diff --git a/src/pyrecest/evaluation/tracking_metrics/_clear_identity.py b/src/pyrecest/evaluation/tracking_metrics/_clear_identity.py
index 46f898a67..4f56f3147 100644
--- a/src/pyrecest/evaluation/tracking_metrics/_clear_identity.py
+++ b/src/pyrecest/evaluation/tracking_metrics/_clear_identity.py
@@ -11,6 +11,7 @@
 from ._data import TrackingSequence, unit_interval_scalar
 
 _EPS = np.finfo(float).eps
+_UNMATCHED_ID = -1
 
 
 @dataclass(frozen=True)
@@ -39,8 +40,8 @@ def evaluate_clear(data: TrackingSequence, *, threshold: float) -> ClearCounts:
         return ClearCounts(0, data.num_tracker_detections, 0, 0, 0.0)
     tp = fp = fn = switches = 0
     motp_sum = 0.0
-    previous_id = np.full(data.num_gt_ids, np.nan)
-    previous_timestep_id = np.full(data.num_gt_ids, np.nan)
+    previous_id = np.full(data.num_gt_ids, _UNMATCHED_ID, dtype=int)
+    previous_timestep_id = np.full(data.num_gt_ids, _UNMATCHED_ID, dtype=int)
     for gt_ids, tracker_ids, similarity in zip(
         data.gt_ids, data.tracker_ids, data.similarity_scores, strict=True
     ):
@@ -60,9 +61,11 @@ def evaluate_clear(data: TrackingSequence, *, threshold: float) -> ClearCounts:
         matched_gt = gt_ids[match_rows]
         matched_tracker = tracker_ids[match_cols]
         previous = previous_id[matched_gt]
-        switches += int(np.sum((~np.isnan(previous)) & (matched_tracker != previous)))
+        switches += int(
+            np.sum((previous != _UNMATCHED_ID) & (matched_tracker != previous))
+        )
         previous_id[matched_gt] = matched_tracker
-        previous_timestep_id[:] = np.nan
+        previous_timestep_id[:] = _UNMATCHED_ID
         previous_timestep_id[matched_gt] = matched_tracker
         matches = len(match_rows)
         tp += matches
diff --git a/tests/evaluation/test_tracking_metrics.py b/tests/evaluation/test_tracking_metrics.py
index c98d47119..b98735415 100644
--- a/tests/evaluation/test_tracking_metrics.py
+++ b/tests/evaluation/test_tracking_metrics.py
@@ -82,6 +82,21 @@ def test_identity_switch_reduces_association_metrics() -> None:
     assert finalize_identity(identity_counts)["idf1"] == pytest.approx(0.5)
 
 
+def test_clear_preserves_large_tracker_identity_precision() -> None:
+    large_tracker_id = 2**53 + 1
+    data = _sequence(
+        [[0], [0]],
+        [[large_tracker_id], [large_tracker_id - 1]],
+        [[[1.0]], [[1.0]]],
+        num_gt_ids=1,
+        num_tracker_ids=large_tracker_id + 1,
+    )
+
+    counts = evaluate_clear(data, threshold=0.5)
+
+    assert (counts.tp, counts.fp, counts.fn, counts.id_switches) == (2, 0, 0, 1)
+
+
 def test_hota_uses_multiple_localization_thresholds() -> None:
     data = _sequence(
         [[0]],