由于List<>在内部使用数组，因此基本性能应该是相同的。为什么这个列表可能会稍微慢一些，有两个原因:

要在列表中查找元素，调用list方法，该方法在底层数组中进行查找。所以你需要一个额外的方法调用。另一方面，编译器可能会识别出这一点，并优化“不必要的”调用。 如果编译器知道数组的大小，它可能会做一些特殊的优化，而对于一个未知长度的列表，它就不能这样做。如果列表中只有几个元素，这可能会带来一些性能改进。

要检查它是否对您有任何影响，最好将发布的计时函数调整为您计划使用的大小列表，并查看您的特殊情况的结果如何。

这是一个使用字典IEnumerable的例子:

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;

static class Program
{
    static void Main()
    {
        List<int> list = new List<int>(6000000);

        for (int i = 0; i < 6000000; i++)
        {
                list.Add(i);
        }
        Console.WriteLine("Count: {0}", list.Count);

        int[] arr = list.ToArray();
        IEnumerable<int> Ienumerable = list.ToArray();
        Dictionary<int, bool> dict = list.ToDictionary(x => x, y => true);

        int chk = 0;
        Stopwatch watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            int len = list.Count;
            for (int i = 0; i < len; i++)
            {
                chk += list[i];
            }
        }
        watch.Stop();
        Console.WriteLine("List/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            for (int i = 0; i < arr.Length; i++)
            {
                chk += arr[i];
            }
        }
        watch.Stop();
        Console.WriteLine("Array/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in Ienumerable)
            {
                chk += i;
            }
        }

        Console.WriteLine("Ienumerable/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in dict.Keys)
            {
                chk += i;
            }
        }

        Console.WriteLine("Dict/for: {0}ms ({1})", watch.ElapsedMilliseconds, chk);


        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in list)
            {
                chk += i;
            }
        }

        watch.Stop();
        Console.WriteLine("List/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in arr)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Array/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);



        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in Ienumerable)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Ienumerable/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in dict.Keys)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Dict/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        Console.ReadLine();
    }
}

对于@Marc Gravell的回答，我有两点需要澄清。

测试是在。net 6 x64版本中完成的。

测试代码结束。

数组和列表没有以相同的方式测试

为了在相同条件下测试array和List，还需要修改for。

for (int i = 0; i < arr.Length; i++)

新版本:

int len = arr.Length;
for (int i = 0; i < len; i++)

瓶颈列表/foreach:

List (List/foreach测试)的瓶颈是可以修复的。

改为:

list.ForEach(x => chk += x);

在Windows 10 pro 21H1 x64的笔记本电脑上测试运行，内核为i7-10510U

List/for Count out: 1495ms (589725196)
List/for Count in: 1706ms (589725196)
Array/for Count out: 945ms (589725196)
Array/for Count in: 1072ms (589725196)
List/foreach: 2114ms (589725196)
List/foreach fixed: 1210ms (589725196)
Array/foreach: 1179ms (589725196)

结果解释

数组/for比原始测试快。(减少12%)

List/foreach fixed比List/for快。

List/foreach fixed接近Array/foreach。

这个测试我已经运行了几次。结果改变了，但数量级保持不变。

这个测试的结果表明，您确实必须对性能有很大的需求才能强制使用Array。

根据用于操作List的方法，性能可以除以2。

这个测试是局部的。没有随机存取、直接存取、写存取测试等。

是我弄错了什么地方，还是你有其他提高性能的想法?

测试代码:

using System;
using System.Collections.Generic;
using System.Diagnostics;
static class Program
{
    static void Main()
    {        List<int> list = new List<int>(6000000);
        Random rand = new Random(12345);
        for (int i = 0; i < 6000000; i++)
        {
            list.Add(rand.Next(5000));
        }
        int[] arr = list.ToArray();

        int chk = 0;
        Stopwatch watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            int len = list.Count;
            for (int i = 0; i < len; i++)
            {
                chk += list[i];
            }
        }
        watch.Stop();
        Console.WriteLine("List/for Count out: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        Stopwatch watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            for (int i = 0; i < list.Count; i++)
            {
                chk += list[i];
            }
        }
        watch.Stop();
        Console.WriteLine("List/for Count in: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            int len = arr.Length;
            for (int i = 0; i < len; i++)
            {
                chk += arr[i];
            }
        }
        watch.Stop();
        Console.WriteLine("Array/for Count out: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            for (int i = 0; i < arr.Length; i++)
            {
                chk += arr[i];
            }
        }
        watch.Stop();
        Console.WriteLine("Array/for Count in: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in list)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("List/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            list.ForEach(i => chk += i);
        }
        watch.Stop();
        Console.WriteLine("List/foreach fixed: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        chk = 0;
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 100; rpt++)
        {
            foreach (int i in arr)
            {
                chk += i;
            }
        }
        watch.Stop();
        Console.WriteLine("Array/foreach: {0}ms ({1})", watch.ElapsedMilliseconds, chk);

        Console.ReadLine();
    }
}

我担心在其他答案中发布的基准测试仍然会为编译器留下优化，消除或合并循环的空间，所以我写了一个:

使用不可预测的输入(随机) 运行计算结果并将结果打印到控制台 每次重复修改输入数据

结果是，直接数组的性能比访问封装在IList中的数组要好250%:

10亿次数组访问:4000毫秒 10亿次列表访问:10000毫秒 1亿个数组访问:350毫秒 1亿次列表访问:1000毫秒

代码如下:

static void Main(string[] args) {
  const int TestPointCount = 1000000;
  const int RepetitionCount = 1000;

  Stopwatch arrayTimer = new Stopwatch();
  Stopwatch listTimer = new Stopwatch();

  Point2[] points = new Point2[TestPointCount];
  var random = new Random();
  for (int index = 0; index < TestPointCount; ++index) {
    points[index].X = random.NextDouble();
    points[index].Y = random.NextDouble();
  }

  for (int repetition = 0; repetition <= RepetitionCount; ++repetition) {
    if (repetition > 0) { // first repetition is for cache warmup
      arrayTimer.Start();
    }
    doWorkOnArray(points);
    if (repetition > 0) { // first repetition is for cache warmup
      arrayTimer.Stop();
    }

    if (repetition > 0) { // first repetition is for cache warmup
      listTimer.Start();
    }
    doWorkOnList(points);
    if (repetition > 0) { // first repetition is for cache warmup
      listTimer.Stop();
    }
  }

  Console.WriteLine("Ignore this: " + points[0].X + points[0].Y);
  Console.WriteLine(
    string.Format(
      "{0} accesses on array took {1} ms",
      RepetitionCount * TestPointCount, arrayTimer.ElapsedMilliseconds
    )
  );
  Console.WriteLine(
    string.Format(
      "{0} accesses on list took {1} ms",
      RepetitionCount * TestPointCount, listTimer.ElapsedMilliseconds
    )
  );

}

private static void doWorkOnArray(Point2[] points) {
  var random = new Random();

  int pointCount = points.Length;

  Point2 accumulated = Point2.Zero;
  for (int index = 0; index < pointCount; ++index) {
    accumulated.X += points[index].X;
    accumulated.Y += points[index].Y;
  }

  accumulated /= pointCount;

  // make use of the result somewhere so the optimizer can't eliminate the loop
  // also modify the input collection so the optimizer can merge the repetition loop
  points[random.Next(0, pointCount)] = accumulated;
}

private static void doWorkOnList(IList<Point2> points) {
  var random = new Random();

  int pointCount = points.Count;

  Point2 accumulated = Point2.Zero;
  for (int index = 0; index < pointCount; ++index) {
    accumulated.X += points[index].X;
    accumulated.Y += points[index].Y;
  }

  accumulated /= pointCount;

  // make use of the result somewhere so the optimizer can't eliminate the loop
  // also modify the input collection so the optimizer can merge the repetition loop
  points[random.Next(0, pointCount)] = accumulated;
}

static long[] longs = new long[500000];
static long[] longs2 = {};
static List<long> listLongs = new List<long> { };
static void Main(string[] args)
{
    Console.CursorVisible = false;
    Stopwatch time = new Stopwatch();

    time.Start();
    for (int f = 50000000; f < 50255000; f++)
    {
        listLongs.Add(f);
    }

    //List  Time: 1ms    Count : 255000
    Console.WriteLine("List Time: " + time.ElapsedMilliseconds + " | Count: " + listLongs.Count());

    time.Restart();
    time.Start();
    for (long i = 1; i < 500000; i++)
    {
        longs[i] = i * 200;
    }

    //Array Time: 2ms Length: 500000 (Unrealistic Data)
    Console.WriteLine("Array Time: " + time.ElapsedMilliseconds + " | Length: " + longs.Length);

    time.Restart();
    time.Start();
    for (int i = 50000000; i < 50055000; i++)
    {
        longs2 = longs2.Append(i).ToArray();
    }

    //Array Time: 17950ms Length: 55000
    Console.WriteLine("Array Append Time: " + time.ElapsedMilliseconds + " | Length: " + longs2.Length);

    Console.ReadLine();
}

如果您计划不断地向数组中添加少量数据，那么list更快

这实际上取决于你将如何使用数组。

不要试图通过增加元素数量来增加容量。

性能

List For Add: 1ms
Array For Add: 2397ms

    Stopwatch watch;
        #region --> List For Add <--

        List<int> intList = new List<int>();
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 60000; rpt++)
        {
            intList.Add(rand.Next());
        }
        watch.Stop();
        Console.WriteLine("List For Add: {0}ms", watch.ElapsedMilliseconds);
        #endregion

        #region --> Array For Add <--

        int[] intArray = new int[0];
        watch = Stopwatch.StartNew();
        int sira = 0;
        for (int rpt = 0; rpt < 60000; rpt++)
        {
            sira += 1;
            Array.Resize(ref intArray, intArray.Length + 1);
            intArray[rpt] = rand.Next();

        }
        watch.Stop();
        Console.WriteLine("Array For Add: {0}ms", watch.ElapsedMilliseconds);

        #endregion