feat: pack recent submissions into reserved account slots first

Preserve shared queue positions for old-model candidates with constrained
admission. Retain headroom balancing for ties and weekly calibration pinning.
Add offline mixed-age allocation regressions.

README.md

@@ -311,6 +311,16 @@ tries the next account. It does not lower the persisted capacity using a cached
 active count: another worker may have filled the queue since that count was
 read. Downward capacity learning remains confined to weekly calibration.
 
+Account allocation is age-aware: recent models first use accounts with only
+reserved positions left, then the account with the fewest shared positions
+remaining. Old models continue to use the account with the most eligible space.
+Largest-headroom and rotating tie-breaks balance otherwise equivalent accounts;
+weekly calibration remains pinned to its target account. For example, with
+accounts at 94/100 and 95/100 and five recent-only positions each, assigning a
+recent model to the second account preserves the first account's last old-model
+position. A recent-then-old pair can both be accepted rather than stranding the
+old model after the recent model takes its only eligible position.
+
 Model verification results are reused for 15 minutes across poll cycles, and a
 locally failed model/GPU pair cools down for 24 hours instead of being excluded
 forever. The `[scan]` lines show every expansion stage, while `[daily] wave_done`

modelhub_submmit_api/modelhub_client.py

@@ -948,6 +948,26 @@ class ModelHubClientPool:
             usable = {index: remaining for index, remaining in remaining_by_index.items() if remaining > 0}
             if not usable:
                 return None
+            if (
+                reserve_capacity_slots is None
+                and weekly_target is None
+                and self.recent_model_reserve_slots > 0
+            ):
+                # Recent models can use every position; old models cannot.
+                # Pack recent work into reserved positions first, then the
+                # account nearest its old-model threshold. This preserves
+                # shared positions for later old candidates, regardless of
+                # candidate arrival order. Keep largest-headroom/round-robin
+                # balancing among accounts with the same shared capacity.
+                shared_slots = {
+                    index: max(0, remaining - self.recent_model_reserve_slots)
+                    for index, remaining in usable.items()
+                }
+                least_shared = min(shared_slots.values())
+                usable = {
+                    index: remaining for index, remaining in usable.items()
+                    if shared_slots[index] == least_shared
+                }
             best_remaining = max(usable.values())
             tied = [index for index, remaining in usable.items() if remaining == best_remaining]
             selected_index = min(

tests/test_concurrency.py

@@ -217,6 +217,43 @@ def make_candidate(index: int) -> dict:
 
 
 class ClientPoolConcurrencyTests(unittest.TestCase):
+    def test_recent_work_preserves_shared_slots_for_later_old_models(self) -> None:
+        for initial_counts, ages, expected_counts in (
+            ([94, 95], ["recent", "old"], [95, 96]),
+            ([93, 94], ["recent", "recent", "old", "old"], [95, 96]),
+        ):
+            with self.subTest(initial_counts=initial_counts):
+                clients = [FakeClient(active_count=count) for count in initial_counts]
+                pool = ModelHubClientPool(
+                    clients,  # type: ignore[arg-type]
+                    active_task_cap=100,
+                    recent_model_reserve_slots=5,
+                    active_counts_ttl=60,
+                    capacity_probe_interval_cycles=0,
+                )
+                for index, age in enumerate(ages):
+                    pool.add_task_for_model(
+                        {"model": f"model-{index}"},
+                        model_last_modified=(
+                            "2026-10-01T00:00:00Z" if age == "recent"
+                            else "2025-01-01T00:00:00Z"
+                        ),
+                        submitted_at="2026-10-02T00:00:00Z",
+                    )
+                self.assertEqual(expected_counts, pool.active_task_counts())
+                self.assertEqual(len(ages), sum(len(client.submitted) for client in clients))
+                self.assertEqual(0, pool.old_model_submit_slots())
+
+    def test_recent_packing_keeps_largest_headroom_without_reserved_slots(self) -> None:
+        clients = [FakeClient(active_count=2), FakeClient(active_count=3)]
+        pool = ModelHubClientPool(
+            clients,  # type: ignore[arg-type]
+            active_task_cap=5,
+            recent_model_reserve_slots=0,
+        )
+        pool.add_task({"model": "recent"})
+        self.assertEqual([1, 0], [len(client.submitted) for client in clients])
+
     def test_stale_capacity_rejection_does_not_poison_learned_limit(self) -> None:
         with tempfile.TemporaryDirectory() as temporary_dir:
             state_path = Path(temporary_dir) / "capacity.json"