diff --git a/volc_limit_sync.py b/volc_limit_sync.py
index c485672..125068a 100644
--- a/volc_limit_sync.py
+++ b/volc_limit_sync.py
@@ -95,7 +95,6 @@ REGION = "cn-beijing"
 # Daemon Config
 BUFFER = 300000  # User requested 30w buffer
 CHECK_INTERVAL = 10
-THRESHOLD = 300000
 
 # 前置闸门预留量：请求开始判定 usage + reserve >= limit 即 429。
 # reserve 优先取本次请求自带 max_tokens（真实上限，零采集损失），
@@ -572,6 +571,14 @@ def restore_blocked_models():
             clean_model = clean_model_name(upstream_model)
             original_api_base = backup.get("api_base")
 
+            # 只恢复监控内的火山条目（clean + 端点 hash），与 soft_evict/请求闸门口径一致，
+            # 避免按 clean 名误恢复同名不同端点（如 newapi 渠道）被踢的条目
+            if MONITORED_MODEL_PAIRS and (
+                clean_model,
+                generate_api_base_hash(params.get("api_base", "")),
+            ) not in MONITORED_MODEL_PAIRS:
+                continue
+
             # Check Quota
             # Need current usage to calculate dynamic limit correctly?
             # get_effective_limit handles fetching usage if None passed.
@@ -697,6 +704,14 @@ def startup_audit():
             if not clean_model:
                 continue
 
+            # 只审计监控内的火山模型（clean + 端点 hash），与请求闸门口径一致，
+            # 避免误判同名非监控渠道（如 newapi 别名模型）超限而误踢
+            if MONITORED_MODEL_PAIRS and (
+                clean_model,
+                generate_api_base_hash(api_base),
+            ) not in MONITORED_MODEL_PAIRS:
+                continue
+
             # 2. Check Limit & Usage
             # We use effective limit logic which checks both static and dynamic
             effective_limit = get_effective_limit(clean_model, api_base)
@@ -1233,6 +1248,28 @@ def _maybe_trigger_daily_consume():
         log(f"❌ 消耗任务调度失败: {e}", level="ERROR")
 
 
+def compute_sync_interval(min_remaining, is_idle):
+    """按最小正剩余余额 + 空闲状态计算同步间隔（秒）。"""
+    # 余额分档退化：余额驱动的"慢速档"已无意义（日返还模型下余额高 = 常态，
+    # 返还/过期/消耗随时发生，慢同步只制造检测延迟窗口）。
+    # 仅保留"低余额加密"：<10万 5min、<30万 10min（返还解锁/扣费检测要紧）；
+    # ≥30万 统一 30min，不再细分。真正的慢同步 = is_idle（base×4，上限 60min）。
+    if min_remaining < 100_000:
+        base_interval = 300  # 紧急 5 minutes
+    elif min_remaining < 300_000:
+        base_interval = 600  # 低余额 10 minutes
+    else:
+        base_interval = 1800  # 常规 30 minutes
+
+    if is_idle:
+        interval = min(base_interval * 4, 3600)
+        if interval < 300:
+            interval = 300
+    else:
+        interval = base_interval
+    return interval
+
+
 def active_monitor_loop():
     # Config Discovery
     MONITORED_MODELS = discover_monitored_models()
@@ -1267,7 +1304,7 @@ def active_monitor_loop():
         "Starting Active Monitor Loop (Safety-Margin + Idle Awareness) / 正在启动主动监控循环 (安全余量 + 空闲感知)...",
         flush=True,
     )
-    print(f"Buffer / 缓冲: {BUFFER}, Threshold / 阈值: {THRESHOLD}", flush=True)
+    print(f"Buffer / 缓冲: {BUFFER}", flush=True)
 
     while True:
         try:
@@ -1318,41 +1355,10 @@ def active_monitor_loop():
                 (now - idle_start_time) > IDLE_THRESHOLD
             )
 
-            # Dynamic Interval
-            # Logic: Adjust intervals based on distance from BUFFER
-            # User specified thresholds (Distance < X):
-            # < 10w -> 2min (120s)
-            # < 30w -> 5min (300s)
-            # < 50w -> 10min (600s)
-            # < 80w -> 30min (1800s)
-            # < 100w -> 60min (3600s)
-            # >= 100w -> 60min (3600s)
-
-            # Determine Base Sync Interval based on global risk (Optimized for Hourly Latency)
-            # Since API updates are hourly, frequent polling provides no new info and wastes resources.
-            # We trust Redis Usage for real-time gating.
-            # < 100k -> 5 min (Emergency check for the update moment)
-            # < 300k -> 10 min
-            # < 500k -> 20 min
-            # < 800k -> 45 min
-            # >= 800k -> 60 min
-            # 余额分档退化：余额驱动的"慢速档"已无意义（日返还模型下余额高 = 常态，
-            # 返还/过期/消耗随时发生，慢同步只制造检测延迟窗口）。
-            # 仅保留"低余额加密"：<10万 5min、<30万 10min（返还解锁/扣费检测要紧）；
-            # ≥30万 统一 30min，不再细分。真正的慢同步 = is_idle（下方 base×4，上限 60min）。
-            if global_min_remaining < 100_000:
-                base_interval = 300  # 紧急 5 minutes
-            elif global_min_remaining < 300_000:
-                base_interval = 600  # 低余额 10 minutes
-            else:
-                base_interval = 1800  # 常规 30 minutes
-
-            if is_idle:
-                current_sync_interval = min(base_interval * 4, 3600)
-                if current_sync_interval < 300:
-                    current_sync_interval = 300
-            else:
-                current_sync_interval = base_interval
+            # Dynamic Interval: 按最小正剩余余额分档（见 compute_sync_interval）
+            current_sync_interval = compute_sync_interval(
+                global_min_remaining, is_idle
+            )
 
             # =====================================================
             # 🚀 Per-Model Burst Detection (精细化突发流量检测)
@@ -1566,8 +1572,10 @@ def active_monitor_loop():
                     mode_icon = "🚨 低余额模式"
                 else:
                     mode_icon = "ℹ️ 常规模式"
+                # 用本次同步后的新 Min Rem 重算，避免"旧 interval + 新 Min Rem"混打误导
+                next_interval = compute_sync_interval(global_min_remaining, is_idle)
                 print(
-                    f"{mode_icon}: 下一次同步 {current_sync_interval}s (Min Rem: {int(global_min_remaining):,}, {'空闲' if is_idle else '活跃'}) / 同步间隔 {current_sync_interval}s",
+                    f"{mode_icon}: 下一次同步 {next_interval}s (Min Rem: {int(global_min_remaining):,}, {'空闲' if is_idle else '活跃'}) / 同步间隔 {next_interval}s",
                     flush=True,
                 )