阿里云服务器国外欧洲与美洲地域云服务器最新价格表

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用户在购买阿里云服务器之前，最为关心的就是阿里云ECS云服务器的价格，阿里云服务器地域分为国内和国外，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，下面是阿里云国外欧洲与美洲地域云服务器最新价格表。
<h5>国外欧洲与美洲地域有哪些？</h5>
阿里云服务器国外欧洲与美洲地域主要包含美国(硅谷)、美国(弗吉尼亚)、德国(法兰克福)、英国(伦敦)这四个地域。






<div class="image-caption">国外云服务器地域图.png

<h5>阿里云服务器国外欧洲与美洲地域活动报价表</h5>

小编先来说下阿里云服务器国外欧洲与美洲地域活动报价情况，目前阿里云全球云服务器精选特惠活动推出【新用户专享】海外云服务器优惠，活动详情如下图所示：







用户可在活动内买到计算型c6实例2核4G、4核8G、8核16G配置，通用型g6实例2核8G、4核16G、8核32G配置，内存型r6实例2核16G、4核32G、8核64G配置的海外云服务器，折扣为3个月付1折，年付3.6折，地域包含五个国外地域可选，其中就包含美国(弗吉尼亚)、德国(法兰克福)这两个国外欧洲与美洲地域，具体活动报价表如下：
<table>
<thead>
<tr>
<th>云服务器实例</th>
<th>配置</th>
<th>活动价格</th>
</tr>
</thead>
<tbody>
<tr>
<td>计算型c6</td>
<td>2核4G</td>
<td>117.25元/3月起1688.47元/年起</td>
</tr>
<tr>
<td>计算型c6</td>
<td>4核8G</td>
<td>216.39元/3月起3116.02元/年起</td>
</tr>
<tr>
<td>计算型c6</td>
<td>8核16G</td>
<td>414.66元/3月起5971.10元/年起</td>
</tr>
<tr>
<td>通用型g6</td>
<td>2核8G</td>
<td>143.88元/3月起2071.87元/年起</td>
</tr>
<tr>
<td>通用型g6</td>
<td>4核16G</td>
<td>269.64元/3月起3882.82元/年起</td>
</tr>
<tr>
<td>通用型g6</td>
<td>8核32G</td>
<td>521.16元/3月起7504.70元/年起</td>
</tr>
<tr>
<td>内存型r6</td>
<td>2核16G</td>
<td>173.47元/3月起2497.95元/年起</td>
</tr>
<tr>
<td>内存型r6</td>
<td>4核32G</td>
<td>328.82元/3月起4734.98元/年起</td>
</tr>
<tr>
<td>内存型r6</td>
<td>8核64G</td>
<td>639.52元/3月起9209.03元/年起</td>
</tr>
</tbody>
</table>
<h5>阿里云服务器国外欧洲与美洲地域云服务器收费标准</h5>
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(弗吉尼亚)地域为例为大家展示阿里云服务器国外欧洲与美洲地域云服务器收费标准，另外，阿里云在官方云小站有免费的代金券可以领取，在实际购买过程中，代金券是一种长期且有效的节约购买成本的优惠券。
<table>
<thead>
<tr>
<th>实例规格</th>
<th>vCPU</th>
<th>内存(GB)</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>通用型 ecs.g6.large</td>
<td>2</td>
<td>8</td>
<td>0.65</td>
<td>300.85</td>
<td>300.85</td>
<td>255.72</td>
<td>165.47</td>
<td>114.32</td>
</tr>
<tr>
<td>通用型 ecs.g6.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.3</td>
<td>601.7</td>
<td>601.7</td>
<td>511.44</td>
<td>330.94</td>
<td>228.65</td>
</tr>
<tr>
<td>通用型 ecs.g6.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.6</td>
<td>1203.4</td>
<td>1203.4</td>
<td>1022.89</td>
<td>661.87</td>
<td>457.29</td>
</tr>
<tr>
<td>通用型 ecs.g6.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.9</td>
<td>1805.1</td>
<td>1805.1</td>
<td>1534.34</td>
<td>992.81</td>
<td>685.94</td>
</tr>
<tr>
<td>通用型 ecs.g6.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.2</td>
<td>2406.8</td>
<td>2406.8</td>
<td>2045.78</td>
<td>1323.74</td>
<td>914.58</td>
</tr>
<tr>
<td>通用型 ecs.g6.6xlarge</td>
<td>24</td>
<td>96</td>
<td>7.8</td>
<td>3610.2</td>
<td>3610.2</td>
<td>3068.67</td>
<td>1985.61</td>
<td>1371.88</td>
</tr>
<tr>
<td>通用型 ecs.g6.8xlarge</td>
<td>32</td>
<td>128</td>
<td>10.4</td>
<td>4813.6</td>
<td>4813.6</td>
<td>4091.56</td>
<td>2647.48</td>
<td>1829.17</td>
</tr>
<tr>
<td>通用型 ecs.g6.13xlarge</td>
<td>52</td>
<td>192</td>
<td>16.9</td>
<td>7822.1</td>
<td>7822.1</td>
<td>6648.78</td>
<td>4302.15</td>
<td>2972.4</td>
</tr>
<tr>
<td>通用型 ecs.g6.26xlarge</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>0.715</td>
<td>330.94</td>
<td>330.94</td>
<td>281.3</td>
<td>182.01</td>
<td>125.76</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.43</td>
<td>661.87</td>
<td>661.87</td>
<td>562.59</td>
<td>364.03</td>
<td>251.51</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.86</td>
<td>1323.74</td>
<td>1323.74</td>
<td>1125.18</td>
<td>728.06</td>
<td>503.02</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.72</td>
<td>2647.48</td>
<td>2647.48</td>
<td>2250.36</td>
<td>1456.11</td>
<td>1006.04</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.44</td>
<td>5294.96</td>
<td>5294.96</td>
<td>4500.72</td>
<td>2912.23</td>
<td>2012.08</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.13xlarge</td>
<td>52</td>
<td>192</td>
<td>18.59</td>
<td>8604.31</td>
<td>8604.31</td>
<td>7313.66</td>
<td>4732.37</td>
<td>3269.64</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c8g1.2xlarge</td>
<td>8</td>
<td>30</td>
<td>15.144184</td>
<td>7269.21</td>
<td>7269.21</td>
<td>6178.83</td>
<td>3998.06</td>
<td>2762.3</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c16g1.4xlarge</td>
<td>16</td>
<td>60</td>
<td>16.035018</td>
<td>7696.81</td>
<td>7696.81</td>
<td>6542.29</td>
<td>4233.24</td>
<td>2924.79</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c32g1.8xlarge</td>
<td>32</td>
<td>188</td>
<td>17.816687</td>
<td>8552.01</td>
<td>8552.01</td>
<td>7269.21</td>
<td>4703.61</td>
<td>3249.76</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c32g1.16xlarge</td>
<td>64</td>
<td>376</td>
<td>35.633375</td>
<td>17104.02</td>
<td>17104.02</td>
<td>14538.42</td>
<td>9407.21</td>
<td>6499.53</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c32g1.32xlarge</td>
<td>128</td>
<td>752</td>
<td>71.26675</td>
<td>34208.04</td>
<td>34208.04</td>
<td>29076.83</td>
<td>18814.42</td>
<td>12999.06</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c2m1.large</td>
<td>2</td>
<td>1</td>
<td>0.07</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>0.13</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>0.26</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>0.51</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>1</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>2</td>
<td>914.39</td>
<td>914.39</td>
<td>777.23</td>
<td>502.91</td>
<td>347.47</td>
</tr>
<tr>
<td>计算型 ecs.c6.large</td>
<td>2</td>
<td>4</td>
<td>0.53</td>
<td>244.43</td>
<td>244.43</td>
<td>207.77</td>
<td>134.44</td>
<td>92.88</td>
</tr>
<tr>
<td>计算型 ecs.c6.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.06</td>
<td>488.86</td>
<td>488.86</td>
<td>415.53</td>
<td>268.87</td>
<td>185.77</td>
</tr>
<tr>
<td>计算型 ecs.c6.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.12</td>
<td>977.72</td>
<td>977.72</td>
<td>831.06</td>
<td>537.75</td>
<td>371.53</td>
</tr>
<tr>
<td>计算型 ecs.c6.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.18</td>
<td>1466.58</td>
<td>1466.58</td>
<td>1246.59</td>
<td>806.62</td>
<td>557.3</td>
</tr>
<tr>
<td>计算型 ecs.c6.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.24</td>
<td>1955.44</td>
<td>1955.44</td>
<td>1662.12</td>
<td>1075.49</td>
<td>743.07</td>
</tr>
<tr>
<td>计算型 ecs.c6.6xlarge</td>
<td>24</td>
<td>48</td>
<td>6.36</td>
<td>2933.16</td>
<td>2933.16</td>
<td>2493.19</td>
<td>1613.24</td>
<td>1114.6</td>
</tr>
<tr>
<td>计算型 ecs.c6.8xlarge</td>
<td>32</td>
<td>64</td>
<td>8.48</td>
<td>3910.88</td>
<td>3910.88</td>
<td>3324.25</td>
<td>2150.98</td>
<td>1486.13</td>
</tr>
<tr>
<td>计算型 ecs.c6.13xlarge</td>
<td>52</td>
<td>96</td>
<td>13.78</td>
<td>6355.18</td>
<td>6355.18</td>
<td>5401.9</td>
<td>3495.35</td>
<td>2414.97</td>
</tr>
<tr>
<td>计算型 ecs.c6.26xlarge</td>
<td>104</td>
<td>192</td>
<td>27.56</td>
<td>12710.36</td>
<td>12710.36</td>
<td>10803.81</td>
<td>6990.7</td>
<td>4829.94</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.large</td>
<td>2</td>
<td>4</td>
<td>0.5565</td>
<td>256.65</td>
<td>256.65</td>
<td>218.15</td>
<td>141.16</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>1.113</td>
<td>513.3</td>
<td>513.3</td>
<td>436.31</td>
<td>282.32</td>
<td>195.06</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.226</td>
<td>1026.61</td>
<td>1026.61</td>
<td>872.61</td>
<td>564.63</td>
<td>390.11</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.452</td>
<td>2053.21</td>
<td>2053.21</td>
<td>1745.23</td>
<td>1129.27</td>
<td>780.22</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.8xlarge</td>
<td>32</td>
<td>64</td>
<td>8.904</td>
<td>4106.42</td>
<td>4106.42</td>
<td>3490.46</td>
<td>2258.53</td>
<td>1560.44</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.13xlarge</td>
<td>52</td>
<td>96</td>
<td>14.469</td>
<td>6672.94</td>
<td>6672.94</td>
<td>5672</td>
<td>3670.12</td>
<td>2535.72</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.26xlarge</td>
<td>104</td>
<td>192</td>
<td>28.938</td>
<td>13345.88</td>
<td>13345.88</td>
<td>11344</td>
<td>7340.23</td>
<td>5071.43</td>
</tr>
<tr>
<td>内存型 ecs.r6.large</td>
<td>2</td>
<td>16</td>
<td>0.85</td>
<td>389.59</td>
<td>389.59</td>
<td>331.15</td>
<td>214.27</td>
<td>148.04</td>
</tr>
<tr>
<td>内存型 ecs.r6.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.7</td>
<td>779.18</td>
<td>779.18</td>
<td>662.3</td>
<td>428.55</td>
<td>296.09</td>
</tr>
<tr>
<td>内存型 ecs.r6.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.4</td>
<td>1558.36</td>
<td>1558.36</td>
<td>1324.61</td>
<td>857.1</td>
<td>592.18</td>
</tr>
<tr>
<td>内存型 ecs.r6.3xlarge</td>
<td>12</td>
<td>96</td>
<td>5.1</td>
<td>2337.54</td>
<td>2337.54</td>
<td>1986.91</td>
<td>1285.65</td>
<td>888.27</td>
</tr>
<tr>
<td>内存型 ecs.r6.4xlarge</td>
<td>16</td>
<td>128</td>
<td>6.8</td>
<td>3116.72</td>
<td>3116.72</td>
<td>2649.21</td>
<td>1714.2</td>
<td>1184.35</td>
</tr>
<tr>
<td>内存型 ecs.r6.6xlarge</td>
<td>24</td>
<td>192</td>
<td>10.2</td>
<td>4675.08</td>
<td>4675.08</td>
<td>3973.82</td>
<td>2571.29</td>
<td>1776.53</td>
</tr>
<tr>
<td>内存型 ecs.r6.8xlarge</td>
<td>32</td>
<td>256</td>
<td>13.6</td>
<td>6233.44</td>
<td>6233.44</td>
<td>5298.42</td>
<td>3428.39</td>
<td>2368.71</td>
</tr>
<tr>
<td>内存型 ecs.r6.13xlarge</td>
<td>52</td>
<td>384</td>
<td>22.1</td>
<td>10129.34</td>
<td>10129.34</td>
<td>8609.94</td>
<td>5571.14</td>
<td>3849.15</td>
</tr>
<tr>
<td>内存型 ecs.r6.26xlarge</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>0.935</td>
<td>428.55</td>
<td>428.55</td>
<td>364.27</td>
<td>235.7</td>
<td>162.85</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.87</td>
<td>857.1</td>
<td>857.1</td>
<td>728.53</td>
<td>471.4</td>
<td>325.7</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.74</td>
<td>1714.2</td>
<td>1714.2</td>
<td>1457.07</td>
<td>942.81</td>
<td>651.39</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.48</td>
<td>3428.39</td>
<td>3428.39</td>
<td>2914.13</td>
<td>1885.62</td>
<td>1302.79</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.96</td>
<td>6856.78</td>
<td>6856.78</td>
<td>5828.27</td>
<td>3771.23</td>
<td>2605.58</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.13xlarge</td>
<td>52</td>
<td>384</td>
<td>24.31</td>
<td>11142.27</td>
<td>11142.27</td>
<td>9470.93</td>
<td>6128.25</td>
<td>4234.06</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.large</td>
<td>2</td>
<td>4</td>
<td>0.61</td>
<td>281.07</td>
<td>281.07</td>
<td>238.91</td>
<td>154.59</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>1.22</td>
<td>562.14</td>
<td>562.14</td>
<td>477.82</td>
<td>309.18</td>
<td>213.61</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.44</td>
<td>1124.28</td>
<td>1124.28</td>
<td>955.64</td>
<td>618.35</td>
<td>427.23</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.66</td>
<td>1686.42</td>
<td>1686.42</td>
<td>1433.46</td>
<td>927.53</td>
<td>640.84</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.88</td>
<td>2248.56</td>
<td>2248.56</td>
<td>1911.28</td>
<td>1236.71</td>
<td>854.45</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.6xlarge</td>
<td>24</td>
<td>48</td>
<td>7.32</td>
<td>3372.84</td>
<td>3372.84</td>
<td>2866.91</td>
<td>1855.06</td>
<td>1281.68</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.8xlarge</td>
<td>32</td>
<td>64</td>
<td>9.76</td>
<td>4497.12</td>
<td>4497.12</td>
<td>3822.55</td>
<td>2473.42</td>
<td>1708.91</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.10xlarge</td>
<td>40</td>
<td>96</td>
<td>12.2</td>
<td>5621.4</td>
<td>5621.4</td>
<td>4778.19</td>
<td>3091.77</td>
<td>2136.13</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.16xlarge</td>
<td>64</td>
<td>128</td>
<td>19.52</td>
<td>8994.24</td>
<td>8994.24</td>
<td>7645.1</td>
<td>4946.83</td>
<td>3417.81</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.20xlarge</td>
<td>80</td>
<td>192</td>
<td>24.4</td>
<td>11242.8</td>
<td>11242.8</td>
<td>9556.38</td>
<td>6183.54</td>
<td>4272.26</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.large</td>
<td>2</td>
<td>8</td>
<td>0.71</td>
<td>330.94</td>
<td>330.94</td>
<td>281.3</td>
<td>182.02</td>
<td>125.76</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.42</td>
<td>661.88</td>
<td>661.88</td>
<td>562.6</td>
<td>364.03</td>
<td>251.51</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.84</td>
<td>1323.76</td>
<td>1323.76</td>
<td>1125.2</td>
<td>728.07</td>
<td>503.03</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.3xlarge</td>
<td>12</td>
<td>48</td>
<td>4.26</td>
<td>1985.64</td>
<td>1985.64</td>
<td>1687.79</td>
<td>1092.1</td>
<td>754.54</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.68</td>
<td>2647.52</td>
<td>2647.52</td>
<td>2250.39</td>
<td>1456.14</td>
<td>1006.06</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.6xlarge</td>
<td>24</td>
<td>96</td>
<td>8.52</td>
<td>3971.28</td>
<td>3971.28</td>
<td>3375.59</td>
<td>2184.2</td>
<td>1509.09</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.36</td>
<td>5295.04</td>
<td>5295.04</td>
<td>4500.78</td>
<td>2912.27</td>
<td>2012.12</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.10xlarge</td>
<td>40</td>
<td>192</td>
<td>14.2</td>
<td>6618.8</td>
<td>6618.8</td>
<td>5625.98</td>
<td>3640.34</td>
<td>2515.14</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.16xlarge</td>
<td>64</td>
<td>256</td>
<td>22.72</td>
<td>10590.08</td>
<td>10590.08</td>
<td>9001.57</td>
<td>5824.54</td>
<td>4024.23</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.20xlarge</td>
<td>80</td>
<td>384</td>
<td>28.4</td>
<td>13237.6</td>
<td>13237.6</td>
<td>11251.96</td>
<td>7280.68</td>
<td>5030.29</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.large</td>
<td>2</td>
<td>16</td>
<td>0.93</td>
<td>428.53</td>
<td>428.53</td>
<td>364.25</td>
<td>235.69</td>
<td>162.84</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.86</td>
<td>857.06</td>
<td>857.06</td>
<td>728.5</td>
<td>471.38</td>
<td>325.68</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.72</td>
<td>1714.12</td>
<td>1714.12</td>
<td>1457</td>
<td>942.77</td>
<td>651.37</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.3xlarge</td>
<td>12</td>
<td>96</td>
<td>5.58</td>
<td>2571.18</td>
<td>2571.18</td>
<td>2185.5</td>
<td>1414.15</td>
<td>977.05</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.44</td>
<td>3428.24</td>
<td>3428.24</td>
<td>2914</td>
<td>1885.53</td>
<td>1302.73</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.6xlarge</td>
<td>24</td>
<td>192</td>
<td>11.16</td>
<td>5142.36</td>
<td>5142.36</td>
<td>4371.01</td>
<td>2828.3</td>
<td>1954.1</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.88</td>
<td>6856.48</td>
<td>6856.48</td>
<td>5828.01</td>
<td>3771.06</td>
<td>2605.46</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.10xlarge</td>
<td>40</td>
<td>384</td>
<td>18.6</td>
<td>8570.6</td>
<td>8570.6</td>
<td>7285.01</td>
<td>4713.83</td>
<td>3256.83</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.16xlarge</td>
<td>64</td>
<td>512</td>
<td>29.76</td>
<td>13712.96</td>
<td>13712.96</td>
<td>11656.02</td>
<td>7542.13</td>
<td>5210.92</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.20xlarge</td>
<td>80</td>
<td>768</td>
<td>37.2</td>
<td>17141.2</td>
<td>17141.2</td>
<td>14570.02</td>
<td>9427.66</td>
<td>6513.66</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6e-c12g1.3xlarge</td>
<td>12</td>
<td>92</td>
<td>19.428</td>
<td>9991.39</td>
<td>9991.39</td>
<td>9991.39</td>
<td>9991.39</td>
<td>9991.39</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6e-c12g1.12xlarge</td>
<td>48</td>
<td>368</td>
<td>77.711</td>
<td>39965.57</td>
<td>39965.57</td>
<td>39965.57</td>
<td>39965.57</td>
<td>39965.57</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6e-c12g1.24xlarge</td>
<td>96</td>
<td>736</td>
<td>155.422</td>
<td>79931.15</td>
<td>79931.15</td>
<td>79931.15</td>
<td>79931.15</td>
<td>79931.15</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c8g1.2xlarge</td>
<td>8</td>
<td>32</td>
<td>18.26</td>
<td>8763.19</td>
<td>8325.03</td>
<td>6572.39</td>
<td>3943.44</td>
<td>2628.96</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c8g1.8xlarge</td>
<td>32</td>
<td>128</td>
<td>73.04</td>
<td>35052.76</td>
<td>33300.12</td>
<td>26289.57</td>
<td>15773.74</td>
<td>10515.83</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c8g1.16xlarge</td>
<td>64</td>
<td>256</td>
<td>146.08</td>
<td>70105.52</td>
<td>66600.24</td>
<td>52579.14</td>
<td>31547.48</td>
<td>21031.66</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c4g1.xlarge</td>
<td>4</td>
<td>15</td>
<td>7.79</td>
<td>3736.48</td>
<td>3736.48</td>
<td>3176.01</td>
<td>2055.06</td>
<td>1419.86</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c8g1.2xlarge</td>
<td>8</td>
<td>31</td>
<td>9.08</td>
<td>4358.1</td>
<td>4358.1</td>
<td>3704.39</td>
<td>2396.95</td>
<td>1656.08</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c16g1.4xlarge</td>
<td>16</td>
<td>62</td>
<td>11.68</td>
<td>5608.1</td>
<td>5608.1</td>
<td>4766.89</td>
<td>3084.45</td>
<td>2131.08</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.6xlarge</td>
<td>24</td>
<td>93</td>
<td>14.84</td>
<td>7121.61</td>
<td>7121.61</td>
<td>6053.37</td>
<td>3916.89</td>
<td>2706.21</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.12xlarge</td>
<td>48</td>
<td>186</td>
<td>29.69</td>
<td>14249.97</td>
<td>14249.97</td>
<td>12112.47</td>
<td>7837.48</td>
<td>5414.99</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.24xlarge</td>
<td>96</td>
<td>372</td>
<td>59.39</td>
<td>28506.7</td>
<td>28506.7</td>
<td>24230.7</td>
<td>15678.69</td>
<td>10832.55</td>
</tr>
<tr>
<td>GPU可视化计算型 ecs.vgn6i-m8.2xlarge</td>
<td>10</td>
<td>46</td>
<td>5.053</td>
<td>2425.56</td>
<td>2425.56</td>
<td>2061.72</td>
<td>1334.06</td>
<td>921.71</td>
</tr>
<tr>
<td>通用型 ecs.g5.large</td>
<td>2</td>
<td>8</td>
<td>0.677</td>
<td>306.14</td>
<td>306.14</td>
<td>260.22</td>
<td>168.38</td>
<td>116.33</td>
</tr>
<tr>
<td>通用型 ecs.g5.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.353</td>
<td>611.79</td>
<td>611.79</td>
<td>520.02</td>
<td>336.48</td>
<td>232.48</td>
</tr>
<tr>
<td>通用型 ecs.g5.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.706</td>
<td>1223.51</td>
<td>1223.51</td>
<td>1039.98</td>
<td>672.93</td>
<td>464.93</td>
</tr>
<tr>
<td>通用型 ecs.g5.3xlarge</td>
<td>12</td>
<td>48</td>
<td>4.059</td>
<td>1835.3</td>
<td>1835.3</td>
<td>1560.01</td>
<td>1009.42</td>
<td>697.41</td>
</tr>
<tr>
<td>通用型 ecs.g5.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.412</td>
<td>2447.08</td>
<td>2447.08</td>
<td>2080.02</td>
<td>1345.89</td>
<td>929.89</td>
</tr>
<tr>
<td>通用型 ecs.g5.6xlarge</td>
<td>24</td>
<td>96</td>
<td>8.117</td>
<td>3670.66</td>
<td>3670.66</td>
<td>3120.06</td>
<td>2018.86</td>
<td>1394.85</td>
</tr>
<tr>
<td>通用型 ecs.g5.8xlarge</td>
<td>32</td>
<td>128</td>
<td>10.823</td>
<td>4894.16</td>
<td>4894.16</td>
<td>4160.04</td>
<td>2691.79</td>
<td>1859.78</td>
</tr>
<tr>
<td>通用型 ecs.g5.16xlarge</td>
<td>64</td>
<td>256</td>
<td>21.645</td>
<td>9788.25</td>
<td>9788.25</td>
<td>8320.01</td>
<td>5383.54</td>
<td>3719.54</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.large</td>
<td>2</td>
<td>8</td>
<td>1.033177</td>
<td>379.11</td>
<td>379.11</td>
<td>322.24</td>
<td>208.51</td>
<td>144.06</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>2.066354</td>
<td>758.22</td>
<td>758.22</td>
<td>644.49</td>
<td>417.02</td>
<td>288.12</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.135</td>
<td>1516.44</td>
<td>1516.44</td>
<td>1288.97</td>
<td>834.04</td>
<td>576.25</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>6.27</td>
<td>3032.88</td>
<td>3032.88</td>
<td>2577.95</td>
<td>1668.08</td>
<td>1152.49</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>12.54</td>
<td>6065.76</td>
<td>6065.76</td>
<td>5155.9</td>
<td>3336.17</td>
<td>2304.99</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.16xlarge</td>
<td>64</td>
<td>256</td>
<td>25.08</td>
<td>12131.52</td>
<td>12131.52</td>
<td>10311.79</td>
<td>6672.34</td>
<td>4609.98</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.18xlarge</td>
<td>72</td>
<td>288</td>
<td>28.215</td>
<td>13647.96</td>
<td>13647.96</td>
<td>11600.77</td>
<td>7506.38</td>
<td>5186.22</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.large</td>
<td>2</td>
<td>2</td>
<td>0.51</td>
<td>234</td>
<td>234</td>
<td>198.9</td>
<td>128.7</td>
<td>88.92</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.xlarge</td>
<td>4</td>
<td>4</td>
<td>1.02</td>
<td>467</td>
<td>467</td>
<td>396.95</td>
<td>256.85</td>
<td>177.46</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.2xlarge</td>
<td>8</td>
<td>8</td>
<td>2.02</td>
<td>934</td>
<td>934</td>
<td>793.9</td>
<td>513.7</td>
<td>354.92</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.3xlarge</td>
<td>12</td>
<td>12</td>
<td>3.04</td>
<td>1401</td>
<td>1401</td>
<td>1190.85</td>
<td>770.55</td>
<td>532.38</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.4xlarge</td>
<td>16</td>
<td>16</td>
<td>4.04</td>
<td>1868</td>
<td>1868</td>
<td>1587.8</td>
<td>1027.4</td>
<td>709.84</td>
</tr>
<tr>
<td>计算型 ecs.c5.large</td>
<td>2</td>
<td>4</td>
<td>0.535</td>
<td>245.8</td>
<td>245.8</td>
<td>208.93</td>
<td>135.19</td>
<td>93.4</td>
</tr>
<tr>
<td>计算型 ecs.c5.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.069</td>
<td>491.53</td>
<td>491.53</td>
<td>417.8</td>
<td>270.34</td>
<td>186.78</td>
</tr>
<tr>
<td>计算型 ecs.c5.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.131</td>
<td>982.99</td>
<td>982.99</td>
<td>835.54</td>
<td>540.64</td>
<td>373.54</td>
</tr>
<tr>
<td>计算型 ecs.c5.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.196</td>
<td>1474.52</td>
<td>1474.52</td>
<td>1253.34</td>
<td>810.99</td>
<td>560.32</td>
</tr>
<tr>
<td>计算型 ecs.c5.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.255</td>
<td>1965.97</td>
<td>1965.97</td>
<td>1671.07</td>
<td>1081.28</td>
<td>747.07</td>
</tr>
<tr>
<td>计算型 ecs.c5.6xlarge</td>
<td>24</td>
<td>48</td>
<td>6.386</td>
<td>2948.96</td>
<td>2948.96</td>
<td>2506.62</td>
<td>1621.93</td>
<td>1120.6</td>
</tr>
<tr>
<td>计算型 ecs.c5.8xlarge</td>
<td>32</td>
<td>64</td>
<td>8.509</td>
<td>3931.94</td>
<td>3931.94</td>
<td>3342.15</td>
<td>2162.57</td>
<td>1494.14</td>
</tr>
<tr>
<td>计算型 ecs.c5.16xlarge</td>
<td>64</td>
<td>128</td>
<td>17.018</td>
<td>7863.88</td>
<td>7863.88</td>
<td>6684.3</td>
<td>4325.13</td>
<td>2988.27</td>
</tr>
<tr>
<td>内存型 ecs.r5.large</td>
<td>2</td>
<td>16</td>
<td>0.9</td>
<td>414.76</td>
<td>414.76</td>
<td>352.55</td>
<td>228.12</td>
<td>157.61</td>
</tr>
<tr>
<td>内存型 ecs.r5.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.8</td>
<td>829.52</td>
<td>829.52</td>
<td>705.09</td>
<td>456.24</td>
<td>315.22</td>
</tr>
<tr>
<td>内存型 ecs.r5.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.599</td>
<td>1659.03</td>
<td>1659.03</td>
<td>1410.18</td>
<td>912.47</td>
<td>630.43</td>
</tr>
<tr>
<td>内存型 ecs.r5.3xlarge</td>
<td>12</td>
<td>96</td>
<td>5.398</td>
<td>2488.55</td>
<td>2488.55</td>
<td>2115.27</td>
<td>1368.7</td>
<td>945.65</td>
</tr>
<tr>
<td>内存型 ecs.r5.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.197</td>
<td>3318.06</td>
<td>3318.06</td>
<td>2820.35</td>
<td>1824.93</td>
<td>1260.86</td>
</tr>
<tr>
<td>内存型 ecs.r5.6xlarge</td>
<td>24</td>
<td>192</td>
<td>10.796</td>
<td>4977.09</td>
<td>4977.09</td>
<td>4230.53</td>
<td>2737.4</td>
<td>1891.29</td>
</tr>
<tr>
<td>内存型 ecs.r5.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.394</td>
<td>6636.11</td>
<td>6636.11</td>
<td>5640.69</td>
<td>3649.86</td>
<td>2521.72</td>
</tr>
<tr>
<td>内存型 ecs.r5.16xlarge</td>
<td>64</td>
<td>512</td>
<td>28.787</td>
<td>13272.22</td>
<td>13272.22</td>
<td>11281.39</td>
<td>7299.72</td>
<td>5043.44</td>
</tr>
<tr>
<td>大数据存储密集型 ecs.d2s.5xlarge</td>
<td>20</td>
<td>88</td>
<td>17.888</td>
<td>5151.29</td>
<td>5151.29</td>
<td>4378.6</td>
<td>2833.21</td>
<td>1957.49</td>
</tr>
<tr>
<td>大数据存储密集型 ecs.d2s.10xlarge</td>
<td>40</td>
<td>176</td>
<td>35.776</td>
<td>10302.58</td>
<td>10302.58</td>
<td>8757.19</td>
<td>5666.42</td>
<td>3914.98</td>
</tr>
<tr>
<td>大数据存储密集型 ecs.d2s.20xlarge</td>
<td>80</td>
<td>352</td>
<td>71.545</td>
<td>20605.12</td>
<td>20605.12</td>
<td>17514.35</td>
<td>11332.82</td>
<td>7829.95</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>4.539</td>
<td>2180.79</td>
<td>2071.75</td>
<td>1635.59</td>
<td>981.36</td>
<td>654.24</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>9.084</td>
<td>4361.58</td>
<td>4143.5</td>
<td>3271.18</td>
<td>1962.71</td>
<td>1308.47</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.6xlarge</td>
<td>24</td>
<td>96</td>
<td>13.63</td>
<td>6542.37</td>
<td>6215.25</td>
<td>4906.78</td>
<td>2944.07</td>
<td>1962.71</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne-c8d3.8xlarge</td>
<td>32</td>
<td>128</td>
<td>17.44</td>
<td>8377</td>
<td>7958.15</td>
<td>6282.75</td>
<td>3769.65</td>
<td>2513.1</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>18.168</td>
<td>8723.22</td>
<td>8287.06</td>
<td>6542.41</td>
<td>3925.45</td>
<td>2616.97</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne-c14d3.14xlarge</td>
<td>56</td>
<td>160</td>
<td>26.46</td>
<td>12705</td>
<td>12069.75</td>
<td>9528.75</td>
<td>5717.25</td>
<td>3811.5</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.14xlarge</td>
<td>56</td>
<td>224</td>
<td>31.804</td>
<td>15265.58</td>
<td>14502.3</td>
<td>11449.18</td>
<td>6869.51</td>
<td>4579.67</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.8</td>
<td>894</td>
<td>894</td>
<td>759.9</td>
<td>491.7</td>
<td>894</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.59</td>
<td>1787</td>
<td>1787</td>
<td>1518.95</td>
<td>982.85</td>
<td>1787</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.18</td>
<td>3574</td>
<td>3574</td>
<td>3037.9</td>
<td>1965.7</td>
<td>3574</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.36</td>
<td>7148</td>
<td>7148</td>
<td>6075.8</td>
<td>3931.4</td>
<td>7148</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.16xlarge</td>
<td>64</td>
<td>512</td>
<td>28.71</td>
<td>14296</td>
<td>14296</td>
<td>12151.6</td>
<td>7862.8</td>
<td>14296</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.952</td>
<td>1449.75</td>
<td>1377.26</td>
<td>1087.31</td>
<td>652.39</td>
<td>1449.75</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.904</td>
<td>2899.5</td>
<td>2754.52</td>
<td>2174.63</td>
<td>1304.78</td>
<td>2899.5</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.808</td>
<td>5799</td>
<td>5509.05</td>
<td>4349.25</td>
<td>2609.55</td>
<td>5799</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.16xlarge</td>
<td>64</td>
<td>256</td>
<td>23.616</td>
<td>11598</td>
<td>11018.1</td>
<td>8698.5</td>
<td>5219.1</td>
<td>11598</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.889999</td>
<td>938.7</td>
<td>938.7</td>
<td>797.89</td>
<td>516.28</td>
<td>356.71</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.78</td>
<td>1877.4</td>
<td>1877.4</td>
<td>1595.79</td>
<td>1032.57</td>
<td>713.41</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.56</td>
<td>3754.8</td>
<td>3754.8</td>
<td>3191.58</td>
<td>2065.14</td>
<td>1426.82</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.8xlarge</td>
<td>32</td>
<td>256</td>
<td>15.12</td>
<td>7509.6</td>
<td>7509.6</td>
<td>6383.16</td>
<td>4130.28</td>
<td>2853.65</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.16xlarge</td>
<td>64</td>
<td>512</td>
<td>30.24</td>
<td>15019.2</td>
<td>15019.2</td>
<td>12766.32</td>
<td>8260.56</td>
<td>5707.3</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.1</td>
<td>1522.24</td>
<td>1522.24</td>
<td>1293.9</td>
<td>837.23</td>
<td>578.45</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>6.2</td>
<td>3044.48</td>
<td>3044.48</td>
<td>2587.81</td>
<td>1674.46</td>
<td>1156.9</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>12.399</td>
<td>6088.95</td>
<td>6088.95</td>
<td>5175.61</td>
<td>3348.92</td>
<td>2313.8</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.16xlarge</td>
<td>64</td>
<td>256</td>
<td>24.8</td>
<td>12177.92</td>
<td>12177.92</td>
<td>10351.23</td>
<td>6697.86</td>
<td>4627.61</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.large</td>
<td>2</td>
<td>8</td>
<td>0.725</td>
<td>327.71</td>
<td>327.71</td>
<td>278.55</td>
<td>180.24</td>
<td>124.53</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.449</td>
<td>654.92</td>
<td>654.92</td>
<td>556.68</td>
<td>360.21</td>
<td>248.87</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.897</td>
<td>1309.79</td>
<td>1309.79</td>
<td>1113.32</td>
<td>720.38</td>
<td>497.72</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.3xlarge</td>
<td>12</td>
<td>48</td>
<td>4.35</td>
<td>1966.26</td>
<td>1966.26</td>
<td>1671.32</td>
<td>1081.44</td>
<td>747.18</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.793</td>
<td>2619.66</td>
<td>2619.66</td>
<td>2226.71</td>
<td>1440.81</td>
<td>995.47</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.6xlarge</td>
<td>24</td>
<td>96</td>
<td>8.7</td>
<td>3932.52</td>
<td>3932.52</td>
<td>3342.64</td>
<td>2162.89</td>
<td>1494.36</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.586</td>
<td>5239.33</td>
<td>5239.33</td>
<td>4453.43</td>
<td>2881.63</td>
<td>1990.95</td>
</tr>
<tr>
<td>通用网络增强型 ecs.sn2ne.14xlarge</td>
<td>56</td>
<td>224</td>
<td>20.275</td>
<td>9176.19</td>
<td>9176.19</td>
<td>7799.76</td>
<td>5046.9</td>
<td>3486.95</td>
</tr>
<tr>
<td>计算网络增强型 ecs.sn1ne.large</td>
<td>2</td>
<td>4</td>
<td>0.623</td>
<td>285.91</td>
<td>285.91</td>
<td>243.02</td>
<td>157.25</td>
<td>108.65</td>
</tr>
<tr>
<td>计算网络增强型 ecs.sn1ne.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.238</td>
<td>571.83</td>
<td>571.83</td>
<td>486.06</td>
<td>314.51</td>
<td>217.3</td>
</tr>
<tr>
<td>计算网络增强型 ecs.sn1ne.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.475</td>
<td>1143.66</td>
<td>1143.66</td>
<td>972.11</td>
<td>629.01</td>
<td>434.59</td>
</tr>
<tr>
<td>计算网络增强型 ecs.sn1ne.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.738</td>
<td>1715.46</td>
<td>1715.46</td>
<td>1458.14</td>
<td>943.5</td>
<td>651.87</td>
</tr>
<tr>
<td>计算网络增强型 ecs.sn1ne.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.95</td>
<td>2287.32</td>
<td>2287.32</td>
<td>1944.22</td>
<td>1258.03</td>
<td>869.18</td>
</tr>
<tr>
<td>计算网络增强型 ecs.sn1ne.6xlarge</td>
<td>24</td>
<td>48</td>
<td>7.476</td>
<td>3430.92</td>
<td>3430.92</td>
<td>2916.28</td>
<td>1887.01</td>
<td>1303.75</td>
</tr>
<tr>
<td>计算网络增强型 ecs.sn1ne.8xlarge</td>
<td>32</td>
<td>64</td>
<td>9.893</td>
<td>4574.64</td>
<td>4574.64</td>
<td>3888.44</td>
<td>2516.05</td>
<td>1738.36</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.large</td>
<td>2</td>
<td>16</td>
<td>0.964</td>
<td>448</td>
<td>448</td>
<td>380.8</td>
<td>246.4</td>
<td>170.24</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.927</td>
<td>874.07</td>
<td>874.07</td>
<td>742.96</td>
<td>480.74</td>
<td>332.15</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.853</td>
<td>1726.22</td>
<td>1726.22</td>
<td>1467.29</td>
<td>949.42</td>
<td>655.96</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.3xlarge</td>
<td>12</td>
<td>96</td>
<td>5.784</td>
<td>2688</td>
<td>2688</td>
<td>2284.8</td>
<td>1478.4</td>
<td>1021.44</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.705</td>
<td>3430.49</td>
<td>3430.49</td>
<td>2915.92</td>
<td>1886.77</td>
<td>1303.59</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.6xlarge</td>
<td>24</td>
<td>192</td>
<td>11.568</td>
<td>5376</td>
<td>5376</td>
<td>4569.6</td>
<td>2956.8</td>
<td>2042.88</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.8xlarge</td>
<td>32</td>
<td>256</td>
<td>15.409</td>
<td>6839.04</td>
<td>6839.04</td>
<td>5813.18</td>
<td>3761.47</td>
<td>2598.84</td>
</tr>
<tr>
<td>内存网络增强型 ecs.se1ne.14xlarge</td>
<td>56</td>
<td>480</td>
<td>28.41</td>
<td>13216.33</td>
<td>13216.33</td>
<td>11233.88</td>
<td>7268.98</td>
<td>5022.21</td>
</tr>
<tr>
<td>内存型 ecs.se1.large</td>
<td>2</td>
<td>16</td>
<td>0.918</td>
<td>426.67</td>
<td>426.67</td>
<td>362.67</td>
<td>213.34</td>
<td>213.34</td>
</tr>
<tr>
<td>内存型 ecs.se1.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.835</td>
<td>832.45</td>
<td>832.45</td>
<td>707.58</td>
<td>416.23</td>
<td>416.23</td>
</tr>
<tr>
<td>内存型 ecs.se1.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.669</td>
<td>1644.02</td>
<td>1644.02</td>
<td>1397.42</td>
<td>822.01</td>
<td>822.01</td>
</tr>
<tr>
<td>内存型 ecs.se1.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.338</td>
<td>3267.14</td>
<td>3267.14</td>
<td>2777.07</td>
<td>1633.57</td>
<td>1633.57</td>
</tr>
<tr>
<td>内存型 ecs.se1.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.675</td>
<td>6513.38</td>
<td>6513.38</td>
<td>5536.37</td>
<td>3256.69</td>
<td>3256.69</td>
</tr>
<tr>
<td>内存型 ecs.se1.14xlarge</td>
<td>56</td>
<td>480</td>
<td>27.057</td>
<td>12586.99</td>
<td>12586.99</td>
<td>10698.94</td>
<td>6293.49</td>
<td>6293.49</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c4g1.xlarge</td>
<td>4</td>
<td>30</td>
<td>10.79</td>
<td>5185</td>
<td>4925.75</td>
<td>3888.75</td>
<td>2333.25</td>
<td>1555.5</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.2xlarge</td>
<td>8</td>
<td>60</td>
<td>13</td>
<td>6244</td>
<td>5931.8</td>
<td>4683</td>
<td>2809.8</td>
<td>1873.2</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c4g1.2xlarge</td>
<td>8</td>
<td>60</td>
<td>21.6</td>
<td>10371</td>
<td>9852.45</td>
<td>7778.25</td>
<td>4666.95</td>
<td>3111.3</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.4xlarge</td>
<td>16</td>
<td>120</td>
<td>26.01</td>
<td>12488</td>
<td>11863.6</td>
<td>9366</td>
<td>5619.6</td>
<td>3746.4</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c28g1.7xlarge</td>
<td>28</td>
<td>112</td>
<td>20.59</td>
<td>8985</td>
<td>8535.75</td>
<td>6738.75</td>
<td>4043.25</td>
<td>2695.5</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.8xlarge</td>
<td>32</td>
<td>240</td>
<td>52.03</td>
<td>24976</td>
<td>23727.2</td>
<td>18732</td>
<td>11239.2</td>
<td>7492.8</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c28g1.14xlarge</td>
<td>56</td>
<td>224</td>
<td>41.18</td>
<td>17970</td>
<td>17071.5</td>
<td>13477.5</td>
<td>8086.5</td>
<td>5391</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c8g1.14xlarge</td>
<td>54</td>
<td>480</td>
<td>104.06</td>
<td>49953</td>
<td>47455.35</td>
<td>37464.75</td>
<td>22478.85</td>
<td>14985.9</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>共享基本型 ecs.xn4.small</td>
<td>1</td>
<td>1</td>
<td>0.084</td>
<td>42.69</td>
<td>42.69</td>
<td>36.29</td>
<td>21.34</td>
<td>21.35</td>
</tr>
<tr>
<td>共享计算型 ecs.n4.small</td>
<td>1</td>
<td>2</td>
<td>0.161</td>
<td>85.39</td>
<td>85.39</td>
<td>72.58</td>
<td>42.7</td>
<td>42.7</td>
</tr>
<tr>
<td>共享计算型 ecs.n4.large</td>
<td>2</td>
<td>4</td>
<td>0.328</td>
<td>170.86</td>
<td>170.86</td>
<td>145.23</td>
<td>85.43</td>
<td>85.43</td>
</tr>
<tr>
<td>共享计算型 ecs.n4.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.177</td>
<td>544.6</td>
<td>544.6</td>
<td>462.91</td>
<td>272.3</td>
<td>272.3</td>
</tr>
<tr>
<td>共享计算型 ecs.n4.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.347</td>
<td>1089.2</td>
<td>1089.2</td>
<td>925.82</td>
<td>544.6</td>
<td>544.6</td>
</tr>
<tr>
<td>共享计算型 ecs.n4.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.686</td>
<td>2178.4</td>
<td>2178.4</td>
<td>1851.64</td>
<td>1089.2</td>
<td>1089.2</td>
</tr>
<tr>
<td>共享计算型 ecs.n4.8xlarge</td>
<td>32</td>
<td>64</td>
<td>9.373</td>
<td>4356.8</td>
<td>4356.8</td>
<td>3703.28</td>
<td>2178.4</td>
<td>2178.4</td>
</tr>
<tr>
<td>共享通用型 ecs.mn4.small</td>
<td>1</td>
<td>4</td>
<td>0.307</td>
<td>156.05</td>
<td>156.05</td>
<td>132.64</td>
<td>78.03</td>
<td>78.03</td>
</tr>
<tr>
<td>共享通用型 ecs.mn4.large</td>
<td>2</td>
<td>8</td>
<td>0.614</td>
<td>312.11</td>
<td>312.11</td>
<td>265.29</td>
<td>156.05</td>
<td>156.05</td>
</tr>
<tr>
<td>共享通用型 ecs.mn4.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.227</td>
<td>623.74</td>
<td>623.74</td>
<td>530.18</td>
<td>311.87</td>
<td>311.87</td>
</tr>
<tr>
<td>共享通用型 ecs.mn4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.459</td>
<td>1247.42</td>
<td>1247.42</td>
<td>1060.31</td>
<td>623.71</td>
<td>623.71</td>
</tr>
<tr>
<td>共享通用型 ecs.mn4.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.913</td>
<td>2494.92</td>
<td>2494.92</td>
<td>2120.68</td>
<td>1247.46</td>
<td>1247.46</td>
</tr>
<tr>
<td>共享通用型 ecs.mn4.8xlarge</td>
<td>32</td>
<td>128</td>
<td>9.815</td>
<td>4989.84</td>
<td>4989.84</td>
<td>4241.36</td>
<td>2494.92</td>
<td>2494.92</td>
</tr>
<tr>
<td>共享内存型 ecs.e4.small</td>
<td>1</td>
<td>8</td>
<td>0.459</td>
<td>213.33</td>
<td>213.33</td>
<td>181.33</td>
<td>106.67</td>
<td>106.66</td>
</tr>
</tbody>
</table>