=['best diff1(%)','best diff2(%)']
         columns={'1st token avg latency (ms)': '{:.2f}', '2+ avg latency (ms/token)': '{:.2f}', 'last1': '{:.2f}', 'diff1(%)': '{:.2f}',
                 'last2': '{:.2f}', 'diff2(%)': '{:.2f}', 'encoder time (ms)': '{:.2f}', 'peak mem (GB)': '{:.2f}',
                 'best 1': '{:.2f}', 'best diff1(%)': '{:.2f}', 'best 2': '{:.2f}', 'best diff2(%)': '{:.2f}'}
 
+        styled_df = latest_csv.style.format(columns).applymap(lambda val: highlight_vals(val, max=3.0, color1='red', color2='green'), subset=subset1)
+        styled_df = styled_df.applymap(lambda val: highlight_vals(val, max=3.0, color1='yellow'), subset=subset2)
+        html_output = styled_df.set_table_attributes("border=1").render()
+
         with open(daily_html, 'w') as f:
-            f.write(latest_csv.style.format(columns).applymap(lambda val: highlight_vals(val, max=highlight_threshold), subset)
-                            .set_table_attributes("border=1").render())
+            f.write(html_output)
     else:
         latest_csv.to_html(daily_html)