diff --git a/.automation_scripts/pytorch-unit-test-scripts/generate_summary.py b/.automation_scripts/pytorch-unit-test-scripts/generate_summary.py
index 5c78317197b43..2ae893cf82333 100644
--- a/.automation_scripts/pytorch-unit-test-scripts/generate_summary.py
+++ b/.automation_scripts/pytorch-unit-test-scripts/generate_summary.py
@@ -114,10 +114,10 @@ def test_config_stats_keys(s1_name, s2_name, has_set2=True):
             f'TOTAL {s1}',
         ]
     return [
-        f'SKIPPED (on {s1_name}, but not on {s2_name})',
+        f'SKIPPED (on {s1_name}, PASSED on {s2_name})',
         f'SKIPPED (on {s1_name})',
         f'SKIPPED (on {s2_name})',
-        f'MISSED (MISSED on {s1_name}, NOT SKIPPED on {s2_name})',
+        f'MISSED (on {s1_name}, PASSED on {s2_name})',
         f'{s1}ONLY (PASSED on {s1}, NOT PASSED on {s2})',
         s2,
         s1,
@@ -141,15 +141,18 @@ def compute_test_config_stats(rows, s1_col, s2_col, s1_name, s2_name, has_set2=T
         vals[keys[4]] = sum(1 for r in rows if r[s1_col].strip())
         return vals
 
+    # Count a ROCm SKIPPED/MISSED test as a disagreement only when CUDA actually
+    # PASSED it. This excludes parametrization variants CUDA never runs (CUDA
+    # MISSED) or also skips, which aren't real ROCm-vs-CUDA coverage gaps.
     s1_skip_not_s2 = sum(
         1 for r in rows
-        if r[s1_col] == 'SKIPPED' and r[s2_col] != 'SKIPPED'
+        if r[s1_col] == 'SKIPPED' and r[s2_col] == 'PASSED'
     )
     s1_skip = sum(1 for r in rows if r[s1_col] == 'SKIPPED')
     s2_skip = sum(1 for r in rows if r[s2_col] == 'SKIPPED')
     s1_miss_not_s2_skip = sum(
         1 for r in rows
-        if r[s1_col] == 'MISSED' and r[s2_col] != 'SKIPPED'
+        if r[s1_col] == 'MISSED' and r[s2_col] == 'PASSED'
     )
     only_s1 = sum(
         1 for r in rows
@@ -233,11 +236,11 @@ def safe_float(v):
         wf_rows = [r for r in rows if r['test_config'] == wf]
         s1_skip_not_s2 = sum(
             1 for r in wf_rows
-            if r[s1_col] == 'SKIPPED' and r[s2_col] != 'SKIPPED'
+            if r[s1_col] == 'SKIPPED' and r[s2_col] == 'PASSED'
         )
         s1_miss_not_s2_skip = sum(
             1 for r in wf_rows
-            if r[s1_col] == 'MISSED' and r[s2_col] != 'SKIPPED'
+            if r[s1_col] == 'MISSED' and r[s2_col] == 'PASSED'
         )
         total_disagree += s1_skip_not_s2 + s1_miss_not_s2_skip
         total_s2 += sum(1 for r in wf_rows if r[s2_col].strip() and r[s2_col].strip() != 'MISSED')