diff --git a/evalharness/cli.py b/evalharness/cli.py
index 72222d9..7d0ffa9 100644
--- a/evalharness/cli.py
+++ b/evalharness/cli.py
@@ -926,15 +926,13 @@ def _cmd_eval_run(args) -> int:
                     print(render(report, style=args.style))
             all_reports.append(report)
             primary = next(iter(report.metrics), '')
-            secs_total = sum(float((s.usage or {}).get('latency_s', 0) or 0)
-                             for s in report.samples)
             groups = {k: v for k, v in report.metric_groups.items()
                       if isinstance(v, dict) and k not in ('run_info',)
                       and not k.startswith('agg_error')}
             info = report.metric_groups.get('run_info', {}) or {}
-            if _repeats > 1 and _rep_secs:
-                # repeats: report the SUM over all runs, not the last one
-                secs_total = _rep_secs
+            if _repeats > 1:
+                # repeats: tokens are the SUM over all runs (real cost of the
+                # predictions used)
                 info = {**info, 'gen_input_tokens': _rep_tin,
                         'gen_output_tokens': _rep_tout,
                         'gen_total_tokens': _rep_tin + _rep_tout}
@@ -945,12 +943,19 @@ def _cmd_eval_run(args) -> int:
                 return lats[min(int(len(lats) * q), len(lats) - 1)] if lats else 0.0
             fins = [(s.usage or {}).get('finish_reason', '')
                     for s in report.samples]
+            # time = THIS run's wall clock everywhere: summing per-prediction
+            # latency_s counts RESTORED predictions' original generation time
+            # (days old, slower setup) -- that once reported 15.9h for a
+            # one-hour run
+            _wall = round(_time.time() - t0, 1)
             rows.append({'name': name, 'metric': primary, 'value': report.metrics.get(primary),
-                         'n': report.num_samples,
+                         # repeats evaluate the SAME N problems k times: the
+                         # count people expect is the generations, not N
+                         'n': report.num_samples * _repeats,
                          'extract_fail': report.num_failed_extractions,
-                         'secs': round(secs_total, 1),
-                         'wall': round(_time.time() - t0, 1),
-                         'hours': round(secs_total / 3600, 2),
+                         'secs': _wall,
+                         'wall': _wall,
+                         'hours': round(_wall / 3600, 2),
                          'tok_in': info.get('gen_input_tokens', 0) or 0,
                          'tok_out': info.get('gen_output_tokens', 0) or 0,
                          'tokens': (info.get('gen_input_tokens', 0) or 0)