diff --git a/src/webui/routes.py b/src/webui/routes.py
index 64d033e8..517b77ed 100644
--- a/src/webui/routes.py
+++ b/src/webui/routes.py
@@ -5,6 +5,7 @@ from typing import Optional
 from src.common.logger import get_logger
 from .token_manager import get_token_manager
 from .config_routes import router as config_router
+from .statistics_routes import router as statistics_router
 
 logger = get_logger("webui.api")
 
@@ -13,6 +14,8 @@ router = APIRouter(prefix="/api/webui", tags=["WebUI"])
 
 # 注册配置管理路由
 router.include_router(config_router)
+# 注册统计数据路由
+router.include_router(statistics_router)
 
 
 class TokenVerifyRequest(BaseModel):
diff --git a/src/webui/statistics_routes.py b/src/webui/statistics_routes.py
new file mode 100644
index 00000000..01d5ea28
--- /dev/null
+++ b/src/webui/statistics_routes.py
@@ -0,0 +1,329 @@
+"""统计数据 API 路由"""
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel, Field
+from typing import Dict, Any, List
+from datetime import datetime, timedelta
+from collections import defaultdict
+
+from src.common.logger import get_logger
+from src.common.database.database_model import LLMUsage, OnlineTime, Messages
+
+logger = get_logger("webui.statistics")
+
+router = APIRouter(prefix="/statistics", tags=["statistics"])
+
+
+class StatisticsSummary(BaseModel):
+    """统计数据摘要"""
+    total_requests: int = Field(0, description="总请求数")
+    total_cost: float = Field(0.0, description="总花费")
+    total_tokens: int = Field(0, description="总token数")
+    online_time: float = Field(0.0, description="在线时间（秒）")
+    total_messages: int = Field(0, description="总消息数")
+    total_replies: int = Field(0, description="总回复数")
+    avg_response_time: float = Field(0.0, description="平均响应时间")
+    cost_per_hour: float = Field(0.0, description="每小时花费")
+    tokens_per_hour: float = Field(0.0, description="每小时token数")
+
+
+class ModelStatistics(BaseModel):
+    """模型统计"""
+    model_name: str
+    request_count: int
+    total_cost: float
+    total_tokens: int
+    avg_response_time: float
+
+
+class TimeSeriesData(BaseModel):
+    """时间序列数据"""
+    timestamp: str
+    requests: int = 0
+    cost: float = 0.0
+    tokens: int = 0
+
+
+class DashboardData(BaseModel):
+    """仪表盘数据"""
+    summary: StatisticsSummary
+    model_stats: List[ModelStatistics]
+    hourly_data: List[TimeSeriesData]
+    daily_data: List[TimeSeriesData]
+    recent_activity: List[Dict[str, Any]]
+
+
+@router.get("/dashboard", response_model=DashboardData)
+async def get_dashboard_data(hours: int = 24):
+    """
+    获取仪表盘统计数据
+    
+    Args:
+        hours: 统计时间范围（小时），默认24小时
+        
+    Returns:
+        仪表盘数据
+    """
+    try:
+        now = datetime.now()
+        start_time = now - timedelta(hours=hours)
+        
+        # 获取摘要数据
+        summary = await _get_summary_statistics(start_time, now)
+        
+        # 获取模型统计
+        model_stats = await _get_model_statistics(start_time)
+        
+        # 获取小时级时间序列数据
+        hourly_data = await _get_hourly_statistics(start_time, now)
+        
+        # 获取日级时间序列数据（最近7天）
+        daily_start = now - timedelta(days=7)
+        daily_data = await _get_daily_statistics(daily_start, now)
+        
+        # 获取最近活动
+        recent_activity = await _get_recent_activity(limit=10)
+        
+        return DashboardData(
+            summary=summary,
+            model_stats=model_stats,
+            hourly_data=hourly_data,
+            daily_data=daily_data,
+            recent_activity=recent_activity
+        )
+    except Exception as e:
+        logger.error(f"获取仪表盘数据失败: {e}")
+        raise HTTPException(status_code=500, detail=f"获取统计数据失败: {str(e)}") from e
+
+
+async def _get_summary_statistics(start_time: datetime, end_time: datetime) -> StatisticsSummary:
+    """获取摘要统计数据"""
+    summary = StatisticsSummary()
+    
+    # 查询 LLM 使用记录
+    llm_records = list(
+        LLMUsage.select()
+        .where(LLMUsage.timestamp >= start_time)
+        .where(LLMUsage.timestamp <= end_time)
+    )
+    
+    total_time_cost = 0.0
+    time_cost_count = 0
+    
+    for record in llm_records:
+        summary.total_requests += 1
+        summary.total_cost += record.cost or 0.0
+        summary.total_tokens += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
+        
+        if record.time_cost and record.time_cost > 0:
+            total_time_cost += record.time_cost
+            time_cost_count += 1
+    
+    # 计算平均响应时间
+    if time_cost_count > 0:
+        summary.avg_response_time = total_time_cost / time_cost_count
+    
+    # 查询在线时间
+    online_records = list(
+        OnlineTime.select()
+        .where(
+            (OnlineTime.start_timestamp >= start_time) |
+            (OnlineTime.end_timestamp >= start_time)
+        )
+    )
+    
+    for record in online_records:
+        start = max(record.start_timestamp, start_time)
+        end = min(record.end_timestamp, end_time)
+        if end > start:
+            summary.online_time += (end - start).total_seconds()
+    
+    # 查询消息数量
+    messages = list(
+        Messages.select()
+        .where(Messages.time >= start_time.timestamp())
+        .where(Messages.time <= end_time.timestamp())
+    )
+    
+    summary.total_messages = len(messages)
+    # 简单统计：如果 reply_to 不为空，则认为是回复
+    summary.total_replies = len([m for m in messages if m.reply_to])
+    
+    # 计算派生指标
+    if summary.online_time > 0:
+        online_hours = summary.online_time / 3600.0
+        summary.cost_per_hour = summary.total_cost / online_hours
+        summary.tokens_per_hour = summary.total_tokens / online_hours
+    
+    return summary
+
+
+async def _get_model_statistics(start_time: datetime) -> List[ModelStatistics]:
+    """获取模型统计数据"""
+    model_data = defaultdict(lambda: {
+        'request_count': 0,
+        'total_cost': 0.0,
+        'total_tokens': 0,
+        'time_costs': []
+    })
+    
+    records = list(
+        LLMUsage.select()
+        .where(LLMUsage.timestamp >= start_time)
+    )
+    
+    for record in records:
+        model_name = record.model_assign_name or record.model_name or "unknown"
+        model_data[model_name]['request_count'] += 1
+        model_data[model_name]['total_cost'] += record.cost or 0.0
+        model_data[model_name]['total_tokens'] += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
+        
+        if record.time_cost and record.time_cost > 0:
+            model_data[model_name]['time_costs'].append(record.time_cost)
+    
+    # 转换为列表并排序
+    result = []
+    for model_name, data in model_data.items():
+        avg_time = sum(data['time_costs']) / len(data['time_costs']) if data['time_costs'] else 0.0
+        result.append(ModelStatistics(
+            model_name=model_name,
+            request_count=data['request_count'],
+            total_cost=data['total_cost'],
+            total_tokens=data['total_tokens'],
+            avg_response_time=avg_time
+        ))
+    
+    # 按请求数排序
+    result.sort(key=lambda x: x.request_count, reverse=True)
+    return result[:10]  # 返回前10个
+
+
+async def _get_hourly_statistics(start_time: datetime, end_time: datetime) -> List[TimeSeriesData]:
+    """获取小时级统计数据"""
+    # 创建小时桶
+    hourly_buckets = defaultdict(lambda: {'requests': 0, 'cost': 0.0, 'tokens': 0})
+    
+    records = list(
+        LLMUsage.select()
+        .where(LLMUsage.timestamp >= start_time)
+        .where(LLMUsage.timestamp <= end_time)
+    )
+    
+    for record in records:
+        # 获取小时键（去掉分钟和秒）
+        hour_key = record.timestamp.replace(minute=0, second=0, microsecond=0)
+        hour_str = hour_key.isoformat()
+        
+        hourly_buckets[hour_str]['requests'] += 1
+        hourly_buckets[hour_str]['cost'] += record.cost or 0.0
+        hourly_buckets[hour_str]['tokens'] += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
+    
+    # 填充所有小时（包括没有数据的）
+    result = []
+    current = start_time.replace(minute=0, second=0, microsecond=0)
+    while current <= end_time:
+        hour_str = current.isoformat()
+        data = hourly_buckets.get(hour_str, {'requests': 0, 'cost': 0.0, 'tokens': 0})
+        result.append(TimeSeriesData(
+            timestamp=hour_str,
+            requests=data['requests'],
+            cost=data['cost'],
+            tokens=data['tokens']
+        ))
+        current += timedelta(hours=1)
+    
+    return result
+
+
+async def _get_daily_statistics(start_time: datetime, end_time: datetime) -> List[TimeSeriesData]:
+    """获取日级统计数据"""
+    daily_buckets = defaultdict(lambda: {'requests': 0, 'cost': 0.0, 'tokens': 0})
+    
+    records = list(
+        LLMUsage.select()
+        .where(LLMUsage.timestamp >= start_time)
+        .where(LLMUsage.timestamp <= end_time)
+    )
+    
+    for record in records:
+        # 获取日期键
+        day_key = record.timestamp.replace(hour=0, minute=0, second=0, microsecond=0)
+        day_str = day_key.isoformat()
+        
+        daily_buckets[day_str]['requests'] += 1
+        daily_buckets[day_str]['cost'] += record.cost or 0.0
+        daily_buckets[day_str]['tokens'] += (record.prompt_tokens or 0) + (record.completion_tokens or 0)
+    
+    # 填充所有天
+    result = []
+    current = start_time.replace(hour=0, minute=0, second=0, microsecond=0)
+    while current <= end_time:
+        day_str = current.isoformat()
+        data = daily_buckets.get(day_str, {'requests': 0, 'cost': 0.0, 'tokens': 0})
+        result.append(TimeSeriesData(
+            timestamp=day_str,
+            requests=data['requests'],
+            cost=data['cost'],
+            tokens=data['tokens']
+        ))
+        current += timedelta(days=1)
+    
+    return result
+
+
+async def _get_recent_activity(limit: int = 10) -> List[Dict[str, Any]]:
+    """获取最近活动"""
+    records = list(
+        LLMUsage.select()
+        .order_by(LLMUsage.timestamp.desc())
+        .limit(limit)
+    )
+    
+    activities = []
+    for record in records:
+        activities.append({
+            'timestamp': record.timestamp.isoformat(),
+            'model': record.model_assign_name or record.model_name,
+            'request_type': record.request_type,
+            'tokens': (record.prompt_tokens or 0) + (record.completion_tokens or 0),
+            'cost': record.cost or 0.0,
+            'time_cost': record.time_cost or 0.0,
+            'status': record.status
+        })
+    
+    return activities
+
+
+@router.get("/summary")
+async def get_summary(hours: int = 24):
+    """
+    获取统计摘要
+    
+    Args:
+        hours: 统计时间范围（小时）
+    """
+    try:
+        now = datetime.now()
+        start_time = now - timedelta(hours=hours)
+        summary = await _get_summary_statistics(start_time, now)
+        return summary
+    except Exception as e:
+        logger.error(f"获取统计摘要失败: {e}")
+        raise HTTPException(status_code=500, detail=str(e)) from e
+
+
+@router.get("/models")
+async def get_model_stats(hours: int = 24):
+    """
+    获取模型统计
+    
+    Args:
+        hours: 统计时间范围（小时）
+    """
+    try:
+        now = datetime.now()
+        start_time = now - timedelta(hours=hours)
+        stats = await _get_model_statistics(start_time)
+        return stats
+    except Exception as e:
+        logger.error(f"获取模型统计失败: {e}")
+        raise HTTPException(status_code=500, detail=str(e)) from e