论坛 › 技术前沿 › 阿里云服务器美国地域多少钱？美国地域最新收费标准及便宜购买教程

tho106796 发表于 2024-10-5 22:53:30

阿里云服务器美国地域多少钱？美国地域最新收费标准及便宜购买教程

阿里云服务器在国内有十几个地域可选，美国地域主要有弗吉尼亚和硅谷两个地域，且不用备案，2024年阿里云中国内地地域云服务器做了降价调整，因此收费标准也有所变化，本文为大家展示阿里云服务器美国地域最新的收费标准，以及在实际购买过程中如何购买价格可以更加便宜，以供参考。
<h2>一、阿里云服务器美国地域接入点及运营商介绍</h2>
阿里云服务器美国地域有弗吉尼亚、硅谷两个接入点，运营商有Equinix、CUA、Coresite等。
<table>
<thead>
<tr>
<th>地域</th>
<th>接入点</th>
<th>运营商</th>
</tr>
</thead>
<tbody>
<tr>
<td>美国（硅谷）</td>
<td>美国-圣何塞-A</td>
<td>Equinix</td>
</tr>
<tr>
<td>美国（弗吉尼亚）</td>
<td>美国-阿什本-A</td>
<td>Equinix</td>
</tr>
<tr>
<td>美国（弗吉尼亚）</td>
<td>美国-阿什本-B</td>
<td>CUA</td>
</tr>
<tr>
<td>美国（弗吉尼亚）</td>
<td>美国-弗吉尼亚-C</td>
<td>CUA</td>
</tr>
<tr>
<td>美国（弗吉尼亚）</td>
<td>美国-弗吉尼亚-D</td>
<td>Coresite</td>
</tr>
</tbody>
</table>
<h2>二、阿里云服务器美国地域最新收费标准</h2>
阿里云服务器配置与实例规格不同，收费标准不一样，同时购买时长不同，换算到每个月的收费标准也不同，下面是阿里云服务器美国地域最新收费标准，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>按量月估价(30天)</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>0.5525</td>
<td>397.8</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>0.4505</td>
<td>324.36</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>0.7225</td>
<td>520.2</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>0.428</td>
<td>308.16</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>0.8559</td>
<td>616.25</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>1.4449</td>
<td>1040.33</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>0.901</td>
<td>648.72</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>1.105</td>
<td>795.6</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>2.21</td>
<td>1591.2</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>1.802</td>
<td>1297.44</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>2.8898</td>
<td>2080.66</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>1.7119</td>
<td>1232.57</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>3.315</td>
<td>2386.8</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>2.5678</td>
<td>1848.82</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>2.703</td>
<td>1946.16</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>4.3346</td>
<td>3120.91</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>3.4238</td>
<td>2465.14</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>5.7795</td>
<td>4161.24</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>4.42</td>
<td>3182.4</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>3.604</td>
<td>2594.88</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>8.84</td>
<td>6364.8</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>11.559</td>
<td>8322.48</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>7.208</td>
<td>5189.76</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>6.8476</td>
<td>4930.27</td>
<td>3158.04</td>
<td>1894.82</td>
<td>1200.05</td>
<td>1200.05</td>
</tr>
<tr>
<td>内存型 ecs.r8i.large</td>
<td>2</td>
<td>16</td>
<td>0.79</td>
<td>568.8</td>
<td>448.31</td>
<td>313.81</td>
<td>201.74</td>
<td>134.49</td>
</tr>
<tr>
<td>内存型 ecs.r8i.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.581</td>
<td>1138.32</td>
<td>896.61</td>
<td>627.63</td>
<td>403.48</td>
<td>268.98</td>
</tr>
<tr>
<td>内存型 ecs.r8i.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.162</td>
<td>2276.64</td>
<td>1793.23</td>
<td>1255.26</td>
<td>806.95</td>
<td>537.97</td>
</tr>
<tr>
<td>内存型 ecs.r8i.3xlarge</td>
<td>12</td>
<td>96</td>
<td>4.742</td>
<td>3414.24</td>
<td>2689.84</td>
<td>1882.89</td>
<td>1210.43</td>
<td>806.95</td>
</tr>
<tr>
<td>内存型 ecs.r8i.4xlarge</td>
<td>16</td>
<td>128</td>
<td>6.323</td>
<td>4552.56</td>
<td>3586.46</td>
<td>2510.52</td>
<td>1613.9</td>
<td>1075.94</td>
</tr>
<tr>
<td>内存型 ecs.r8i.6xlarge</td>
<td>24</td>
<td>192</td>
<td>9.485</td>
<td>6829.2</td>
<td>5379.68</td>
<td>3765.78</td>
<td>2420.86</td>
<td>1613.9</td>
</tr>
<tr>
<td>内存型 ecs.r8i.8xlarge</td>
<td>32</td>
<td>256</td>
<td>12.646</td>
<td>9105.12</td>
<td>7172.91</td>
<td>5021.04</td>
<td>3227.81</td>
<td>2151.87</td>
</tr>
<tr>
<td>内存型 ecs.r8i.12xlarge</td>
<td>48</td>
<td>384</td>
<td>18.97</td>
<td>13658.4</td>
<td>10759.37</td>
<td>7531.56</td>
<td>4841.71</td>
<td>3227.81</td>
</tr>
<tr>
<td>计算型 ecs.c8i.large</td>
<td>2</td>
<td>4</td>
<td>0.533</td>
<td>383.76</td>
<td>281.26</td>
<td>196.88</td>
<td>126.57</td>
<td>106.88</td>
</tr>
<tr>
<td>计算型 ecs.c8i.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.066</td>
<td>767.52</td>
<td>562.53</td>
<td>393.77</td>
<td>253.14</td>
<td>168.76</td>
</tr>
<tr>
<td>计算型 ecs.c8i.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.133</td>
<td>1535.76</td>
<td>1125.06</td>
<td>787.54</td>
<td>506.28</td>
<td>337.52</td>
</tr>
<tr>
<td>计算型 ecs.c8i.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.199</td>
<td>2303.28</td>
<td>1687.58</td>
<td>1181.31</td>
<td>759.41</td>
<td>506.27</td>
</tr>
<tr>
<td>计算型 ecs.c8i.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.266</td>
<td>3071.52</td>
<td>2250.11</td>
<td>1575.08</td>
<td>1012.55</td>
<td>675.03</td>
</tr>
<tr>
<td>计算型 ecs.c8i.6xlarge</td>
<td>24</td>
<td>48</td>
<td>6.398</td>
<td>4606.56</td>
<td>3375.17</td>
<td>2362.62</td>
<td>1518.82</td>
<td>1012.55</td>
</tr>
<tr>
<td>计算型 ecs.c8i.8xlarge</td>
<td>32</td>
<td>64</td>
<td>8.531</td>
<td>6142.32</td>
<td>4500.22</td>
<td>3150.16</td>
<td>2025.1</td>
<td>1350.07</td>
</tr>
<tr>
<td>计算型 ecs.c8i.12xlarge</td>
<td>48</td>
<td>96</td>
<td>12.796</td>
<td>9213.12</td>
<td>6750.33</td>
<td>4725.23</td>
<td>3037.65</td>
<td>2025.1</td>
</tr>
<tr>
<td>计算型 ecs.c8i.16xlarge</td>
<td>64</td>
<td>128</td>
<td>17.063</td>
<td>12285.36</td>
<td>9000.45</td>
<td>6300.31</td>
<td>4050.2</td>
<td>2700.13</td>
</tr>
<tr>
<td>计算型 ecs.c8i.24xlarge</td>
<td>96</td>
<td>192</td>
<td>25.592</td>
<td>18426.24</td>
<td>13500.67</td>
<td>9450.47</td>
<td>6075.3</td>
<td>4050.2</td>
</tr>
<tr>
<td>通用型 ecs.g8i.large</td>
<td>2</td>
<td>8</td>
<td>0.602</td>
<td>433.44</td>
<td>346.19</td>
<td>242.33</td>
<td>155.78</td>
<td>103.86</td>
</tr>
<tr>
<td>通用型 ecs.g8i.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.204</td>
<td>866.88</td>
<td>692.38</td>
<td>484.66</td>
<td>311.57</td>
<td>207.71</td>
</tr>
<tr>
<td>通用型 ecs.g8i.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.409</td>
<td>1734.48</td>
<td>1384.76</td>
<td>969.33</td>
<td>623.14</td>
<td>415.43</td>
</tr>
<tr>
<td>通用型 ecs.g8i.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.613</td>
<td>2601.36</td>
<td>2077.14</td>
<td>1454</td>
<td>934.71</td>
<td>623.14</td>
</tr>
<tr>
<td>通用型 ecs.g8i.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.818</td>
<td>3468.96</td>
<td>2769.52</td>
<td>1938.66</td>
<td>1246.28</td>
<td>830.85</td>
</tr>
<tr>
<td>通用型 ecs.g8i.6xlarge</td>
<td>24</td>
<td>96</td>
<td>7.226</td>
<td>5202.72</td>
<td>4154.27</td>
<td>2907.99</td>
<td>1869.42</td>
<td>1246.28</td>
</tr>
<tr>
<td>通用型 ecs.g8i.8xlarge</td>
<td>32</td>
<td>128</td>
<td>9.635</td>
<td>6937.2</td>
<td>5539.03</td>
<td>3877.32</td>
<td>2492.56</td>
<td>1661.71</td>
</tr>
<tr>
<td>通用型 ecs.g8i.12xlarge</td>
<td>48</td>
<td>192</td>
<td>14.452</td>
<td>10405.44</td>
<td>8308.55</td>
<td>5815.98</td>
<td>3738.85</td>
<td>2492.56</td>
</tr>
<tr>
<td>通用型 ecs.g8i.16xlarge</td>
<td>64</td>
<td>256</td>
<td>19.271</td>
<td>13875.12</td>
<td>11078.06</td>
<td>7754.64</td>
<td>4985.13</td>
<td>3323.42</td>
</tr>
<tr>
<td>通用型 ecs.g8i.24xlarge</td>
<td>96</td>
<td>384</td>
<td>28.904</td>
<td>20810.88</td>
<td>16617.09</td>
<td>11631.96</td>
<td>7477.69</td>
<td>4985.13</td>
</tr>
<tr>
<td>通用型 ecs.g7.large</td>
<td>2</td>
<td>8</td>
<td>0.53578</td>
<td>385.76</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>771.52</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>1543.69</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>2315.21</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>3087.37</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>4630.42</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>6174.11</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>12348.86</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>24697.07</td>
<td>22156.12</td>
<td>15509.29</td>
<td>9970.26</td>
<td>6646.84</td>
</tr>
<tr>
<td>内存型 ecs.r7.large</td>
<td>2</td>
<td>16</td>
<td>0.7031</td>
<td>506.23</td>
<td>448.31</td>
<td>313.81</td>
<td>201.74</td>
<td>134.49</td>
</tr>
<tr>
<td>内存型 ecs.r7.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.40709</td>
<td>1013.1</td>
<td>896.61</td>
<td>627.63</td>
<td>403.48</td>
<td>268.98</td>
</tr>
<tr>
<td>内存型 ecs.r7.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.81418</td>
<td>2026.21</td>
<td>1793.23</td>
<td>1255.26</td>
<td>806.95</td>
<td>537.97</td>
</tr>
<tr>
<td>内存型 ecs.r7.3xlarge</td>
<td>12</td>
<td>96</td>
<td>4.22038</td>
<td>3038.67</td>
<td>2689.84</td>
<td>1882.89</td>
<td>1210.43</td>
<td>806.95</td>
</tr>
<tr>
<td>内存型 ecs.r7.4xlarge</td>
<td>16</td>
<td>128</td>
<td>5.62747</td>
<td>4051.78</td>
<td>3586.46</td>
<td>2510.52</td>
<td>1613.9</td>
<td>1075.94</td>
</tr>
<tr>
<td>内存型 ecs.r7.6xlarge</td>
<td>24</td>
<td>192</td>
<td>8.44165</td>
<td>6077.99</td>
<td>5379.68</td>
<td>3765.78</td>
<td>2420.86</td>
<td>1613.9</td>
</tr>
<tr>
<td>内存型 ecs.r7.8xlarge</td>
<td>32</td>
<td>256</td>
<td>11.25494</td>
<td>8103.56</td>
<td>7172.91</td>
<td>5021.04</td>
<td>3227.81</td>
<td>2151.87</td>
</tr>
<tr>
<td>内存型 ecs.r7.16xlarge</td>
<td>64</td>
<td>512</td>
<td>22.51077</td>
<td>16207.75</td>
<td>14345.82</td>
<td>10042.07</td>
<td>6455.62</td>
<td>4303.75</td>
</tr>
<tr>
<td>内存型 ecs.r7.32xlarge</td>
<td>128</td>
<td>1024</td>
<td>45.02065</td>
<td>32414.87</td>
<td>28691.64</td>
<td>20084.15</td>
<td>12911.24</td>
<td>8607.49</td>
</tr>
<tr>
<td>计算型 ecs.c7.large</td>
<td>2</td>
<td>4</td>
<td>0.47437</td>
<td>341.55</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>683.09</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>1366.83</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>2049.92</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>2733.65</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>4099.84</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>5466.66</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>10933.97</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>21867.3</td>
<td>18000.89</td>
<td>12600.62</td>
<td>8100.4</td>
<td>5400.27</td>
</tr>
<tr>
<td>计算型弹性裸金属服务器 ecs.ebmc7.32xlarge</td>
<td>128</td>
<td>256</td>
<td>34.125</td>
<td>24570</td>
<td>18000.89</td>
<td>15300.76</td>
<td>9900.49</td>
<td>6840.34</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c7a.large</td>
<td>2</td>
<td>4</td>
<td>0.425331</td>
<td>306.24</td>
<td>249.33</td>
<td>174.53</td>
<td>137.13</td>
<td>94.75</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c7a.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.850662</td>
<td>612.48</td>
<td>498.66</td>
<td>349.06</td>
<td>224.4</td>
<td>149.6</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c7a.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.701235</td>
<td>1224.89</td>
<td>997.33</td>
<td>698.13</td>
<td>448.8</td>
<td>299.2</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c7a.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.402559</td>
<td>2449.84</td>
<td>1994.65</td>
<td>1396.26</td>
<td>897.59</td>
<td>598.4</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c7a.8xlarge</td>
<td>32</td>
<td>64</td>
<td>6.805118</td>
<td>4899.68</td>
<td>3989.3</td>
<td>2792.51</td>
<td>1795.19</td>
<td>1196.79</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c7a.16xlarge</td>
<td>64</td>
<td>128</td>
<td>13.610147</td>
<td>9799.31</td>
<td>7978.61</td>
<td>5585.03</td>
<td>3590.37</td>
<td>2393.58</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c7a.32xlarge</td>
<td>128</td>
<td>256</td>
<td>27.220383</td>
<td>19598.68</td>
<td>15957.21</td>
<td>11170.05</td>
<td>7180.75</td>
<td>4787.16</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g7a.large</td>
<td>2</td>
<td>8</td>
<td>0.480333</td>
<td>345.84</td>
<td>281.61</td>
<td>197.13</td>
<td>126.72</td>
<td>107.01</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g7a.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.960755</td>
<td>691.74</td>
<td>563.21</td>
<td>394.25</td>
<td>253.45</td>
<td>168.96</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g7a.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.92151</td>
<td>1383.49</td>
<td>1126.43</td>
<td>788.5</td>
<td>506.89</td>
<td>337.93</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g7a.4xlarge</td>
<td>16</td>
<td>64</td>
<td>3.84302</td>
<td>2766.97</td>
<td>2252.85</td>
<td>1577</td>
<td>1013.78</td>
<td>675.86</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g7a.8xlarge</td>
<td>32</td>
<td>128</td>
<td>7.685951</td>
<td>5533.88</td>
<td>4505.71</td>
<td>3154</td>
<td>2027.57</td>
<td>1351.71</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g7a.16xlarge</td>
<td>64</td>
<td>256</td>
<td>15.371991</td>
<td>11067.83</td>
<td>9011.41</td>
<td>6307.99</td>
<td>4055.13</td>
<td>2703.42</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g7a.32xlarge</td>
<td>128</td>
<td>512</td>
<td>30.743893</td>
<td>22135.6</td>
<td>18022.82</td>
<td>12615.98</td>
<td>8110.27</td>
<td>5406.85</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r7a.large</td>
<td>2</td>
<td>16</td>
<td>0.630476</td>
<td>453.94</td>
<td>369.61</td>
<td>258.73</td>
<td>166.33</td>
<td>110.88</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r7a.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.260952</td>
<td>907.89</td>
<td>739.22</td>
<td>517.46</td>
<td>332.65</td>
<td>221.77</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r7a.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.521993</td>
<td>1815.83</td>
<td>1478.45</td>
<td>1034.91</td>
<td>665.3</td>
<td>443.53</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r7a.4xlarge</td>
<td>16</td>
<td>128</td>
<td>5.043986</td>
<td>3631.67</td>
<td>2956.89</td>
<td>2069.83</td>
<td>1330.6</td>
<td>887.07</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r7a.8xlarge</td>
<td>32</td>
<td>256</td>
<td>10.087972</td>
<td>7263.34</td>
<td>5913.79</td>
<td>4139.65</td>
<td>2661.2</td>
<td>1774.14</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r7a.16xlarge</td>
<td>64</td>
<td>512</td>
<td>20.175855</td>
<td>14526.62</td>
<td>11827.57</td>
<td>8279.3</td>
<td>5322.41</td>
<td>3548.27</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r7a.32xlarge</td>
<td>128</td>
<td>1024</td>
<td>40.35171</td>
<td>29053.23</td>
<td>23655.15</td>
<td>16558.61</td>
<td>10644.82</td>
<td>7096.55</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c8g1.2xlarge</td>
<td>8</td>
<td>30</td>
<td>15.144184</td>
<td>10903.81</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>11545.21</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>12828.01</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-c48g1.12xlarge</td>
<td>48</td>
<td>310</td>
<td>21.380025</td>
<td>15393.62</td>
<td>10262.41</td>
<td>8723.05</td>
<td>5644.33</td>
<td>3899.72</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c56g1.14xlarge</td>
<td>56</td>
<td>346</td>
<td>25.65603</td>
<td>18472.34</td>
<td>12314.89</td>
<td>10467.66</td>
<td>6773.19</td>
<td>4679.66</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c32g1.16xlarge</td>
<td>64</td>
<td>376</td>
<td>35.633375</td>
<td>25656.03</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>51312.06</td>
<td>34208.04</td>
<td>29076.83</td>
<td>18814.42</td>
<td>12999.06</td>
</tr>
<tr>
<td>内存型弹性裸金属服务器 ecs.ebmre7p.32xlarge</td>
<td>128</td>
<td>512</td>
<td>75.643</td>
<td>54462.96</td>
<td>36308.81</td>
<td>36308.81</td>
<td>36308.81</td>
<td>36308.81</td>
</tr>
<tr>
<td>计算网络增强型 ecs.c7nex.large</td>
<td>2</td>
<td>4</td>
<td>0.592962</td>
<td>426.93</td>
<td>351.58</td>
<td>246.11</td>
<td>158.21</td>
<td>105.47</td>
</tr>
<tr>
<td>计算网络增强型 ecs.c7nex.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.185925</td>
<td>853.87</td>
<td>703.16</td>
<td>492.21</td>
<td>316.42</td>
<td>210.95</td>
</tr>
<tr>
<td>计算网络增强型 ecs.c7nex.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.372962</td>
<td>1708.53</td>
<td>1406.32</td>
<td>984.42</td>
<td>632.84</td>
<td>421.9</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g7nex.large</td>
<td>2</td>
<td>8</td>
<td>0.669725</td>
<td>482.2</td>
<td>432.74</td>
<td>302.92</td>
<td>194.73</td>
<td>129.82</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g7nex.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.33945</td>
<td>964.4</td>
<td>865.47</td>
<td>605.83</td>
<td>389.46</td>
<td>259.64</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g7nex.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.680012</td>
<td>1929.61</td>
<td>1730.95</td>
<td>1211.66</td>
<td>778.93</td>
<td>519.28</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c8g1.2xlarge</td>
<td>8</td>
<td>32</td>
<td>18.26</td>
<td>13147.2</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>52588.8</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>105177.6</td>
<td>66600.24</td>
<td>52579.14</td>
<td>31547.48</td>
<td>21031.66</td>
</tr>
<tr>
<td>通用型 ecs.g6.large</td>
<td>2</td>
<td>8</td>
<td>0.5785</td>
<td>416.52</td>
<td>300.85</td>
<td>210.59</td>
<td>135.38</td>
<td>114.32</td>
</tr>
<tr>
<td>通用型 ecs.g6.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.157</td>
<td>833.04</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>1666.08</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>2499.12</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>3332.16</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>4998.24</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>6664.32</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>10829.52</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>21659.04</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>7.79</td>
<td>5608.8</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>6537.6</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>8409.6</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>10684.8</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-c40g1.10xlarge</td>
<td>40</td>
<td>155</td>
<td>19.44</td>
<td>13996.8</td>
<td>9331.06</td>
<td>7931.4</td>
<td>5132.08</td>
<td>3545.8</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.12xlarge</td>
<td>48</td>
<td>186</td>
<td>29.69</td>
<td>21376.8</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>42760.8</td>
<td>28506.7</td>
<td>24230.7</td>
<td>15678.69</td>
<td>10832.55</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>24336</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>458.17</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>916.34</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>1832.69</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>3665.38</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>7330.75</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>11912.47</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>339.62</td>
<td>244.43</td>
<td>171.1</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>0.9434</td>
<td>679.25</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>1358.5</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>2037.74</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>2716.99</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>4075.49</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>5433.98</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>8830.22</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>17660.45</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>544.68</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>1089.36</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>2178.72</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>3268.08</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>4357.44</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>6536.16</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>8714.88</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>14161.68</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>28323.36</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>26.78</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>46.87</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>87.05</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>174.1</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>341.5</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>669.6</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>1339.2</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>390.89</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>781.78</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>1563.55</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>2345.33</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>3127.1</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>4690.66</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>6254.21</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>7817.76</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>12508.42</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>15635.52</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>454.97</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>909.94</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>1819.87</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>2729.81</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>3639.74</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>5459.62</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>7279.49</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>9099.36</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>14558.98</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>18198.72</td>
<td>13237.6</td>
<td>9266.32</td>
<td>5956.92</td>
<td>3971.28</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6e-c12g1.3xlarge</td>
<td>12</td>
<td>92</td>
<td>19.428</td>
<td>13988.16</td>
<td>9991.39</td>
<td>8492.68</td>
<td>5495.27</td>
<td>3796.73</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6e-c12g1.12xlarge</td>
<td>48</td>
<td>368</td>
<td>77.711</td>
<td>55951.92</td>
<td>39965.57</td>
<td>33970.74</td>
<td>21981.07</td>
<td>15186.92</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6e-c12g1.24xlarge</td>
<td>96</td>
<td>736</td>
<td>155.422</td>
<td>111903.84</td>
<td>79931.15</td>
<td>67941.47</td>
<td>43962.13</td>
<td>30373.84</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>595.94</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>1191.89</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>2383.78</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>3575.66</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>4767.55</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>7151.33</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>9535.1</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>11918.88</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>19070.21</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>23837.76</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>31824</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>599.15</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>1198.3</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>2396.59</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>4793.18</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>9586.37</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>15577.85</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>356.61</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>713.21</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>1426.42</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>2852.84</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>5705.68</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>9271.74</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>18543.47</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>10.79</td>
<td>7768.8</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>9360</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-c8g1.4xlarge</td>
<td>16</td>
<td>120</td>
<td>26.01</td>
<td>18727.2</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-c8g1.8xlarge</td>
<td>32</td>
<td>240</td>
<td>52.03</td>
<td>37461.6</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-c8g1.14xlarge</td>
<td>54</td>
<td>480</td>
<td>104.06</td>
<td>74923.2</td>
<td>47455.35</td>
<td>37464.75</td>
<td>22478.85</td>
<td>14985.9</td>
</tr>
<tr>
<td>计算型 ecs.c5.large</td>
<td>2</td>
<td>4</td>
<td>0.535</td>
<td>385.2</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>769.68</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>1534.32</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>2301.12</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>3063.6</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>4597.92</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>6126.48</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>12252.96</td>
<td>7863.88</td>
<td>6684.3</td>
<td>4325.13</td>
<td>2988.27</td>
</tr>
<tr>
<td>通用型 ecs.g5.large</td>
<td>2</td>
<td>8</td>
<td>0.677</td>
<td>487.44</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>974.16</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>1948.32</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>2922.48</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>3896.64</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>5844.24</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>7792.56</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>15584.4</td>
<td>9788.25</td>
<td>8320.01</td>
<td>5383.54</td>
<td>3719.54</td>
</tr>
<tr>
<td>内存型 ecs.r5.large</td>
<td>2</td>
<td>16</td>
<td>0.9</td>
<td>648</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>1296</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>2591.28</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>3886.56</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>5181.84</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>7773.12</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>10363.68</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>20726.64</td>
<td>13272.22</td>
<td>11281.39</td>
<td>7299.72</td>
<td>5043.44</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.large</td>
<td>2</td>
<td>4</td>
<td>0.643</td>
<td>462.96</td>
<td>280.8</td>
<td>221.68</td>
<td>133.01</td>
<td>88.67</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.286</td>
<td>925.92</td>
<td>561.54</td>
<td>443.32</td>
<td>265.99</td>
<td>177.33</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.564</td>
<td>1846.08</td>
<td>1123.01</td>
<td>886.59</td>
<td>531.95</td>
<td>354.64</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.849</td>
<td>2771.28</td>
<td>1684.55</td>
<td>1329.91</td>
<td>797.94</td>
<td>531.96</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.4xlarge</td>
<td>16</td>
<td>32</td>
<td>5.121</td>
<td>3687.12</td>
<td>2245.95</td>
<td>1773.12</td>
<td>1063.87</td>
<td>709.25</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.6xlarge</td>
<td>24</td>
<td>48</td>
<td>7.684</td>
<td>5532.48</td>
<td>3368.96</td>
<td>2659.7</td>
<td>1595.82</td>
<td>1063.88</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.8xlarge</td>
<td>32</td>
<td>64</td>
<td>10.241</td>
<td>7373.52</td>
<td>4491.89</td>
<td>3546.23</td>
<td>2127.74</td>
<td>1418.49</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.large</td>
<td>2</td>
<td>8</td>
<td>0.711</td>
<td>511.92</td>
<td>308.88</td>
<td>243.86</td>
<td>146.31</td>
<td>97.54</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.414</td>
<td>1018.08</td>
<td>617.7</td>
<td>487.66</td>
<td>292.59</td>
<td>195.06</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.821</td>
<td>2031.12</td>
<td>1235.33</td>
<td>975.26</td>
<td>585.16</td>
<td>390.1</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.3xlarge</td>
<td>12</td>
<td>48</td>
<td>4.235</td>
<td>3049.2</td>
<td>1853.02</td>
<td>1462.91</td>
<td>877.75</td>
<td>585.17</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.635</td>
<td>4057.2</td>
<td>2470.59</td>
<td>1950.47</td>
<td>1170.28</td>
<td>780.19</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.6xlarge</td>
<td>24</td>
<td>96</td>
<td>8.455</td>
<td>6087.6</td>
<td>3705.85</td>
<td>2925.67</td>
<td>1755.4</td>
<td>1170.27</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.269</td>
<td>8113.68</td>
<td>4941.11</td>
<td>3900.88</td>
<td>2340.53</td>
<td>1560.35</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.14xlarge</td>
<td>56</td>
<td>160</td>
<td>19.724</td>
<td>14201.28</td>
<td>8646.96</td>
<td>6826.54</td>
<td>4095.93</td>
<td>2730.62</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc2m1.nano</td>
<td>1</td>
<td>0.5</td>
<td>0.0372</td>
<td>26.78</td>
<td>16.15</td>
<td>12.75</td>
<td>7.65</td>
<td>5.1</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m1.small</td>
<td>1</td>
<td>1</td>
<td>0.0651</td>
<td>46.87</td>
<td>29.45</td>
<td>23.25</td>
<td>13.95</td>
<td>9.3</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m2.small</td>
<td>1</td>
<td>2</td>
<td>0.1116</td>
<td>80.35</td>
<td>47.5</td>
<td>37.5</td>
<td>22.5</td>
<td>15</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.1767</td>
<td>127.22</td>
<td>77.9</td>
<td>61.5</td>
<td>36.9</td>
<td>24.6</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.2418</td>
<td>174.1</td>
<td>108.3</td>
<td>85.5</td>
<td>51.3</td>
<td>34.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.3813</td>
<td>274.54</td>
<td>168.15</td>
<td>132.75</td>
<td>79.65</td>
<td>53.1</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.2046</td>
<td>147.31</td>
<td>95</td>
<td>75</td>
<td>45</td>
<td>30</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.3069</td>
<td>220.97</td>
<td>140.6</td>
<td>111</td>
<td>66.6</td>
<td>44.4</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.xlarge</td>
<td>4</td>
<td>4</td>
<td>0.3441</td>
<td>247.75</td>
<td>155.8</td>
<td>123</td>
<td>73.8</td>
<td>49.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.4836</td>
<td>348.19</td>
<td>215.65</td>
<td>170.25</td>
<td>102.15</td>
<td>68.1</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.7533</td>
<td>542.38</td>
<td>335.35</td>
<td>264.75</td>
<td>158.85</td>
<td>105.9</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.2xlarge</td>
<td>8</td>
<td>8</td>
<td>0.6975</td>
<td>502.2</td>
<td>311.6</td>
<td>246</td>
<td>147.6</td>
<td>98.4</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>0.9579</td>
<td>689.69</td>
<td>431.3</td>
<td>340.5</td>
<td>204.3</td>
<td>136.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.5066</td>
<td>1084.75</td>
<td>669.75</td>
<td>528.75</td>
<td>317.25</td>
<td>211.5</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.4xlarge</td>
<td>16</td>
<td>16</td>
<td>1.3857</td>
<td>997.7</td>
<td>621.3</td>
<td>490.5</td>
<td>294.3</td>
<td>196.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.4xlarge</td>
<td>16</td>
<td>32</td>
<td>1.9158</td>
<td>1379.38</td>
<td>861.65</td>
<td>680.25</td>
<td>408.15</td>
<td>272.1</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.large</td>
<td>2</td>
<td>2</td>
<td>0.51</td>
<td>367.2</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>734.4</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>1454.4</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>2188.8</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>2908.8</td>
<td>1868</td>
<td>1587.8</td>
<td>1027.4</td>
<td>709.84</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.6xlarge</td>
<td>24</td>
<td>24</td>
<td>6.07</td>
<td>4370.4</td>
<td>2802</td>
<td>2381.7</td>
<td>1541.1</td>
<td>1064.76</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.8xlarge</td>
<td>32</td>
<td>32</td>
<td>8.08</td>
<td>5817.6</td>
<td>3735</td>
<td>3174.75</td>
<td>2054.25</td>
<td>1419.3</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.16xlarge</td>
<td>64</td>
<td>64</td>
<td>16.17</td>
<td>11642.4</td>
<td>7471</td>
<td>6350.35</td>
<td>4109.05</td>
<td>2838.98</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.large</td>
<td>2</td>
<td>8</td>
<td>0.919528</td>
<td>662.06</td>
<td>379.11</td>
<td>265.38</td>
<td>170.6</td>
<td>113.73</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.839055</td>
<td>1324.12</td>
<td>758.22</td>
<td>530.75</td>
<td>341.2</td>
<td>227.47</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.79015</td>
<td>2008.91</td>
<td>1516.44</td>
<td>1061.51</td>
<td>682.4</td>
<td>454.93</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.5803</td>
<td>4017.82</td>
<td>3032.88</td>
<td>2123.02</td>
<td>1364.8</td>
<td>909.86</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.1606</td>
<td>8035.63</td>
<td>6065.76</td>
<td>4246.03</td>
<td>2729.59</td>
<td>1819.73</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.16xlarge</td>
<td>64</td>
<td>256</td>
<td>22.3212</td>
<td>16071.26</td>
<td>12131.52</td>
<td>8492.06</td>
<td>5459.18</td>
<td>3639.46</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.18xlarge</td>
<td>72</td>
<td>288</td>
<td>25.11135</td>
<td>18080.17</td>
<td>13647.96</td>
<td>9553.57</td>
<td>6141.58</td>
<td>4094.39</td>
</tr>
<tr>
<td>通用型 ecs.n4.small</td>
<td>1</td>
<td>2</td>
<td>0.161</td>
<td>115.92</td>
<td>85.39</td>
<td>72.58</td>
<td>42.7</td>
<td>42.7</td>
</tr>
<tr>
<td>通用型 ecs.n4.large</td>
<td>2</td>
<td>4</td>
<td>0.328</td>
<td>236.16</td>
<td>170.86</td>
<td>145.23</td>
<td>85.43</td>
<td>85.43</td>
</tr>
<tr>
<td>通用型 ecs.n4.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.177</td>
<td>847.44</td>
<td>544.6</td>
<td>462.91</td>
<td>272.3</td>
<td>272.3</td>
</tr>
<tr>
<td>通用型 ecs.n4.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.347</td>
<td>1689.84</td>
<td>1089.2</td>
<td>925.82</td>
<td>544.6</td>
<td>544.6</td>
</tr>
<tr>
<td>通用型 ecs.n4.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.686</td>
<td>3373.92</td>
<td>2178.4</td>
<td>1851.64</td>
<td>1089.2</td>
<td>1089.2</td>
</tr>
<tr>
<td>通用型 ecs.n4.8xlarge</td>
<td>32</td>
<td>64</td>
<td>9.373</td>
<td>6748.56</td>
<td>4356.8</td>
<td>3703.28</td>
<td>2178.4</td>
<td>2178.4</td>
</tr>
<tr>
<td>通用型 ecs.mn4.small</td>
<td>1</td>
<td>4</td>
<td>0.307</td>
<td>221.04</td>
<td>156.05</td>
<td>132.64</td>
<td>78.03</td>
<td>78.03</td>
</tr>
<tr>
<td>通用型 ecs.mn4.large</td>
<td>2</td>
<td>8</td>
<td>0.614</td>
<td>442.08</td>
<td>312.11</td>
<td>265.29</td>
<td>156.05</td>
<td>156.05</td>
</tr>
<tr>
<td>通用型 ecs.mn4.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.227</td>
<td>883.44</td>
<td>623.74</td>
<td>530.18</td>
<td>311.87</td>
<td>311.87</td>
</tr>
<tr>
<td>通用型 ecs.mn4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.459</td>
<td>1770.48</td>
<td>1247.42</td>
<td>1060.31</td>
<td>623.71</td>
<td>623.71</td>
</tr>
<tr>
<td>通用型 ecs.mn4.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.913</td>
<td>3537.36</td>
<td>2494.92</td>
<td>2120.68</td>
<td>1247.46</td>
<td>1247.46</td>
</tr>
<tr>
<td>通用型 ecs.mn4.8xlarge</td>
<td>32</td>
<td>128</td>
<td>9.815</td>
<td>7066.8</td>
<td>4989.84</td>
<td>4241.36</td>
<td>2494.92</td>
<td>2494.92</td>
</tr>
<tr>
<td>通用型 ecs.xn4.small</td>
<td>1</td>
<td>1</td>
<td>0.084</td>
<td>60.48</td>
<td>42.69</td>
<td>36.29</td>
<td>21.34</td>
<td>21.35</td>
</tr>
<tr>
<td>经济型 ecs.e4.small</td>
<td>1</td>
<td>8</td>
<td>0.459</td>
<td>330.48</td>
<td>213.33</td>
<td>181.33</td>
<td>106.67</td>
<td>106.66</td>
</tr>
<tr>
<td>本地SSD型 ecs.i4.large</td>
<td>2</td>
<td>16</td>
<td>1.0231</td>
<td>736.63</td>
<td>491.1</td>
<td>417.43</td>
<td>270.1</td>
<td>186.62</td>
</tr>
<tr>
<td>本地SSD型 ecs.i4.xlarge</td>
<td>4</td>
<td>32</td>
<td>2.0462</td>
<td>1473.26</td>
<td>982.2</td>
<td>834.87</td>
<td>540.21</td>
<td>373.23</td>
</tr>
<tr>
<td>本地SSD型 ecs.i4.2xlarge</td>
<td>8</td>
<td>64</td>
<td>4.0925</td>
<td>2946.6</td>
<td>1964.39</td>
<td>1669.73</td>
<td>1080.41</td>
<td>746.47</td>
</tr>
<tr>
<td>本地SSD型 ecs.i4.4xlarge</td>
<td>16</td>
<td>128</td>
<td>8.185</td>
<td>5893.2</td>
<td>3928.78</td>
<td>3339.46</td>
<td>2160.83</td>
<td>1492.94</td>
</tr>
<tr>
<td>本地SSD型 ecs.i4.8xlarge</td>
<td>32</td>
<td>256</td>
<td>16.3699</td>
<td>11786.33</td>
<td>7857.56</td>
<td>6678.93</td>
<td>4321.66</td>
<td>2985.87</td>
</tr>
<tr>
<td>本地SSD型 ecs.i4.16xlarge</td>
<td>64</td>
<td>512</td>
<td>32.7398</td>
<td>23572.66</td>
<td>15715.12</td>
<td>13357.86</td>
<td>8643.32</td>
<td>5971.75</td>
</tr>
<tr>
<td>本地SSD型 ecs.i4.32xlarge</td>
<td>128</td>
<td>1024</td>
<td>65.4797</td>
<td>47145.38</td>
<td>31430.25</td>
<td>26715.71</td>
<td>17286.64</td>
<td>11943.49</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.95978</td>
<td>1411.04</td>
<td>1055.38</td>
<td>738.77</td>
<td>474.92</td>
<td>316.61</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.91867</td>
<td>2821.44</td>
<td>2110.76</td>
<td>1477.53</td>
<td>949.84</td>
<td>633.23</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.83022</td>
<td>5637.76</td>
<td>4221.51</td>
<td>2955.06</td>
<td>1899.68</td>
<td>1266.45</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.8xlarge</td>
<td>32</td>
<td>256</td>
<td>15.66044</td>
<td>11275.52</td>
<td>8443.01</td>
<td>5910.11</td>
<td>3799.35</td>
<td>2532.9</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.13xlarge</td>
<td>52</td>
<td>384</td>
<td>23.48443</td>
<td>16908.79</td>
<td>12664.51</td>
<td>8865.16</td>
<td>5699.03</td>
<td>3799.35</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.26xlarge</td>
<td>104</td>
<td>768</td>
<td>46.96797</td>
<td>33816.94</td>
<td>25329.01</td>
<td>17730.31</td>
<td>11398.05</td>
<td>7598.7</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.61037</td>
<td>1879.47</td>
<td>1405.55</td>
<td>983.89</td>
<td>632.5</td>
<td>421.67</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.21451</td>
<td>3754.45</td>
<td>2811.09</td>
<td>1967.76</td>
<td>1264.99</td>
<td>843.33</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.8xlarge</td>
<td>32</td>
<td>128</td>
<td>10.42813</td>
<td>7508.25</td>
<td>5622.17</td>
<td>3935.52</td>
<td>2529.98</td>
<td>1686.65</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.13xlarge</td>
<td>52</td>
<td>192</td>
<td>15.64175</td>
<td>11262.06</td>
<td>8433.26</td>
<td>5903.28</td>
<td>3794.97</td>
<td>2529.98</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.26xlarge</td>
<td>104</td>
<td>384</td>
<td>31.27727</td>
<td>22519.63</td>
<td>16866.51</td>
<td>11806.56</td>
<td>7589.93</td>
<td>5059.95</td>
</tr>
<tr>
<td>ecs.sn2ne.large</td>
<td>2</td>
<td>8</td>
<td>0.725</td>
<td>522</td>
<td>327.71</td>
<td>278.55</td>
<td>180.24</td>
<td>124.53</td>
</tr>
<tr>
<td>ecs.sn2ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.449</td>
<td>1043.28</td>
<td>654.92</td>
<td>556.68</td>
<td>360.21</td>
<td>248.87</td>
</tr>
<tr>
<td>ecs.sn2ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.897</td>
<td>2085.84</td>
<td>1309.79</td>
<td>1113.32</td>
<td>720.38</td>
<td>497.72</td>
</tr>
<tr>
<td>ecs.sn2ne.3xlarge</td>
<td>12</td>
<td>48</td>
<td>4.35</td>
<td>3132</td>
<td>1966.26</td>
<td>1671.32</td>
<td>1081.44</td>
<td>747.18</td>
</tr>
<tr>
<td>ecs.sn2ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.793</td>
<td>4170.96</td>
<td>2619.66</td>
<td>2226.71</td>
<td>1440.81</td>
<td>995.47</td>
</tr>
<tr>
<td>ecs.sn2ne.6xlarge</td>
<td>24</td>
<td>96</td>
<td>8.7</td>
<td>6264</td>
<td>3932.52</td>
<td>3342.64</td>
<td>2162.89</td>
<td>1494.36</td>
</tr>
<tr>
<td>ecs.sn2ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.586</td>
<td>8341.92</td>
<td>5239.33</td>
<td>4453.43</td>
<td>2881.63</td>
<td>1990.95</td>
</tr>
<tr>
<td>ecs.sn2ne.14xlarge</td>
<td>56</td>
<td>224</td>
<td>20.275</td>
<td>14598</td>
<td>9176.19</td>
<td>7799.76</td>
<td>5046.9</td>
<td>3486.95</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.602</td>
<td>1153.44</td>
<td>894</td>
<td>625.8</td>
<td>402.3</td>
<td>268.2</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.1951</td>
<td>2300.47</td>
<td>1787</td>
<td>1250.9</td>
<td>804.15</td>
<td>536.1</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.4xlarge</td>
<td>16</td>
<td>128</td>
<td>6.3902</td>
<td>4600.94</td>
<td>3574</td>
<td>2501.8</td>
<td>1608.3</td>
<td>1072.2</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.8xlarge</td>
<td>32</td>
<td>256</td>
<td>12.7804</td>
<td>9201.89</td>
<td>7148</td>
<td>5003.6</td>
<td>3216.6</td>
<td>2144.4</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.16xlarge</td>
<td>64</td>
<td>512</td>
<td>25.5519</td>
<td>18397.37</td>
<td>14296</td>
<td>10007.2</td>
<td>6433.2</td>
<td>4288.8</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.62728</td>
<td>1891.64</td>
<td>1377.26</td>
<td>1014.82</td>
<td>652.39</td>
<td>434.93</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.25456</td>
<td>3783.28</td>
<td>2754.52</td>
<td>2029.65</td>
<td>1304.78</td>
<td>869.85</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.8xlarge</td>
<td>32</td>
<td>128</td>
<td>10.50912</td>
<td>7566.57</td>
<td>5509.05</td>
<td>4059.3</td>
<td>2609.55</td>
<td>1739.7</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.16xlarge</td>
<td>64</td>
<td>256</td>
<td>21.01824</td>
<td>15133.13</td>
<td>11018.1</td>
<td>8118.6</td>
<td>5219.1</td>
<td>3479.4</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.889999</td>
<td>1360.8</td>
<td>938.7</td>
<td>797.89</td>
<td>516.28</td>
<td>356.71</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.78</td>
<td>2721.6</td>
<td>1877.4</td>
<td>1595.79</td>
<td>1032.57</td>
<td>713.41</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.56</td>
<td>5443.2</td>
<td>3754.8</td>
<td>3191.58</td>
<td>2065.14</td>
<td>1426.82</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.8xlarge</td>
<td>32</td>
<td>256</td>
<td>15.12</td>
<td>10886.4</td>
<td>7509.6</td>
<td>6383.16</td>
<td>4130.28</td>
<td>2853.65</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.16xlarge</td>
<td>64</td>
<td>512</td>
<td>30.24</td>
<td>21772.8</td>
<td>15019.2</td>
<td>12766.32</td>
<td>8260.56</td>
<td>5707.3</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.20xlarge</td>
<td>80</td>
<td>704</td>
<td>37.8</td>
<td>27216</td>
<td>18774</td>
<td>15957.9</td>
<td>10325.7</td>
<td>7134.12</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2gne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.759</td>
<td>1986.48</td>
<td>1522.24</td>
<td>1065.57</td>
<td>685.01</td>
<td>456.67</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2gne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.518</td>
<td>3972.96</td>
<td>3044.48</td>
<td>2131.14</td>
<td>1370.02</td>
<td>913.34</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2gne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.03511</td>
<td>7945.28</td>
<td>6088.95</td>
<td>4262.27</td>
<td>2740.03</td>
<td>1826.69</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2gne.16xlarge</td>
<td>64</td>
<td>256</td>
<td>22.072</td>
<td>15891.84</td>
<td>12177.92</td>
<td>8524.54</td>
<td>5480.06</td>
<td>3653.38</td>
</tr>
<tr>
<td>大数据存储型 ecs.d2s.5xlarge</td>
<td>20</td>
<td>88</td>
<td>15.92032</td>
<td>11462.63</td>
<td>5151.29</td>
<td>3605.9</td>
<td>2318.08</td>
<td>1545.39</td>
</tr>
<tr>
<td>大数据存储型 ecs.d2s.10xlarge</td>
<td>40</td>
<td>176</td>
<td>31.84064</td>
<td>22925.26</td>
<td>10302.58</td>
<td>7211.81</td>
<td>4636.16</td>
<td>3090.77</td>
</tr>
<tr>
<td>大数据存储型 ecs.d2s.20xlarge</td>
<td>80</td>
<td>352</td>
<td>63.67505</td>
<td>45846.04</td>
<td>20605.12</td>
<td>14423.58</td>
<td>9272.3</td>
<td>6181.54</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.large</td>
<td>2</td>
<td>16</td>
<td>0.918</td>
<td>660.96</td>
<td>426.67</td>
<td>362.67</td>
<td>213.34</td>
<td>213.34</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.835</td>
<td>1321.2</td>
<td>832.45</td>
<td>707.58</td>
<td>416.23</td>
<td>416.23</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.669</td>
<td>2641.68</td>
<td>1644.02</td>
<td>1397.42</td>
<td>822.01</td>
<td>822.01</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.338</td>
<td>5283.36</td>
<td>3267.14</td>
<td>2777.07</td>
<td>1633.57</td>
<td>1633.57</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.8xlarge</td>
<td>32</td>
<td>256</td>
<td>14.675</td>
<td>10566</td>
<td>6513.38</td>
<td>5536.37</td>
<td>3256.69</td>
<td>3256.69</td>
</tr>
<tr>
<td>ecs.sn1ne.large</td>
<td>2</td>
<td>4</td>
<td>0.623</td>
<td>448.56</td>
<td>285.91</td>
<td>243.02</td>
<td>157.25</td>
<td>108.65</td>
</tr>
<tr>
<td>ecs.sn1ne.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.238</td>
<td>891.36</td>
<td>571.83</td>
<td>486.06</td>
<td>314.51</td>
<td>217.3</td>
</tr>
<tr>
<td>ecs.sn1ne.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.475</td>
<td>1782</td>
<td>1143.66</td>
<td>972.11</td>
<td>629.01</td>
<td>434.59</td>
</tr>
<tr>
<td>ecs.sn1ne.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.738</td>
<td>2691.36</td>
<td>1715.46</td>
<td>1458.14</td>
<td>943.5</td>
<td>651.87</td>
</tr>
<tr>
<td>ecs.sn1ne.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.95</td>
<td>3564</td>
<td>2287.32</td>
<td>1944.22</td>
<td>1258.03</td>
<td>869.18</td>
</tr>
<tr>
<td>ecs.sn1ne.6xlarge</td>
<td>24</td>
<td>48</td>
<td>7.476</td>
<td>5382.72</td>
<td>3430.92</td>
<td>2916.28</td>
<td>1887.01</td>
<td>1303.75</td>
</tr>
<tr>
<td>ecs.sn1ne.8xlarge</td>
<td>32</td>
<td>64</td>
<td>9.893</td>
<td>7122.96</td>
<td>4574.64</td>
<td>3888.44</td>
<td>2516.05</td>
<td>1738.36</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.large</td>
<td>2</td>
<td>16</td>
<td>0.964</td>
<td>694.08</td>
<td>448</td>
<td>380.8</td>
<td>246.4</td>
<td>170.24</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.927</td>
<td>1387.44</td>
<td>874.07</td>
<td>742.96</td>
<td>480.74</td>
<td>332.15</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.853</td>
<td>2774.16</td>
<td>1726.22</td>
<td>1467.29</td>
<td>949.42</td>
<td>655.96</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.3xlarge</td>
<td>12</td>
<td>96</td>
<td>5.784</td>
<td>4164.48</td>
<td>2688</td>
<td>2284.8</td>
<td>1478.4</td>
<td>1021.44</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.705</td>
<td>5547.6</td>
<td>3430.49</td>
<td>2915.92</td>
<td>1886.77</td>
<td>1303.59</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.6xlarge</td>
<td>24</td>
<td>192</td>
<td>11.568</td>
<td>8328.96</td>
<td>5376</td>
<td>4569.6</td>
<td>2956.8</td>
<td>2042.88</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.14xlarge</td>
<td>56</td>
<td>480</td>
<td>28.41</td>
<td>20455.2</td>
<td>13216.33</td>
<td>11233.88</td>
<td>7268.98</td>
<td>5022.21</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>3268.08</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>6540.48</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>9813.6</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.8xlarge</td>
<td>32</td>
<td>128</td>
<td>18.168</td>
<td>13080.96</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-c8d3.8xlarge</td>
<td>32</td>
<td>128</td>
<td>17.44</td>
<td>12556.8</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.14xlarge</td>
<td>56</td>
<td>224</td>
<td>31.804</td>
<td>22898.88</td>
<td>14502.3</td>
<td>11449.18</td>
<td>6869.51</td>
<td>4579.67</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>19051.2</td>
<td>12069.75</td>
<td>9528.75</td>
<td>5717.25</td>
<td>3811.5</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.1958</td>
<td>140.98</td>
<td>90.19</td>
<td>76.66</td>
<td>49.6</td>
<td>34.27</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.4352</td>
<td>313.34</td>
<td>199.95</td>
<td>169.96</td>
<td>109.97</td>
<td>75.98</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.0979</td>
<td>70.49</td>
<td>45.07</td>
<td>38.31</td>
<td>24.79</td>
<td>17.13</td>
</tr>
<tr>
<td>经济型 ecs.e-c4m1.large</td>
<td>2</td>
<td>0.5</td>
<td>0.0272</td>
<td>19.58</td>
<td>12.33</td>
<td>10.48</td>
<td>6.78</td>
<td>4.69</td>
</tr>
<tr>
<td>经济型 ecs.e-c2m1.large</td>
<td>2</td>
<td>1</td>
<td>0.0544</td>
<td>39.17</td>
<td>25.07</td>
<td>21.31</td>
<td>13.79</td>
<td>9.53</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.8704</td>
<td>626.69</td>
<td>400.37</td>
<td>340.32</td>
<td>220.21</td>
<td>152.14</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.5832</td>
<td>419.9</td>
<td>268.25</td>
<td>228.01</td>
<td>147.54</td>
<td>101.94</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.7408</td>
<td>1253.38</td>
<td>800.75</td>
<td>680.63</td>
<td>440.41</td>
<td>304.28</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.1664</td>
<td>839.81</td>
<td>536.5</td>
<td>456.03</td>
<td>295.08</td>
<td>203.87</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美国地域收费标准之后，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82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。
<h3>第一步：领取新用户满减优惠券或代金券</h3>
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。
<h3>第二步：参与专属活动获取优惠</h3>
除了领取优惠券和代金券外，用户还可以通过参与阿里云的专属活动来获取国外云服务器的优惠。以下是两个值得关注的活动：
活动一：云服务器新人特惠活动
该活动专为新用户设计，提供了购买国外地域云服务器的特惠价格。用户可以在活动页面选择多个国外地域的云服务器，并享受优惠价格。此外，活动还提供了多种实例类型和配置供用户选择，满足不同场景下的需求。通过参与该活动，新用户可以在初次购买时即享受到较大的优惠。
活动二： 全球云服务器精选特惠
该活动不仅提供了国外地域的轻量应用服务器的优惠价格，还不定期上架一些国外地域的云服务器ECS产品。用户可以在活动页面查看最新的优惠信息和产品列表，并选择适合自己的云服务器进行购买。通过参与该活动，用户可以及时获取到最新的优惠信息，并在购买时享受到相应的折扣。活动地址：https://www.aliyun.com/daily-act/ecs/activity_global



https://upload-images.jianshu.io/upload_images/19316870-17951fd9ad1fd5fd.png




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

<h3>第三步：下单购买并使用满减优惠券</h3>
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



通过以上详细的购买指南和优惠技巧，相信您已经对如何选购阿里云美国地域的云服务器有了全面的了解。结合地域选择、实例规格、操作系统、云盘配置、购买时长及带宽规划等多方面的考量，您能够更精准地找到满足需求的云服务器配置。同时，利用新用户满减优惠券和参与专属活动，您将能以更优惠的价格购得心仪的云服务器。

查看完整版本: 阿里云服务器美国地域多少钱？美国地域最新收费标准及便宜购买教程