diff --git a/debug/accuracy_tools/api_accuracy_checker/compare/algorithm.py b/debug/accuracy_tools/api_accuracy_checker/compare/algorithm.py
index 0bb30cc72d7d7f0a2387385084ec0722dc1cbffe..17243a7415881198c1841afa119cc242292bfdc1 100644
--- a/debug/accuracy_tools/api_accuracy_checker/compare/algorithm.py
+++ b/debug/accuracy_tools/api_accuracy_checker/compare/algorithm.py
@@ -54,20 +54,19 @@ def cosine_sim(cpu_output, npu_output):
         return get_max_rel_err(n_value, b_value)
     if n_value.dtype == np.uint8:
         return compare_uint8_data(n_value, b_value)
-    n_value = n_value / (np.max(np.abs(n_value)) + np.finfo(n_value.dtype).eps)
-    b_value = b_value / (np.max(np.abs(b_value)) + np.finfo(b_value.dtype).eps)
-    num = n_value.dot(b_value)
-    a_norm = np.linalg.norm(n_value)
-    b_norm = np.linalg.norm(b_value)
-    if a_norm <= np.finfo(float).eps and b_norm <= np.finfo(float).eps:
+    n_max = np.max(np.abs(n_value))
+    b_max = np.max(np.abs(b_value))
+    if n_max <= np.finfo(float).eps and b_max <= np.finfo(float).eps:
         return cos, True
-    elif a_norm <= np.finfo(float).eps:
+    elif n_max <= np.finfo(float).eps:
         print_warn_log("All the data is Zero in npu dump data. Compare by relative error.")
         return get_max_rel_err(n_value, b_value)
-    elif b_norm <= np.finfo(float).eps:
+    elif b_max <= np.finfo(float).eps:
         print_warn_log("All the data is Zero in bench dump data. Compare by relative error.")
     else:
-        cos = num / (a_norm * b_norm)
+        n_value = n_value.astype(float) / n_max
+        b_value = b_value.astype(float) / b_max
+        cos = np.dot(n_value, b_value) / (np.linalg.norm(n_value) * np.linalg.norm(b_value))
         if np.isnan(cos):
             print_warn_log("Dump data has NaN when comparing with Cosine Similarity.")
         return cos, cos > 0.99