阿里云服务器海外地域最新租用收费价格表（2024更新）
阿里云服务器海外地域有亚太、欧洲、美洲和中东，海外地域的云服务器租用收费价格相比国内地域要高一点，不同地域的云服务器价格是不一样的，购买时长的不同，价格也不一样，购买时间越长，价格越便宜，下面是2024年截至目前阿里云海外地域云服务器的最新租用收费价格表。https://upload-images.jianshu.io/upload_images/19316870-5cface46bd0c435c.png
<h2>阿里云服务器海外地域有哪些？</h2>
阿里云服务器海外地域有亚太、欧洲、美洲和中东，亚太地域主要包括日本(东京)、韩国(首尔)、新加坡、马来西亚(吉隆坡)、菲律宾(马尼拉)、印度尼西亚（雅加达)、泰国(曼谷)。欧洲地域主要包括英国（伦敦)和德国(法兰克福)。美洲地域主要包括美国(弗吉尼亚)和美国(硅谷)。中东地域主要为阿联酋(迪拜)。具体的地域ID、可用区数量、可用区名称、可用区ID如下表所示：
<table>
<thead>
<tr>
<th>地域名称</th>
<th>地域ID</th>
<th>可用区数量</th>
<th>可用区名称</th>
<th>可用区ID</th>
</tr>
</thead>
<tbody>
<tr>
<td>新加坡</td>
<td>ap-southeast-1</td>
<td>3</td>
<td>新加坡 可用区A新加坡 可用区B新加坡 可用区C</td>
<td>ap-southeast-1aap-southeast-1bap-southeast-1c</td>
</tr>
<tr>
<td>澳大利亚（悉尼）</td>
<td>ap-southeast-2</td>
<td>2</td>
<td>悉尼 可用区A悉尼 可用区B</td>
<td>ap-southeast-2aap-southeast-2b</td>
</tr>
<tr>
<td>马来西亚（吉隆坡）</td>
<td>ap-southeast-3</td>
<td>2</td>
<td>吉隆坡 可用区A吉隆坡 可用区B</td>
<td>ap-southeast-3aap-southeast-3b</td>
</tr>
<tr>
<td>印度尼西亚（雅加达）</td>
<td>ap-southeast-5</td>
<td>3</td>
<td>雅加达 可用区A雅加达 可用区B雅加达 可用区C</td>
<td>ap-southeast-5aap-southeast-5bap-southeast-5c</td>
</tr>
<tr>
<td>菲律宾（马尼拉）</td>
<td>ap-southeast-6</td>
<td>1</td>
<td>马尼拉 可用区A</td>
<td>ap-southeast-6a</td>
</tr>
<tr>
<td>泰国（曼谷）</td>
<td>ap-southeast-7</td>
<td>1</td>
<td>曼谷 可用区A</td>
<td>ap-southeast-7a</td>
</tr>
<tr>
<td>印度（孟买）</td>
<td>ap-south-1</td>
<td>2</td>
<td>孟买 可用区A孟买 可用区B</td>
<td>ap-south-1aap-south-1b</td>
</tr>
<tr>
<td>日本（东京）</td>
<td>ap-northeast-1</td>
<td>3</td>
<td>东京 可用区A东京 可用区B东京 可用区C</td>
<td>ap-northeast-1aap-northeast-1bap-northeast-1c</td>
</tr>
<tr>
<td>韩国（首尔）</td>
<td>ap-northeast-2</td>
<td>1</td>
<td>首尔 可用区A</td>
<td>ap-northeast-2a</td>
</tr>
<tr>
<td>美国（硅谷）</td>
<td>us-west-1</td>
<td>2</td>
<td>硅谷 可用区A硅谷 可用区B</td>
<td>us-west-1aus-west-1b</td>
</tr>
<tr>
<td>美国（弗吉尼亚）</td>
<td>us-east-1</td>
<td>2</td>
<td>弗吉尼亚 可用区A弗吉尼亚 可用区B</td>
<td>us-east-1aus-east-1b</td>
</tr>
<tr>
<td>德国（法兰克福）</td>
<td>eu-central-1</td>
<td>3</td>
<td>法兰克福 可用区A法兰克福 可用区B法兰克福 可用区C</td>
<td>eu-central-1aeu-central-1beu-central-1c</td>
</tr>
<tr>
<td>英国（伦敦）</td>
<td>eu-west-1</td>
<td>2</td>
<td>伦敦 可用区A伦敦 可用区B</td>
<td>eu-west-1aeu-west-1b</td>
</tr>
<tr>
<td>阿联酋（迪拜）</td>
<td>me-east-1</td>
<td>1</td>
<td>迪拜 可用区A</td>
<td>me-east-1a</td>
</tr>
</tbody>
</table>
<h2>阿里云服务器海外地域云服务器收费标准</h2>
云服务器的收费方式可以按量（小时）计费、按月计费和年付不同的方式，详细的收费标准可通过阿里云价格计算器查询，以下以美国(硅谷)地域为例为大家展示阿里云服务器海外地域云服务器收费标准，包括按量(小时)、标准目录月价、优惠月价、年付月价、3年付月价、5年付月价。
<table>
<thead>
<tr>
<th>实例规格</th>
<th>vCPUs</th>
<th>内存(GiB)</th>
<th>按量(小时)</th>
<th>标准目录月价</th>
<th>优惠月价</th>
<th>年付月价</th>
<th>3年付月价</th>
<th>5年付月价</th>
</tr>
</thead>
<tbody>
<tr>
<td>通用算力型 ecs.u1-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.491725</td>
<td>255.72</td>
<td>255.72</td>
<td>153.43</td>
<td>97.17</td>
<td>97.17</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.400945</td>
<td>207.77</td>
<td>207.77</td>
<td>124.66</td>
<td>78.95</td>
<td>78.95</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.large</td>
<td>2</td>
<td>16</td>
<td>0.643025</td>
<td>331.15</td>
<td>331.15</td>
<td>198.69</td>
<td>125.84</td>
<td>125.84</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.380771</td>
<td>197.38</td>
<td>197.38</td>
<td>118.43</td>
<td>75</td>
<td>75</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.xlarge</td>
<td>4</td>
<td>4</td>
<td>0.761543</td>
<td>394.75</td>
<td>394.75</td>
<td>236.85</td>
<td>150.01</td>
<td>150.01</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.28605</td>
<td>662.3</td>
<td>662.3</td>
<td>397.38</td>
<td>251.68</td>
<td>251.68</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.80189</td>
<td>415.53</td>
<td>415.53</td>
<td>249.32</td>
<td>157.9</td>
<td>157.9</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.98345</td>
<td>511.45</td>
<td>511.45</td>
<td>306.87</td>
<td>194.35</td>
<td>194.35</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.9669</td>
<td>1022.89</td>
<td>1022.89</td>
<td>613.73</td>
<td>388.7</td>
<td>388.7</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.60378</td>
<td>831.06</td>
<td>831.06</td>
<td>498.64</td>
<td>315.8</td>
<td>315.8</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.5721</td>
<td>1324.61</td>
<td>1324.61</td>
<td>794.76</td>
<td>503.35</td>
<td>503.35</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.2xlarge</td>
<td>8</td>
<td>8</td>
<td>1.523927</td>
<td>789.51</td>
<td>789.51</td>
<td>473.71</td>
<td>300.01</td>
<td>300.01</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.3xlarge</td>
<td>12</td>
<td>48</td>
<td>2.95035</td>
<td>1534.34</td>
<td>1534.34</td>
<td>920.6</td>
<td>583.05</td>
<td>583.05</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.3xlarge</td>
<td>12</td>
<td>12</td>
<td>2.28547</td>
<td>1184.26</td>
<td>1184.26</td>
<td>710.56</td>
<td>450.02</td>
<td>450.02</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.40567</td>
<td>1246.59</td>
<td>1246.59</td>
<td>747.96</td>
<td>473.71</td>
<td>473.71</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.3xlarge</td>
<td>12</td>
<td>96</td>
<td>3.85815</td>
<td>1986.91</td>
<td>1986.91</td>
<td>1192.15</td>
<td>755.03</td>
<td>755.03</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.4xlarge</td>
<td>16</td>
<td>16</td>
<td>3.047014</td>
<td>1579.02</td>
<td>1579.02</td>
<td>947.41</td>
<td>600.03</td>
<td>600.03</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.4xlarge</td>
<td>16</td>
<td>128</td>
<td>5.1442</td>
<td>2649.21</td>
<td>2649.21</td>
<td>1589.53</td>
<td>1006.7</td>
<td>1006.7</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.4xlarge</td>
<td>16</td>
<td>64</td>
<td>3.9338</td>
<td>2045.78</td>
<td>2045.78</td>
<td>1227.47</td>
<td>777.4</td>
<td>777.4</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.20756</td>
<td>1662.12</td>
<td>1662.12</td>
<td>997.27</td>
<td>631.61</td>
<td>631.61</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.8xlarge</td>
<td>32</td>
<td>128</td>
<td>7.8676</td>
<td>4091.56</td>
<td>4091.56</td>
<td>2454.94</td>
<td>1554.79</td>
<td>1554.79</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.8xlarge</td>
<td>32</td>
<td>256</td>
<td>10.2884</td>
<td>5298.42</td>
<td>5298.42</td>
<td>3179.05</td>
<td>2013.4</td>
<td>2013.4</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.8xlarge</td>
<td>32</td>
<td>64</td>
<td>6.41512</td>
<td>3324.25</td>
<td>3324.25</td>
<td>1994.55</td>
<td>1263.21</td>
<td>1263.21</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.8xlarge</td>
<td>32</td>
<td>32</td>
<td>6.094028</td>
<td>3158.04</td>
<td>3158.04</td>
<td>1894.82</td>
<td>1200.05</td>
<td>1200.05</td>
</tr>
<tr>
<td>通用型 ecs.g7.large</td>
<td>2</td>
<td>8</td>
<td>0.53578</td>
<td>346.19</td>
<td>346.19</td>
<td>242.33</td>
<td>155.78</td>
<td>103.86</td>
</tr>
<tr>
<td>通用型 ecs.g7.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.07156</td>
<td>692.38</td>
<td>692.38</td>
<td>484.66</td>
<td>311.57</td>
<td>207.71</td>
</tr>
<tr>
<td>通用型 ecs.g7.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.14401</td>
<td>1384.76</td>
<td>1384.76</td>
<td>969.33</td>
<td>623.14</td>
<td>415.43</td>
</tr>
<tr>
<td>通用型 ecs.g7.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.21557</td>
<td>2077.14</td>
<td>2077.14</td>
<td>1454</td>
<td>934.71</td>
<td>623.14</td>
</tr>
<tr>
<td>通用型 ecs.g7.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.28802</td>
<td>2769.52</td>
<td>2769.52</td>
<td>1938.66</td>
<td>1246.28</td>
<td>830.85</td>
</tr>
<tr>
<td>通用型 ecs.g7.6xlarge</td>
<td>24</td>
<td>96</td>
<td>6.43114</td>
<td>4154.27</td>
<td>4154.27</td>
<td>2907.99</td>
<td>1869.42</td>
<td>1246.28</td>
</tr>
<tr>
<td>通用型 ecs.g7.8xlarge</td>
<td>32</td>
<td>128</td>
<td>8.57515</td>
<td>5539.03</td>
<td>5539.03</td>
<td>3877.32</td>
<td>2492.56</td>
<td>1661.71</td>
</tr>
<tr>
<td>通用型 ecs.g7.16xlarge</td>
<td>64</td>
<td>256</td>
<td>17.15119</td>
<td>11078.06</td>
<td>11078.06</td>
<td>7754.64</td>
<td>4985.13</td>
<td>3323.42</td>
</tr>
<tr>
<td>通用型 ecs.g7.32xlarge</td>
<td>128</td>
<td>512</td>
<td>34.30149</td>
<td>22156.12</td>
<td>22156.12</td>
<td>15509.29</td>
<td>9970.26</td>
<td>6646.84</td>
</tr>
<tr>
<td>计算型 ecs.c7.large</td>
<td>2</td>
<td>4</td>
<td>0.47437</td>
<td>281.26</td>
<td>281.26</td>
<td>196.88</td>
<td>126.57</td>
<td>106.88</td>
</tr>
<tr>
<td>计算型 ecs.c7.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.94874</td>
<td>562.53</td>
<td>562.53</td>
<td>393.77</td>
<td>253.14</td>
<td>168.76</td>
</tr>
<tr>
<td>计算型 ecs.c7.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.89837</td>
<td>1125.06</td>
<td>1125.06</td>
<td>787.54</td>
<td>506.28</td>
<td>337.52</td>
</tr>
<tr>
<td>计算型 ecs.c7.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.84711</td>
<td>1687.58</td>
<td>1687.58</td>
<td>1181.31</td>
<td>759.41</td>
<td>506.27</td>
</tr>
<tr>
<td>计算型 ecs.c7.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.79674</td>
<td>2250.11</td>
<td>2250.11</td>
<td>1575.08</td>
<td>1012.55</td>
<td>675.03</td>
</tr>
<tr>
<td>计算型 ecs.c7.6xlarge</td>
<td>24</td>
<td>48</td>
<td>5.69422</td>
<td>3375.17</td>
<td>3375.17</td>
<td>2362.62</td>
<td>1518.82</td>
<td>1012.55</td>
</tr>
<tr>
<td>计算型 ecs.c7.8xlarge</td>
<td>32</td>
<td>64</td>
<td>7.59259</td>
<td>4500.22</td>
<td>4500.22</td>
<td>3150.16</td>
<td>2025.1</td>
<td>1350.07</td>
</tr>
<tr>
<td>计算型 ecs.c7.16xlarge</td>
<td>64</td>
<td>128</td>
<td>15.18607</td>
<td>9000.45</td>
<td>9000.45</td>
<td>6300.31</td>
<td>4050.2</td>
<td>2700.13</td>
</tr>
<tr>
<td>计算型 ecs.c7.32xlarge</td>
<td>128</td>
<td>256</td>
<td>30.37125</td>
<td>18000.89</td>
<td>18000.89</td>
<td>12600.62</td>
<td>8100.4</td>
<td>5400.27</td>
</tr>
<tr>
<td>通用型 ecs.g6.large</td>
<td>2</td>
<td>8</td>
<td>0.5785</td>
<td>300.85</td>
<td>300.85</td>
<td>210.59</td>
<td>135.38</td>
<td>90.26</td>
</tr>
<tr>
<td>通用型 ecs.g6.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.157</td>
<td>601.7</td>
<td>601.7</td>
<td>421.19</td>
<td>270.77</td>
<td>180.51</td>
</tr>
<tr>
<td>通用型 ecs.g6.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.314</td>
<td>1203.4</td>
<td>1203.4</td>
<td>842.38</td>
<td>541.53</td>
<td>361.02</td>
</tr>
<tr>
<td>通用型 ecs.g6.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.471</td>
<td>1805.1</td>
<td>1805.1</td>
<td>1263.57</td>
<td>812.29</td>
<td>541.53</td>
</tr>
<tr>
<td>通用型 ecs.g6.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.628</td>
<td>2406.8</td>
<td>2406.8</td>
<td>1684.76</td>
<td>1083.06</td>
<td>722.04</td>
</tr>
<tr>
<td>通用型 ecs.g6.6xlarge</td>
<td>24</td>
<td>96</td>
<td>6.942</td>
<td>3610.2</td>
<td>3610.2</td>
<td>2527.14</td>
<td>1624.59</td>
<td>1083.06</td>
</tr>
<tr>
<td>通用型 ecs.g6.8xlarge</td>
<td>32</td>
<td>128</td>
<td>9.256</td>
<td>4813.6</td>
<td>4813.6</td>
<td>3369.52</td>
<td>2166.12</td>
<td>1444.08</td>
</tr>
<tr>
<td>通用型 ecs.g6.13xlarge</td>
<td>52</td>
<td>192</td>
<td>15.041</td>
<td>7822.1</td>
<td>7822.1</td>
<td>5475.47</td>
<td>3519.95</td>
<td>2346.63</td>
</tr>
<tr>
<td>通用型 ecs.g6.26xlarge</td>
<td>104</td>
<td>384</td>
<td>30.082</td>
<td>15644.2</td>
<td>15644.2</td>
<td>10950.94</td>
<td>7039.89</td>
<td>4693.26</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c4g1.xlarge</td>
<td>4</td>
<td>15</td>
<td>8.025</td>
<td>3852.04</td>
<td>3852.04</td>
<td>3274.23</td>
<td>2118.62</td>
<td>1463.78</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c8g1.2xlarge</td>
<td>8</td>
<td>31</td>
<td>9.36</td>
<td>4492.89</td>
<td>4492.89</td>
<td>3818.96</td>
<td>2471.09</td>
<td>1707.3</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c16g1.4xlarge</td>
<td>16</td>
<td>62</td>
<td>12.045</td>
<td>5781.54</td>
<td>5781.54</td>
<td>4914.31</td>
<td>3179.85</td>
<td>2196.99</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.6xlarge</td>
<td>24</td>
<td>93</td>
<td>15.296</td>
<td>7341.86</td>
<td>7341.86</td>
<td>6240.58</td>
<td>4038.02</td>
<td>2789.91</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.12xlarge</td>
<td>48</td>
<td>186</td>
<td>30.606</td>
<td>14690.69</td>
<td>14690.69</td>
<td>12487.09</td>
<td>8079.88</td>
<td>5582.46</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.24xlarge</td>
<td>96</td>
<td>372</td>
<td>61.226</td>
<td>29388.35</td>
<td>29388.35</td>
<td>24980.1</td>
<td>16163.59</td>
<td>11167.57</td>
</tr>
<tr>
<td>通用型弹性裸金属服务器 ecs.ebmg6.26xlarge</td>
<td>104</td>
<td>384</td>
<td>33.8</td>
<td>15644.2</td>
<td>15644.2</td>
<td>13297.57</td>
<td>8604.31</td>
<td>5944.8</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.large</td>
<td>2</td>
<td>8</td>
<td>0.63635</td>
<td>330.94</td>
<td>330.94</td>
<td>231.65</td>
<td>148.92</td>
<td>99.28</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.2727</td>
<td>661.87</td>
<td>661.87</td>
<td>463.31</td>
<td>297.84</td>
<td>198.56</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.5454</td>
<td>1323.74</td>
<td>1323.74</td>
<td>926.62</td>
<td>595.68</td>
<td>397.12</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.0908</td>
<td>2647.48</td>
<td>2647.48</td>
<td>1853.24</td>
<td>1191.37</td>
<td>794.24</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.8xlarge</td>
<td>32</td>
<td>128</td>
<td>10.1816</td>
<td>5294.96</td>
<td>5294.96</td>
<td>3706.47</td>
<td>2382.73</td>
<td>1588.49</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.13xlarge</td>
<td>52</td>
<td>192</td>
<td>16.5451</td>
<td>8604.31</td>
<td>8604.31</td>
<td>6023.02</td>
<td>3871.94</td>
<td>2581.29</td>
</tr>
<tr>
<td>计算型 ecs.c6.large</td>
<td>2</td>
<td>4</td>
<td>0.4717</td>
<td>244.43</td>
<td>244.43</td>
<td>171.1</td>
<td>109.99</td>
<td>92.88</td>
</tr>
<tr>
<td>计算型 ecs.c6.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.9434</td>
<td>488.86</td>
<td>488.86</td>
<td>342.2</td>
<td>219.99</td>
<td>146.66</td>
</tr>
<tr>
<td>计算型 ecs.c6.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.8868</td>
<td>977.72</td>
<td>977.72</td>
<td>684.4</td>
<td>439.97</td>
<td>293.32</td>
</tr>
<tr>
<td>计算型 ecs.c6.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.8302</td>
<td>1466.58</td>
<td>1466.58</td>
<td>1026.61</td>
<td>659.96</td>
<td>439.97</td>
</tr>
<tr>
<td>计算型 ecs.c6.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.7736</td>
<td>1955.44</td>
<td>1955.44</td>
<td>1368.81</td>
<td>879.95</td>
<td>586.63</td>
</tr>
<tr>
<td>计算型 ecs.c6.6xlarge</td>
<td>24</td>
<td>48</td>
<td>5.6604</td>
<td>2933.16</td>
<td>2933.16</td>
<td>2053.21</td>
<td>1319.92</td>
<td>879.95</td>
</tr>
<tr>
<td>计算型 ecs.c6.8xlarge</td>
<td>32</td>
<td>64</td>
<td>7.5472</td>
<td>3910.88</td>
<td>3910.88</td>
<td>2737.62</td>
<td>1759.9</td>
<td>1173.26</td>
</tr>
<tr>
<td>计算型 ecs.c6.13xlarge</td>
<td>52</td>
<td>96</td>
<td>12.2642</td>
<td>6355.18</td>
<td>6355.18</td>
<td>4448.63</td>
<td>2859.83</td>
<td>1906.55</td>
</tr>
<tr>
<td>计算型 ecs.c6.26xlarge</td>
<td>104</td>
<td>192</td>
<td>24.5284</td>
<td>12710.36</td>
<td>12710.36</td>
<td>8897.25</td>
<td>5719.66</td>
<td>3813.11</td>
</tr>
<tr>
<td>内存型 ecs.r6.large</td>
<td>2</td>
<td>16</td>
<td>0.7565</td>
<td>389.59</td>
<td>389.59</td>
<td>272.71</td>
<td>175.32</td>
<td>116.88</td>
</tr>
<tr>
<td>内存型 ecs.r6.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.513</td>
<td>779.18</td>
<td>779.18</td>
<td>545.43</td>
<td>350.63</td>
<td>233.75</td>
</tr>
<tr>
<td>内存型 ecs.r6.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.026</td>
<td>1558.36</td>
<td>1558.36</td>
<td>1090.85</td>
<td>701.26</td>
<td>467.51</td>
</tr>
<tr>
<td>内存型 ecs.r6.3xlarge</td>
<td>12</td>
<td>96</td>
<td>4.539</td>
<td>2337.54</td>
<td>2337.54</td>
<td>1636.28</td>
<td>1051.89</td>
<td>701.26</td>
</tr>
<tr>
<td>内存型 ecs.r6.4xlarge</td>
<td>16</td>
<td>128</td>
<td>6.052</td>
<td>3116.72</td>
<td>3116.72</td>
<td>2181.7</td>
<td>1402.52</td>
<td>935.02</td>
</tr>
<tr>
<td>内存型 ecs.r6.6xlarge</td>
<td>24</td>
<td>192</td>
<td>9.078</td>
<td>4675.08</td>
<td>4675.08</td>
<td>3272.56</td>
<td>2103.79</td>
<td>1402.52</td>
</tr>
<tr>
<td>内存型 ecs.r6.8xlarge</td>
<td>32</td>
<td>256</td>
<td>12.104</td>
<td>6233.44</td>
<td>6233.44</td>
<td>4363.41</td>
<td>2805.05</td>
<td>1870.03</td>
</tr>
<tr>
<td>内存型 ecs.r6.13xlarge</td>
<td>52</td>
<td>384</td>
<td>19.669</td>
<td>10129.34</td>
<td>10129.34</td>
<td>7090.54</td>
<td>4558.2</td>
<td>3038.8</td>
</tr>
<tr>
<td>内存型 ecs.r6.26xlarge</td>
<td>104</td>
<td>768</td>
<td>39.338</td>
<td>20258.68</td>
<td>20258.68</td>
<td>14181.08</td>
<td>9116.41</td>
<td>6077.6</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c4m1.large</td>
<td>2</td>
<td>0.5</td>
<td>0.0372</td>
<td>14.49</td>
<td>14.49</td>
<td>12.32</td>
<td>7.97</td>
<td>5.51</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c2m1.large</td>
<td>2</td>
<td>1</td>
<td>0.0651</td>
<td>28.49</td>
<td>28.49</td>
<td>24.22</td>
<td>15.67</td>
<td>10.83</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.1209</td>
<td>56.98</td>
<td>56.98</td>
<td>48.43</td>
<td>31.34</td>
<td>21.65</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.2418</td>
<td>114.45</td>
<td>114.45</td>
<td>97.28</td>
<td>62.95</td>
<td>43.49</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.4743</td>
<td>228.82</td>
<td>228.82</td>
<td>194.5</td>
<td>125.85</td>
<td>86.95</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.93</td>
<td>457.23</td>
<td>457.23</td>
<td>388.65</td>
<td>251.48</td>
<td>173.75</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.86</td>
<td>914.39</td>
<td>914.39</td>
<td>777.23</td>
<td>502.91</td>
<td>347.47</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.large</td>
<td>2</td>
<td>4</td>
<td>0.5429</td>
<td>281.07</td>
<td>281.07</td>
<td>196.75</td>
<td>126.48</td>
<td>106.81</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.0858</td>
<td>562.14</td>
<td>562.14</td>
<td>393.5</td>
<td>252.96</td>
<td>168.64</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.1716</td>
<td>1124.28</td>
<td>1124.28</td>
<td>787</td>
<td>505.93</td>
<td>337.28</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.2574</td>
<td>1686.42</td>
<td>1686.42</td>
<td>1180.49</td>
<td>758.89</td>
<td>505.93</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.3432</td>
<td>2248.56</td>
<td>2248.56</td>
<td>1573.99</td>
<td>1011.85</td>
<td>674.57</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.6xlarge</td>
<td>24</td>
<td>48</td>
<td>6.5148</td>
<td>3372.84</td>
<td>3372.84</td>
<td>2360.99</td>
<td>1517.78</td>
<td>1011.85</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.8xlarge</td>
<td>32</td>
<td>64</td>
<td>8.6864</td>
<td>4497.12</td>
<td>4497.12</td>
<td>3147.98</td>
<td>2023.7</td>
<td>1349.14</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.10xlarge</td>
<td>40</td>
<td>96</td>
<td>10.858</td>
<td>5621.4</td>
<td>5621.4</td>
<td>3934.98</td>
<td>2529.63</td>
<td>1686.42</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.16xlarge</td>
<td>64</td>
<td>128</td>
<td>17.3728</td>
<td>8994.24</td>
<td>8994.24</td>
<td>6295.97</td>
<td>4047.41</td>
<td>2698.27</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.20xlarge</td>
<td>80</td>
<td>192</td>
<td>21.716</td>
<td>11242.8</td>
<td>11242.8</td>
<td>7869.96</td>
<td>5059.26</td>
<td>3372.84</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.large</td>
<td>2</td>
<td>8</td>
<td>0.6319</td>
<td>330.94</td>
<td>330.94</td>
<td>231.66</td>
<td>148.92</td>
<td>99.28</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.2638</td>
<td>661.88</td>
<td>661.88</td>
<td>463.32</td>
<td>297.85</td>
<td>198.56</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.5276</td>
<td>1323.76</td>
<td>1323.76</td>
<td>926.63</td>
<td>595.69</td>
<td>397.13</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.7914</td>
<td>1985.64</td>
<td>1985.64</td>
<td>1389.95</td>
<td>893.54</td>
<td>595.69</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.0552</td>
<td>2647.52</td>
<td>2647.52</td>
<td>1853.26</td>
<td>1191.38</td>
<td>794.26</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.6xlarge</td>
<td>24</td>
<td>96</td>
<td>7.5828</td>
<td>3971.28</td>
<td>3971.28</td>
<td>2779.9</td>
<td>1787.08</td>
<td>1191.38</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.8xlarge</td>
<td>32</td>
<td>128</td>
<td>10.1104</td>
<td>5295.04</td>
<td>5295.04</td>
<td>3706.53</td>
<td>2382.77</td>
<td>1588.51</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.10xlarge</td>
<td>40</td>
<td>192</td>
<td>12.638</td>
<td>6618.8</td>
<td>6618.8</td>
<td>4633.16</td>
<td>2978.46</td>
<td>1985.64</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.16xlarge</td>
<td>64</td>
<td>256</td>
<td>20.2208</td>
<td>10590.08</td>
<td>10590.08</td>
<td>7413.06</td>
<td>4765.54</td>
<td>3177.02</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.20xlarge</td>
<td>80</td>
<td>384</td>
<td>25.276</td>
<td>13237.6</td>
<td>13237.6</td>
<td>9266.32</td>
<td>5956.92</td>
<td>3971.28</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.large</td>
<td>2</td>
<td>16</td>
<td>0.8277</td>
<td>428.53</td>
<td>428.53</td>
<td>299.97</td>
<td>192.84</td>
<td>128.56</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.6554</td>
<td>857.06</td>
<td>857.06</td>
<td>599.94</td>
<td>385.68</td>
<td>257.12</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.3108</td>
<td>1714.12</td>
<td>1714.12</td>
<td>1199.88</td>
<td>771.35</td>
<td>514.24</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.3xlarge</td>
<td>12</td>
<td>96</td>
<td>4.9662</td>
<td>2571.18</td>
<td>2571.18</td>
<td>1799.83</td>
<td>1157.03</td>
<td>771.35</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.4xlarge</td>
<td>16</td>
<td>128</td>
<td>6.6216</td>
<td>3428.24</td>
<td>3428.24</td>
<td>2399.77</td>
<td>1542.71</td>
<td>1028.47</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.6xlarge</td>
<td>24</td>
<td>192</td>
<td>9.9324</td>
<td>5142.36</td>
<td>5142.36</td>
<td>3599.65</td>
<td>2314.06</td>
<td>1542.71</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.8xlarge</td>
<td>32</td>
<td>256</td>
<td>13.2432</td>
<td>6856.48</td>
<td>6856.48</td>
<td>4799.54</td>
<td>3085.42</td>
<td>2056.94</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.10xlarge</td>
<td>40</td>
<td>384</td>
<td>16.554</td>
<td>8570.6</td>
<td>8570.6</td>
<td>5999.42</td>
<td>3856.77</td>
<td>2571.18</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.16xlarge</td>
<td>64</td>
<td>512</td>
<td>26.4864</td>
<td>13712.96</td>
<td>13712.96</td>
<td>9599.07</td>
<td>6170.83</td>
<td>4113.89</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.20xlarge</td>
<td>80</td>
<td>768</td>
<td>33.108</td>
<td>17141.2</td>
<td>17141.2</td>
<td>11998.84</td>
<td>7713.54</td>
<td>5142.36</td>
</tr>
<tr>
<td>内存型弹性裸金属服务器 ecs.ebmr6.26xlarge</td>
<td>104</td>
<td>768</td>
<td>44.2</td>
<td>20258.68</td>
<td>20258.68</td>
<td>17219.88</td>
<td>11142.27</td>
<td>7698.3</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.large</td>
<td>2</td>
<td>16</td>
<td>0.83215</td>
<td>428.55</td>
<td>428.55</td>
<td>299.98</td>
<td>192.85</td>
<td>128.56</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.6643</td>
<td>857.1</td>
<td>857.1</td>
<td>599.97</td>
<td>385.69</td>
<td>257.13</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.3286</td>
<td>1714.2</td>
<td>1714.2</td>
<td>1199.94</td>
<td>771.39</td>
<td>514.26</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.4xlarge</td>
<td>16</td>
<td>128</td>
<td>6.6572</td>
<td>3428.39</td>
<td>3428.39</td>
<td>2399.87</td>
<td>1542.78</td>
<td>1028.52</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.8xlarge</td>
<td>32</td>
<td>256</td>
<td>13.3144</td>
<td>6856.78</td>
<td>6856.78</td>
<td>4799.75</td>
<td>3085.55</td>
<td>2057.04</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.13xlarge</td>
<td>52</td>
<td>384</td>
<td>21.6359</td>
<td>11142.27</td>
<td>11142.27</td>
<td>7799.59</td>
<td>5014.02</td>
<td>3342.68</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.large</td>
<td>2</td>
<td>4</td>
<td>0.495285</td>
<td>256.65</td>
<td>256.65</td>
<td>179.66</td>
<td>115.49</td>
<td>97.53</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.99057</td>
<td>513.3</td>
<td>513.3</td>
<td>359.31</td>
<td>230.99</td>
<td>153.99</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.98114</td>
<td>1026.61</td>
<td>1026.61</td>
<td>718.62</td>
<td>461.97</td>
<td>307.98</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.96228</td>
<td>2053.21</td>
<td>2053.21</td>
<td>1437.25</td>
<td>923.95</td>
<td>615.96</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.8xlarge</td>
<td>32</td>
<td>64</td>
<td>7.92456</td>
<td>4106.42</td>
<td>4106.42</td>
<td>2874.5</td>
<td>1847.89</td>
<td>1231.93</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.13xlarge</td>
<td>52</td>
<td>96</td>
<td>12.87741</td>
<td>6672.94</td>
<td>6672.94</td>
<td>4671.06</td>
<td>3002.82</td>
<td>2001.88</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.26xlarge</td>
<td>104</td>
<td>192</td>
<td>25.75482</td>
<td>13345.88</td>
<td>13345.88</td>
<td>9342.11</td>
<td>6005.65</td>
<td>4003.76</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c4g1.xlarge</td>
<td>4</td>
<td>30</td>
<td>11.88</td>
<td>5704</td>
<td>5418.8</td>
<td>4278</td>
<td>2566.8</td>
<td>1711.2</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.2xlarge</td>
<td>8</td>
<td>60</td>
<td>14.3</td>
<td>6868</td>
<td>6524.6</td>
<td>5151</td>
<td>3090.6</td>
<td>2060.4</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c4g1.2xlarge</td>
<td>8</td>
<td>60</td>
<td>23.76</td>
<td>11408</td>
<td>10837.6</td>
<td>8556</td>
<td>5133.6</td>
<td>3422.4</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.4xlarge</td>
<td>16</td>
<td>120</td>
<td>28.61</td>
<td>13737</td>
<td>13050.15</td>
<td>10302.75</td>
<td>6181.65</td>
<td>4121.1</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c28g1.7xlarge</td>
<td>28</td>
<td>112</td>
<td>20.59</td>
<td>9883</td>
<td>9388.85</td>
<td>7412.25</td>
<td>4447.35</td>
<td>2964.9</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.8xlarge</td>
<td>32</td>
<td>240</td>
<td>57.23</td>
<td>27474</td>
<td>26100.3</td>
<td>20605.5</td>
<td>12363.3</td>
<td>8242.2</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.14xlarge</td>
<td>54</td>
<td>480</td>
<td>114.47</td>
<td>54948</td>
<td>52200.6</td>
<td>41211</td>
<td>24726.6</td>
<td>16484.4</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c28g1.14xlarge</td>
<td>56</td>
<td>224</td>
<td>41.18</td>
<td>19766</td>
<td>18777.7</td>
<td>14824.5</td>
<td>8894.7</td>
<td>5929.8</td>
</tr>
<tr>
<td>计算型 ecs.c5.large</td>
<td>2</td>
<td>4</td>
<td>0.64</td>
<td>324</td>
<td>324</td>
<td>275.4</td>
<td>178.2</td>
<td>123.12</td>
</tr>
<tr>
<td>计算型 ecs.c5.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.29</td>
<td>649</td>
<td>649</td>
<td>551.65</td>
<td>356.95</td>
<td>246.62</td>
</tr>
<tr>
<td>计算型 ecs.c5.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.57</td>
<td>1298</td>
<td>1298</td>
<td>1103.3</td>
<td>713.9</td>
<td>493.24</td>
</tr>
<tr>
<td>计算型 ecs.c5.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.86</td>
<td>1946</td>
<td>1946</td>
<td>1654.1</td>
<td>1070.3</td>
<td>739.48</td>
</tr>
<tr>
<td>计算型 ecs.c5.4xlarge</td>
<td>16</td>
<td>32</td>
<td>5.14</td>
<td>2595</td>
<td>2595</td>
<td>2205.75</td>
<td>1427.25</td>
<td>986.1</td>
</tr>
<tr>
<td>计算型 ecs.c5.6xlarge</td>
<td>24</td>
<td>48</td>
<td>7.71</td>
<td>3893</td>
<td>3893</td>
<td>3309.05</td>
<td>2141.15</td>
<td>1479.34</td>
</tr>
<tr>
<td>计算型 ecs.c5.8xlarge</td>
<td>32</td>
<td>64</td>
<td>10.28</td>
<td>5190</td>
<td>5190</td>
<td>4411.5</td>
<td>2854.5</td>
<td>1972.2</td>
</tr>
<tr>
<td>计算型 ecs.c5.16xlarge</td>
<td>64</td>
<td>128</td>
<td>20.56</td>
<td>10381</td>
<td>10381</td>
<td>8823.85</td>
<td>5709.55</td>
<td>3944.78</td>
</tr>
<tr>
<td>通用型 ecs.g5.large</td>
<td>2</td>
<td>8</td>
<td>0.72</td>
<td>394</td>
<td>394</td>
<td>334.9</td>
<td>216.7</td>
<td>149.72</td>
</tr>
<tr>
<td>通用型 ecs.g5.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.43</td>
<td>788</td>
<td>788</td>
<td>669.8</td>
<td>433.4</td>
<td>299.44</td>
</tr>
<tr>
<td>通用型 ecs.g5.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.87</td>
<td>1576</td>
<td>1576</td>
<td>1339.6</td>
<td>866.8</td>
<td>598.88</td>
</tr>
<tr>
<td>通用型 ecs.g5.3xlarge</td>
<td>12</td>
<td>48</td>
<td>4.3</td>
<td>2364</td>
<td>2364</td>
<td>2009.4</td>
<td>1300.2</td>
<td>898.32</td>
</tr>
<tr>
<td>通用型 ecs.g5.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.74</td>
<td>3152</td>
<td>3152</td>
<td>2679.2</td>
<td>1733.6</td>
<td>1197.76</td>
</tr>
<tr>
<td>通用型 ecs.g5.6xlarge</td>
<td>24</td>
<td>96</td>
<td>8.6</td>
<td>4728</td>
<td>4728</td>
<td>4018.8</td>
<td>2600.4</td>
<td>1796.64</td>
</tr>
<tr>
<td>通用型 ecs.g5.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.47</td>
<td>6304</td>
<td>6304</td>
<td>5358.4</td>
<td>3467.2</td>
<td>2395.52</td>
</tr>
<tr>
<td>通用型 ecs.g5.16xlarge</td>
<td>64</td>
<td>256</td>
<td>22.94</td>
<td>12608</td>
<td>12608</td>
<td>10716.8</td>
<td>6934.4</td>
<td>4791.04</td>
</tr>
<tr>
<td>内存型 ecs.r5.large</td>
<td>2</td>
<td>16</td>
<td>0.901</td>
<td>415</td>
<td>415</td>
<td>352.75</td>
<td>228.25</td>
<td>157.7</td>
</tr>
<tr>
<td>内存型 ecs.r5.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.801</td>
<td>830</td>
<td>830</td>
<td>705.5</td>
<td>456.5</td>
<td>315.4</td>
</tr>
<tr>
<td>内存型 ecs.r5.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.601</td>
<td>1660</td>
<td>1660</td>
<td>1411</td>
<td>913</td>
<td>630.8</td>
</tr>
<tr>
<td>内存型 ecs.r5.3xlarge</td>
<td>12</td>
<td>96</td>
<td>5.401</td>
<td>2490</td>
<td>2490</td>
<td>2116.5</td>
<td>1369.5</td>
<td>946.2</td>
</tr>
<tr>
<td>内存型 ecs.r5.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.201</td>
<td>3320</td>
<td>3320</td>
<td>2822</td>
<td>1826</td>
<td>1261.6</td>
</tr>
<tr>
<td>内存型 ecs.r5.6xlarge</td>
<td>24</td>
<td>192</td>
<td>10.802</td>
<td>4980</td>
<td>4980</td>
<td>4233</td>
<td>2739</td>
<td>1892.4</td>
</tr>
<tr>
<td>内存型 ecs.r5.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.402</td>
<td>6640</td>
<td>6640</td>
<td>5644</td>
<td>3652</td>
<td>2523.2</td>
</tr>
<tr>
<td>内存型 ecs.r5.16xlarge</td>
<td>64</td>
<td>512</td>
<td>28.806</td>
<td>13281</td>
<td>13281</td>
<td>11288.85</td>
<td>7304.55</td>
<td>5046.78</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.large</td>
<td>2</td>
<td>4</td>
<td>0.77</td>
<td>389</td>
<td>369.55</td>
<td>291.75</td>
<td>175.05</td>
<td>116.7</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.54</td>
<td>779</td>
<td>740.05</td>
<td>584.25</td>
<td>350.55</td>
<td>233.7</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.2xlarge</td>
<td>8</td>
<td>16</td>
<td>3.08</td>
<td>1557</td>
<td>1479.15</td>
<td>1167.75</td>
<td>700.65</td>
<td>467.1</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.3xlarge</td>
<td>12</td>
<td>24</td>
<td>4.63</td>
<td>2336</td>
<td>2219.2</td>
<td>1752</td>
<td>1051.2</td>
<td>700.8</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.4xlarge</td>
<td>16</td>
<td>32</td>
<td>6.17</td>
<td>3114</td>
<td>2958.3</td>
<td>2335.5</td>
<td>1401.3</td>
<td>934.2</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.6xlarge</td>
<td>24</td>
<td>48</td>
<td>9.25</td>
<td>4671</td>
<td>4437.45</td>
<td>3503.25</td>
<td>2101.95</td>
<td>1401.3</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.8xlarge</td>
<td>32</td>
<td>64</td>
<td>12.34</td>
<td>6228</td>
<td>5916.6</td>
<td>4671</td>
<td>2802.6</td>
<td>1868.4</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.large</td>
<td>2</td>
<td>8</td>
<td>0.88</td>
<td>438.64</td>
<td>416.71</td>
<td>328.98</td>
<td>197.39</td>
<td>131.59</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.76</td>
<td>877</td>
<td>833.15</td>
<td>657.75</td>
<td>394.65</td>
<td>263.1</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.52</td>
<td>1754</td>
<td>1666.3</td>
<td>1315.5</td>
<td>789.3</td>
<td>526.2</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.3xlarge</td>
<td>12</td>
<td>48</td>
<td>5.28</td>
<td>2631.53</td>
<td>2499.95</td>
<td>1973.65</td>
<td>1184.19</td>
<td>789.46</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.4xlarge</td>
<td>16</td>
<td>64</td>
<td>7.03</td>
<td>3508.66</td>
<td>3333.23</td>
<td>2631.49</td>
<td>1578.9</td>
<td>1052.6</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.6xlarge</td>
<td>24</td>
<td>96</td>
<td>10.55</td>
<td>5262.99</td>
<td>4999.84</td>
<td>3947.24</td>
<td>2368.35</td>
<td>1578.9</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.8xlarge</td>
<td>32</td>
<td>128</td>
<td>14.07</td>
<td>7017</td>
<td>6666.15</td>
<td>5262.75</td>
<td>3157.65</td>
<td>2105.1</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.14xlarge</td>
<td>56</td>
<td>160</td>
<td>24.62</td>
<td>12280</td>
<td>11666</td>
<td>9210</td>
<td>5526</td>
<td>3684</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc2m1.nano</td>
<td>1</td>
<td>0.5</td>
<td>0.0465</td>
<td>23</td>
<td>21.85</td>
<td>17.25</td>
<td>10.35</td>
<td>6.9</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m1.small</td>
<td>1</td>
<td>1</td>
<td>0.0744</td>
<td>43</td>
<td>40.85</td>
<td>32.25</td>
<td>19.35</td>
<td>12.9</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m2.small</td>
<td>1</td>
<td>2</td>
<td>0.1302</td>
<td>70</td>
<td>66.5</td>
<td>52.5</td>
<td>31.5</td>
<td>21</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.2046</td>
<td>115</td>
<td>109.25</td>
<td>86.25</td>
<td>51.75</td>
<td>34.5</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.2883</td>
<td>159</td>
<td>151.05</td>
<td>119.25</td>
<td>71.55</td>
<td>47.7</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.4371</td>
<td>246</td>
<td>233.7</td>
<td>184.5</td>
<td>110.7</td>
<td>73.8</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.2418</td>
<td>139</td>
<td>132.05</td>
<td>104.25</td>
<td>62.55</td>
<td>41.7</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.3627</td>
<td>207</td>
<td>196.65</td>
<td>155.25</td>
<td>93.15</td>
<td>62.1</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.xlarge</td>
<td>4</td>
<td>4</td>
<td>0.4092</td>
<td>229</td>
<td>217.55</td>
<td>171.75</td>
<td>103.05</td>
<td>68.7</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.5673</td>
<td>317</td>
<td>301.15</td>
<td>237.75</td>
<td>142.65</td>
<td>95.1</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.8835</td>
<td>492</td>
<td>467.4</td>
<td>369</td>
<td>221.4</td>
<td>147.6</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.2xlarge</td>
<td>8</td>
<td>8</td>
<td>0.8184</td>
<td>457</td>
<td>434.15</td>
<td>342.75</td>
<td>205.65</td>
<td>137.1</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.1346</td>
<td>634</td>
<td>602.3</td>
<td>475.5</td>
<td>285.3</td>
<td>190.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.7577</td>
<td>984</td>
<td>934.8</td>
<td>738</td>
<td>442.8</td>
<td>295.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.4xlarge</td>
<td>16</td>
<td>16</td>
<td>1.6368</td>
<td>914</td>
<td>868.3</td>
<td>685.5</td>
<td>411.3</td>
<td>274.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.4xlarge</td>
<td>16</td>
<td>32</td>
<td>2.2692</td>
<td>1268</td>
<td>1204.6</td>
<td>951</td>
<td>570.6</td>
<td>380.4</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.large</td>
<td>2</td>
<td>2</td>
<td>0.62</td>
<td>308</td>
<td>308</td>
<td>261.8</td>
<td>169.4</td>
<td>117.04</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.xlarge</td>
<td>4</td>
<td>4</td>
<td>1.23</td>
<td>616</td>
<td>616</td>
<td>523.6</td>
<td>338.8</td>
<td>234.08</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.2xlarge</td>
<td>8</td>
<td>8</td>
<td>2.46</td>
<td>1233</td>
<td>1233</td>
<td>1048.05</td>
<td>678.15</td>
<td>468.54</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.3xlarge</td>
<td>12</td>
<td>12</td>
<td>3.69</td>
<td>1849</td>
<td>1849</td>
<td>1571.65</td>
<td>1016.95</td>
<td>702.62</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.4xlarge</td>
<td>16</td>
<td>16</td>
<td>4.92</td>
<td>2465</td>
<td>2465</td>
<td>2095.25</td>
<td>1355.75</td>
<td>936.7</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.6xlarge</td>
<td>24</td>
<td>24</td>
<td>7.39</td>
<td>3698</td>
<td>3698</td>
<td>3143.3</td>
<td>2033.9</td>
<td>1405.24</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.8xlarge</td>
<td>32</td>
<td>32</td>
<td>9.85</td>
<td>4931</td>
<td>4931</td>
<td>4191.35</td>
<td>2712.05</td>
<td>1873.78</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.16xlarge</td>
<td>64</td>
<td>64</td>
<td>19.7</td>
<td>9861</td>
<td>9861</td>
<td>8381.85</td>
<td>5423.55</td>
<td>3747.18</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.large</td>
<td>2</td>
<td>8</td>
<td>0.578036</td>
<td>495.93</td>
<td>495.93</td>
<td>347.15</td>
<td>223.17</td>
<td>148.78</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.156073</td>
<td>991.85</td>
<td>991.85</td>
<td>694.3</td>
<td>446.33</td>
<td>297.56</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.67659</td>
<td>1983.7</td>
<td>1983.7</td>
<td>1388.59</td>
<td>892.66</td>
<td>595.11</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>7.35318</td>
<td>3967.4</td>
<td>3967.4</td>
<td>2777.18</td>
<td>1785.33</td>
<td>1190.22</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>14.70636</td>
<td>7934.8</td>
<td>7934.8</td>
<td>5554.36</td>
<td>3570.66</td>
<td>2380.44</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.16xlarge</td>
<td>64</td>
<td>256</td>
<td>29.41272</td>
<td>15869.6</td>
<td>15869.6</td>
<td>11108.72</td>
<td>7141.32</td>
<td>4760.88</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.18xlarge</td>
<td>72</td>
<td>288</td>
<td>33.08931</td>
<td>17853.3</td>
<td>17853.3</td>
<td>12497.31</td>
<td>8033.99</td>
<td>5355.99</td>
</tr>
<tr>
<td>通用型 ecs.n4.small</td>
<td>1</td>
<td>2</td>
<td>0.213</td>
<td>113.15</td>
<td>113.15</td>
<td>96.18</td>
<td>56.58</td>
<td>56.58</td>
</tr>
<tr>
<td>通用型 ecs.n4.large</td>
<td>2</td>
<td>4</td>
<td>0.425</td>
<td>226.31</td>
<td>226.31</td>
<td>192.36</td>
<td>113.16</td>
<td>113.16</td>
</tr>
<tr>
<td>通用型 ecs.n4.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.475</td>
<td>734.77</td>
<td>734.77</td>
<td>624.55</td>
<td>367.38</td>
<td>367.38</td>
</tr>
<tr>
<td>通用型 ecs.n4.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.948</td>
<td>1469.55</td>
<td>1469.55</td>
<td>1249.12</td>
<td>734.78</td>
<td>734.77</td>
</tr>
<tr>
<td>通用型 ecs.n4.4xlarge</td>
<td>16</td>
<td>32</td>
<td>5.896</td>
<td>2939.11</td>
<td>2939.11</td>
<td>2498.24</td>
<td>1469.56</td>
<td>1469.56</td>
</tr>
<tr>
<td>通用型 ecs.n4.8xlarge</td>
<td>32</td>
<td>64</td>
<td>11.783</td>
<td>5882.54</td>
<td>5882.54</td>
<td>5000.16</td>
<td>2941.27</td>
<td>2941.27</td>
</tr>
<tr>
<td>通用型 ecs.mn4.small</td>
<td>1</td>
<td>4</td>
<td>0.404</td>
<td>205.53</td>
<td>205.53</td>
<td>174.7</td>
<td>102.77</td>
<td>102.77</td>
</tr>
<tr>
<td>通用型 ecs.mn4.large</td>
<td>2</td>
<td>8</td>
<td>0.807</td>
<td>411.07</td>
<td>411.07</td>
<td>349.41</td>
<td>205.53</td>
<td>205.53</td>
</tr>
<tr>
<td>通用型 ecs.mn4.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.614</td>
<td>821.68</td>
<td>821.68</td>
<td>698.43</td>
<td>410.84</td>
<td>410.84</td>
</tr>
<tr>
<td>通用型 ecs.mn4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.228</td>
<td>1643.43</td>
<td>1643.43</td>
<td>1396.92</td>
<td>821.72</td>
<td>821.72</td>
</tr>
<tr>
<td>通用型 ecs.mn4.4xlarge</td>
<td>16</td>
<td>64</td>
<td>6.455</td>
<td>3286.81</td>
<td>3286.81</td>
<td>2793.79</td>
<td>1643.4</td>
<td>1643.4</td>
</tr>
<tr>
<td>通用型 ecs.mn4.8xlarge</td>
<td>32</td>
<td>128</td>
<td>12.91</td>
<td>6573.62</td>
<td>6573.62</td>
<td>5587.58</td>
<td>3286.81</td>
<td>3286.81</td>
</tr>
<tr>
<td>通用型 ecs.xn4.small</td>
<td>1</td>
<td>1</td>
<td>0.105</td>
<td>56.42</td>
<td>56.42</td>
<td>47.96</td>
<td>28.21</td>
<td>28.21</td>
</tr>
<tr>
<td>经济型 ecs.e4.small</td>
<td>1</td>
<td>8</td>
<td>0.511</td>
<td>235.08</td>
<td>235.08</td>
<td>199.82</td>
<td>117.54</td>
<td>117.54</td>
</tr>
<tr>
<td>计算型 ecs.cm4.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.88</td>
<td>985.99</td>
<td>936.69</td>
<td>739.49</td>
<td>443.7</td>
<td>295.8</td>
</tr>
<tr>
<td>计算型 ecs.cm4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.83</td>
<td>1972.06</td>
<td>1873.46</td>
<td>1479.05</td>
<td>887.43</td>
<td>591.62</td>
</tr>
<tr>
<td>计算型 ecs.cm4.3xlarge</td>
<td>12</td>
<td>48</td>
<td>5.64</td>
<td>2957.97</td>
<td>2810.07</td>
<td>2218.48</td>
<td>1331.09</td>
<td>887.39</td>
</tr>
<tr>
<td>计算型 ecs.cm4.4xlarge</td>
<td>16</td>
<td>64</td>
<td>7.73</td>
<td>3944.12</td>
<td>3746.91</td>
<td>2958.09</td>
<td>1774.85</td>
<td>1183.24</td>
</tr>
<tr>
<td>计算型 ecs.cm4.6xlarge</td>
<td>24</td>
<td>96</td>
<td>11.56</td>
<td>5916.19</td>
<td>5620.38</td>
<td>4437.14</td>
<td>2662.29</td>
<td>1774.86</td>
</tr>
<tr>
<td>计算型 ecs.ce4.xlarge</td>
<td>4</td>
<td>32</td>
<td>2.44</td>
<td>1129</td>
<td>1072.55</td>
<td>846.75</td>
<td>508.05</td>
<td>338.7</td>
</tr>
<tr>
<td>计算型 ecs.ce4.2xlarge</td>
<td>8</td>
<td>64</td>
<td>4.888</td>
<td>2258</td>
<td>2145.1</td>
<td>1693.5</td>
<td>1016.1</td>
<td>677.4</td>
</tr>
<tr>
<td>计算型 ecs.c4.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.67</td>
<td>863.74</td>
<td>820.55</td>
<td>647.8</td>
<td>388.68</td>
<td>259.12</td>
</tr>
<tr>
<td>计算型 ecs.c4.2xlarge</td>
<td>8</td>
<td>16</td>
<td>3.34</td>
<td>1727.49</td>
<td>1641.12</td>
<td>1295.62</td>
<td>777.37</td>
<td>518.25</td>
</tr>
<tr>
<td>计算型 ecs.c4.3xlarge</td>
<td>12</td>
<td>24</td>
<td>5.013</td>
<td>2591.22</td>
<td>2461.66</td>
<td>1943.41</td>
<td>1166.05</td>
<td>777.37</td>
</tr>
<tr>
<td>计算型 ecs.c4.4xlarge</td>
<td>16</td>
<td>32</td>
<td>6.69</td>
<td>3454.99</td>
<td>3282.24</td>
<td>2591.24</td>
<td>1554.75</td>
<td>1036.5</td>
</tr>
<tr>
<td>ecs.sn2ne.large</td>
<td>2</td>
<td>8</td>
<td>0.848</td>
<td>431.62</td>
<td>431.62</td>
<td>366.88</td>
<td>237.39</td>
<td>164.02</td>
</tr>
<tr>
<td>ecs.sn2ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.695</td>
<td>862.76</td>
<td>862.76</td>
<td>733.35</td>
<td>474.52</td>
<td>327.85</td>
</tr>
<tr>
<td>ecs.sn2ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.39</td>
<td>1725.6</td>
<td>1725.6</td>
<td>1466.76</td>
<td>949.08</td>
<td>655.73</td>
</tr>
<tr>
<td>ecs.sn2ne.3xlarge</td>
<td>12</td>
<td>48</td>
<td>5.088</td>
<td>2589.72</td>
<td>2589.72</td>
<td>2201.26</td>
<td>1424.35</td>
<td>984.09</td>
</tr>
<tr>
<td>ecs.sn2ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>6.778</td>
<td>3451.15</td>
<td>3451.15</td>
<td>2933.48</td>
<td>1898.13</td>
<td>1311.44</td>
</tr>
<tr>
<td>ecs.sn2ne.6xlarge</td>
<td>24</td>
<td>96</td>
<td>10.176</td>
<td>5179.44</td>
<td>5179.44</td>
<td>4402.52</td>
<td>2848.69</td>
<td>1968.19</td>
</tr>
<tr>
<td>ecs.sn2ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>13.556</td>
<td>6902.3</td>
<td>6902.3</td>
<td>5866.96</td>
<td>3796.27</td>
<td>2622.87</td>
</tr>
<tr>
<td>ecs.sn2ne.14xlarge</td>
<td>56</td>
<td>224</td>
<td>23.722</td>
<td>12085.59</td>
<td>12085.59</td>
<td>10272.75</td>
<td>6647.07</td>
<td>4592.52</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.8414</td>
<td>986</td>
<td>986</td>
<td>690.2</td>
<td>443.7</td>
<td>295.8</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.6735</td>
<td>1971</td>
<td>1971</td>
<td>1379.7</td>
<td>886.95</td>
<td>591.3</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.347</td>
<td>3942</td>
<td>3942</td>
<td>2759.4</td>
<td>1773.9</td>
<td>1182.6</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.694</td>
<td>7883</td>
<td>7883</td>
<td>5518.1</td>
<td>3547.35</td>
<td>2364.9</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.16xlarge</td>
<td>64</td>
<td>512</td>
<td>29.388</td>
<td>15766</td>
<td>15766</td>
<td>11036.2</td>
<td>7094.7</td>
<td>4729.8</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.large</td>
<td>2</td>
<td>16</td>
<td>1.021</td>
<td>470.17</td>
<td>470.17</td>
<td>399.64</td>
<td>235.08</td>
<td>235.09</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.xlarge</td>
<td>4</td>
<td>32</td>
<td>2.042</td>
<td>940.89</td>
<td>940.89</td>
<td>799.76</td>
<td>470.44</td>
<td>470.44</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.2xlarge</td>
<td>8</td>
<td>64</td>
<td>4.09</td>
<td>1881.72</td>
<td>1881.72</td>
<td>1599.46</td>
<td>940.86</td>
<td>940.86</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.4xlarge</td>
<td>16</td>
<td>128</td>
<td>8.179</td>
<td>3763.52</td>
<td>3763.52</td>
<td>3198.99</td>
<td>1881.76</td>
<td>1881.76</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.8xlarge</td>
<td>32</td>
<td>256</td>
<td>16.351</td>
<td>7527.04</td>
<td>7527.04</td>
<td>6397.98</td>
<td>3763.52</td>
<td>3763.52</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.14xlarge</td>
<td>56</td>
<td>480</td>
<td>30.109</td>
<td>14079.08</td>
<td>14079.08</td>
<td>11967.22</td>
<td>7039.54</td>
<td>7039.54</td>
</tr>
<tr>
<td>大数据型 ecs.d1.2xlarge</td>
<td>8</td>
<td>32</td>
<td>5.41</td>
<td>2598</td>
<td>2468.1</td>
<td>1948.5</td>
<td>1169.1</td>
<td>779.4</td>
</tr>
<tr>
<td>大数据型 ecs.d1.3xlarge</td>
<td>12</td>
<td>48</td>
<td>8.115</td>
<td>3897</td>
<td>3702.15</td>
<td>2922.75</td>
<td>1753.65</td>
<td>1169.1</td>
</tr>
<tr>
<td>大数据型 ecs.d1.4xlarge</td>
<td>16</td>
<td>64</td>
<td>10.82</td>
<td>5197</td>
<td>4937.15</td>
<td>3897.75</td>
<td>2338.65</td>
<td>1559.1</td>
</tr>
<tr>
<td>大数据型 ecs.d1.6xlarge</td>
<td>24</td>
<td>96</td>
<td>16.23</td>
<td>7795</td>
<td>7405.25</td>
<td>5846.25</td>
<td>3507.75</td>
<td>2338.5</td>
</tr>
<tr>
<td>大数据型 ecs.d1.8xlarge</td>
<td>32</td>
<td>128</td>
<td>21.64</td>
<td>10394</td>
<td>9874.3</td>
<td>7795.5</td>
<td>4677.3</td>
<td>3118.2</td>
</tr>
<tr>
<td>大数据型 ecs.d1-c8d3.8xlarge</td>
<td>32</td>
<td>128</td>
<td>20.78</td>
<td>9979</td>
<td>9480.05</td>
<td>7484.25</td>
<td>4490.55</td>
<td>2993.7</td>
</tr>
<tr>
<td>大数据型 ecs.d1.14xlarge</td>
<td>56</td>
<td>224</td>
<td>37.89</td>
<td>18190</td>
<td>17280.5</td>
<td>13642.5</td>
<td>8185.5</td>
<td>5457</td>
</tr>
<tr>
<td>大数据型 ecs.d1-c14d3.14xlarge</td>
<td>56</td>
<td>160</td>
<td>31.52</td>
<td>15134</td>
<td>14377.3</td>
<td>11350.5</td>
<td>6810.3</td>
<td>4540.2</td>
</tr>
<tr>
<td>ecs.sn1ne.large</td>
<td>2</td>
<td>4</td>
<td>0.772</td>
<td>385.74</td>
<td>385.74</td>
<td>327.88</td>
<td>212.16</td>
<td>146.58</td>
</tr>
<tr>
<td>ecs.sn1ne.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.549</td>
<td>771.5</td>
<td>771.5</td>
<td>655.77</td>
<td>424.33</td>
<td>293.17</td>
</tr>
<tr>
<td>ecs.sn1ne.2xlarge</td>
<td>8</td>
<td>16</td>
<td>3.097</td>
<td>1543.02</td>
<td>1543.02</td>
<td>1311.57</td>
<td>848.66</td>
<td>586.35</td>
</tr>
<tr>
<td>ecs.sn1ne.3xlarge</td>
<td>12</td>
<td>24</td>
<td>4.632</td>
<td>2314.44</td>
<td>2314.44</td>
<td>1967.27</td>
<td>1272.94</td>
<td>879.49</td>
</tr>
<tr>
<td>ecs.sn1ne.4xlarge</td>
<td>16</td>
<td>32</td>
<td>6.2</td>
<td>3086.06</td>
<td>3086.06</td>
<td>2623.15</td>
<td>1697.33</td>
<td>1172.7</td>
</tr>
<tr>
<td>ecs.sn1ne.6xlarge</td>
<td>24</td>
<td>48</td>
<td>9.264</td>
<td>4628.88</td>
<td>4628.88</td>
<td>3934.55</td>
<td>2545.88</td>
<td>1758.97</td>
</tr>
<tr>
<td>ecs.sn1ne.8xlarge</td>
<td>32</td>
<td>64</td>
<td>12.392</td>
<td>6176.66</td>
<td>6176.66</td>
<td>5250.16</td>
<td>3397.16</td>
<td>2347.13</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.large</td>
<td>2</td>
<td>16</td>
<td>1.073</td>
<td>493.67</td>
<td>493.67</td>
<td>419.62</td>
<td>271.52</td>
<td>187.59</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>2.145</td>
<td>987.93</td>
<td>987.93</td>
<td>839.74</td>
<td>543.36</td>
<td>375.41</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>4.295</td>
<td>1975.8</td>
<td>1975.8</td>
<td>1679.43</td>
<td>1086.69</td>
<td>750.8</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.3xlarge</td>
<td>12</td>
<td>96</td>
<td>6.438</td>
<td>2962.02</td>
<td>2962.02</td>
<td>2517.72</td>
<td>1629.11</td>
<td>1125.57</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>8.588</td>
<td>3951.69</td>
<td>3951.69</td>
<td>3358.94</td>
<td>2173.43</td>
<td>1501.64</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.6xlarge</td>
<td>24</td>
<td>192</td>
<td>12.876</td>
<td>5924.04</td>
<td>5924.04</td>
<td>5035.43</td>
<td>3258.22</td>
<td>2251.14</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.8xlarge</td>
<td>32</td>
<td>256</td>
<td>17.169</td>
<td>7903.39</td>
<td>7903.39</td>
<td>6717.88</td>
<td>4346.86</td>
<td>3003.29</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.14xlarge</td>
<td>56</td>
<td>480</td>
<td>31.615</td>
<td>14783.03</td>
<td>14783.03</td>
<td>12565.58</td>
<td>8130.67</td>
<td>5617.55</td>
</tr>
</tbody>
</table>
<h2>三、阿里云服务器便宜购买技巧（比活动价格更便宜）</h2>
了解完阿里云服务器海外地域收费标准之后，我们再来说说如何购买阿里云服务器能比活动价格还低，2024年阿里云活动中的云服务器有多种配置和实例规格的云服务器可选，其中轻量应用服务器2核2G3M最低61元/1年，云服务器2核2G3M最低仅需99元/1年，云服务器2核4G5M最低仅需199元/1年。在阿里云活动中购买云服务器时，很多新用户会问，阿里云活动中的云服务器价格还能便宜吗？答案是肯定的，现在我们可以通过领取新用户满减优惠券，在购买阿里云活动中的云服务器时享受更多优惠，实际购买价格比活动价格更便宜。
第一步：领取新用户满减优惠券或代金券
首先，我们需要领取新用户满减优惠券或代金券，阿里云官方会不定期为个人和企业新用户推出各种满减优惠券或者代金券，您可以从以下两个活动中领取优惠券：
[*]阿里云活动中心的“领券中心”。官网地址为：https://www.aliyun.com/activity
[*]阿里云官方云小站平台内的“云产品通用代金券”。官网地址为：https://www.aliyun.com/minisite/goods
</ol>
https://upload-images.jianshu.io/upload_images/19316870-bc2616e80eea80f1.png
<div class="image-caption">云小站代金券图.png
我们随便进入一个活动领取优惠券即可。为了方便起见，小编建议您直接通过云小站平台领取优惠券，因为领取后可以直接在活动内购买云服务器使用。
第二步：比较活动内云服务器不同地域的活动价格
在相同实例规格和配置的情况下，不同地域的阿里云服务器活动价格是不一样的，我们在购买时候可以先比较一下不同地域之间的云服务器活动价格，然后选择价格更低的，这样也能达到更便宜购买的目的，例如同样是计算型c7实例2核4G1M带宽配置，目前阿里云活动内显示的价格是2129.41元1年，这个价格只是北京、杭州、上海、深圳等地域的价格，如果我们选择乌兰察布、河源等地域，活动价格则是1875.79元1年，价格要便宜253.62元，如下图所示：
https://upload-images.jianshu.io/upload_images/19316870-875cd4c8e9a04623.png
<div class="image-caption">1875.79图.png
第三步：下单购买并使用满减优惠券
当我们领取完满减优惠券并选择好云服务器配置之后，可以看下这款云服务器是否支持叠加使用优惠券，如下图所示：
https://upload-images.jianshu.io/upload_images/19316870-f5b615f8a1b6ae21.png
<div class="image-caption">可叠加使用优惠券图.png
最后，在支付云服务器订单的时候，系统会自动显示此订单可使用的全部满减优惠券金额，如下图所示：
https://upload-images.jianshu.io/upload_images/19316870-3aac5ead51ec0ef6.png
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