阿里云服务器青岛地域多少钱？青岛地域最新收费标准及便宜购买教程

翰宫 · 发表于 2024-10-5 22:53:58

阿里云服务器在国内有十几个地域可选，青岛地域主要适合北方用户选择，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青岛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。

一、阿里云服务器青岛地域接入点及运营商介绍
阿里云服务器青岛地域有两个接入点，运营商为联通和中立。
<table>
<thead>
<tr>
<th>地域</th>
<th>接入点</th>
<th>运营商</th>
<th>附近的建筑物</th>
</tr>
</thead>
<tbody>
<tr>
<td>华北1（青岛）</td>
<td>青岛-崂山-A</td>
<td>联通</td>
<td>青岛国际高尔夫俱乐部</td>
</tr>
<tr>
<td>华北1（青岛）</td>
<td>青岛-李沧-A</td>
<td>中立</td>
<td>青岛恒星科技学院</td>
</tr>
</tbody>
</table>

二、阿里云服务器青岛地域最新收费标准
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青岛地域最新收费标准，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>标准目录月价</th>
<th>优惠月价</th>
<th>年付月价</th>
<th>3年付月价</th>
<th>5年付月价</th>
</tr>
</thead>
<tbody>
<tr>
<td>通用算力型 ecs.u1-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.45</td>
<td>216</td>
<td>216</td>
<td>116.64</td>
<td>75.6</td>
<td>51.84</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.351</td>
<td>168.48</td>
<td>168.48</td>
<td>90.98</td>
<td>58.97</td>
<td>40.44</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.large</td>
<td>2</td>
<td>16</td>
<td>0.59625</td>
<td>286.2</td>
<td>286.2</td>
<td>154.55</td>
<td>100.17</td>
<td>68.69</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.33375</td>
<td>160.2</td>
<td>160.2</td>
<td>86.51</td>
<td>56.07</td>
<td>38.45</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.xlarge</td>
<td>4</td>
<td>4</td>
<td>0.6675</td>
<td>320.4</td>
<td>320.4</td>
<td>173.02</td>
<td>112.14</td>
<td>76.9</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.1925</td>
<td>572.4</td>
<td>572.4</td>
<td>309.1</td>
<td>200.34</td>
<td>137.38</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.702</td>
<td>336.96</td>
<td>336.96</td>
<td>181.96</td>
<td>117.94</td>
<td>80.87</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.9</td>
<td>432</td>
<td>432</td>
<td>233.28</td>
<td>151.2</td>
<td>103.68</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.8</td>
<td>864</td>
<td>864</td>
<td>466.56</td>
<td>302.4</td>
<td>207.36</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.404</td>
<td>673.92</td>
<td>673.92</td>
<td>363.92</td>
<td>235.87</td>
<td>161.74</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.385</td>
<td>1144.8</td>
<td>1144.8</td>
<td>618.19</td>
<td>400.68</td>
<td>274.75</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.2xlarge</td>
<td>8</td>
<td>8</td>
<td>1.335</td>
<td>640.8</td>
<td>640.8</td>
<td>346.03</td>
<td>224.28</td>
<td>153.79</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.3xlarge</td>
<td>12</td>
<td>48</td>
<td>2.7</td>
<td>1296</td>
<td>1296</td>
<td>699.84</td>
<td>453.6</td>
<td>311.04</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.3xlarge</td>
<td>12</td>
<td>12</td>
<td>2.0025</td>
<td>961.2</td>
<td>961.2</td>
<td>519.05</td>
<td>336.42</td>
<td>230.69</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.106</td>
<td>1010.88</td>
<td>1010.88</td>
<td>545.88</td>
<td>353.81</td>
<td>242.61</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.3xlarge</td>
<td>12</td>
<td>96</td>
<td>3.5775</td>
<td>1717.2</td>
<td>1717.2</td>
<td>927.29</td>
<td>601.02</td>
<td>412.13</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.4xlarge</td>
<td>16</td>
<td>16</td>
<td>2.67</td>
<td>1281.6</td>
<td>1281.6</td>
<td>692.06</td>
<td>448.56</td>
<td>307.58</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.4xlarge</td>
<td>16</td>
<td>128</td>
<td>4.77</td>
<td>2289.6</td>
<td>2289.6</td>
<td>1236.38</td>
<td>801.36</td>
<td>549.5</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.4xlarge</td>
<td>16</td>
<td>64</td>
<td>3.6</td>
<td>1728</td>
<td>1728</td>
<td>933.12</td>
<td>604.8</td>
<td>414.72</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.4xlarge</td>
<td>16</td>
<td>32</td>
<td>2.808</td>
<td>1347.84</td>
<td>1347.84</td>
<td>727.83</td>
<td>471.74</td>
<td>323.48</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m4.8xlarge</td>
<td>32</td>
<td>128</td>
<td>7.2</td>
<td>3456</td>
<td>3456</td>
<td>1866.24</td>
<td>1209.6</td>
<td>829.44</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m8.8xlarge</td>
<td>32</td>
<td>256</td>
<td>9.54</td>
<td>4579.2</td>
<td>4579.2</td>
<td>2472.77</td>
<td>1602.72</td>
<td>1099.01</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m2.8xlarge</td>
<td>32</td>
<td>64</td>
<td>5.616</td>
<td>2695.68</td>
<td>2695.68</td>
<td>1455.67</td>
<td>943.49</td>
<td>646.96</td>
</tr>
<tr>
<td>通用算力型 ecs.u1-c1m1.8xlarge</td>
<td>32</td>
<td>32</td>
<td>5.34</td>
<td>2563.2</td>
<td>2563.2</td>
<td>1384.13</td>
<td>897.12</td>
<td>615.17</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c8g1.2xlarge</td>
<td>8</td>
<td>32</td>
<td>26.46</td>
<td>7620</td>
<td>4572</td>
<td>3429</td>
<td>2209.8</td>
<td>2209.8</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c8g1.8xlarge</td>
<td>32</td>
<td>128</td>
<td>105.84</td>
<td>30480</td>
<td>18288</td>
<td>13716</td>
<td>8839.2</td>
<td>8839.2</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c8g1.16xlarge</td>
<td>64</td>
<td>256</td>
<td>211.68</td>
<td>60960</td>
<td>36576</td>
<td>27432</td>
<td>17678.4</td>
<td>17678.4</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6v-c10g1.20xlarge</td>
<td>82</td>
<td>336</td>
<td>219.64</td>
<td>63255</td>
<td>37953</td>
<td>28464.75</td>
<td>18343.95</td>
<td>18343.95</td>
</tr>
<tr>
<td>通用型 ecs.g6.large</td>
<td>2</td>
<td>8</td>
<td>0.5</td>
<td>240</td>
<td>240</td>
<td>156</td>
<td>103.2</td>
<td>72</td>
</tr>
<tr>
<td>通用型 ecs.g6.xlarge</td>
<td>4</td>
<td>16</td>
<td>1</td>
<td>480</td>
<td>480</td>
<td>312</td>
<td>206.4</td>
<td>144</td>
</tr>
<tr>
<td>通用型 ecs.g6.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2</td>
<td>960</td>
<td>960</td>
<td>624</td>
<td>412.8</td>
<td>288</td>
</tr>
<tr>
<td>通用型 ecs.g6.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3</td>
<td>1440</td>
<td>1440</td>
<td>936</td>
<td>619.2</td>
<td>432</td>
</tr>
<tr>
<td>通用型 ecs.g6.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4</td>
<td>1920</td>
<td>1920</td>
<td>1248</td>
<td>825.6</td>
<td>576</td>
</tr>
<tr>
<td>通用型 ecs.g6.6xlarge</td>
<td>24</td>
<td>96</td>
<td>6</td>
<td>2880</td>
<td>2880</td>
<td>1872</td>
<td>1238.4</td>
<td>864</td>
</tr>
<tr>
<td>通用型 ecs.g6.8xlarge</td>
<td>32</td>
<td>128</td>
<td>8</td>
<td>3840</td>
<td>3840</td>
<td>2496</td>
<td>1651.2</td>
<td>1152</td>
</tr>
<tr>
<td>通用型 ecs.g6.13xlarge</td>
<td>52</td>
<td>192</td>
<td>13</td>
<td>6240</td>
<td>6240</td>
<td>4056</td>
<td>2683.2</td>
<td>1872</td>
</tr>
<tr>
<td>通用型 ecs.g6.26xlarge</td>
<td>104</td>
<td>384</td>
<td>26</td>
<td>12480</td>
<td>12480</td>
<td>8112</td>
<td>5366.4</td>
<td>3744</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c4g1.xlarge</td>
<td>4</td>
<td>15</td>
<td>11.63</td>
<td>3348</td>
<td>3348</td>
<td>1674</td>
<td>1071.36</td>
<td>1071.36</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c8g1.2xlarge</td>
<td>8</td>
<td>31</td>
<td>14</td>
<td>4032</td>
<td>4032</td>
<td>2016</td>
<td>1290.24</td>
<td>1290.24</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c16g1.4xlarge</td>
<td>16</td>
<td>62</td>
<td>16.41</td>
<td>4725</td>
<td>4725</td>
<td>2362.5</td>
<td>1512</td>
<td>1512</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.6xlarge</td>
<td>24</td>
<td>93</td>
<td>17.19</td>
<td>4950</td>
<td>4950</td>
<td>2475</td>
<td>1584</td>
<td>1584</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c40g1.10xlarge</td>
<td>40</td>
<td>155</td>
<td>14.819</td>
<td>7112.9</td>
<td>7112.9</td>
<td>3556.45</td>
<td>2276.13</td>
<td>2276.13</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.12xlarge</td>
<td>48</td>
<td>186</td>
<td>34.38</td>
<td>9900</td>
<td>9900</td>
<td>4950</td>
<td>3168</td>
<td>3168</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn6i-c24g1.24xlarge</td>
<td>96</td>
<td>372</td>
<td>68.75</td>
<td>19800</td>
<td>19800</td>
<td>9900</td>
<td>6336</td>
<td>6336</td>
</tr>
<tr>
<td>计算型 ecs.c6.large</td>
<td>2</td>
<td>4</td>
<td>0.39</td>
<td>187</td>
<td>187</td>
<td>121.55</td>
<td>80.41</td>
<td>56.1</td>
</tr>
<tr>
<td>计算型 ecs.c6.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.78</td>
<td>374</td>
<td>374</td>
<td>243.1</td>
<td>160.82</td>
<td>112.2</td>
</tr>
<tr>
<td>计算型 ecs.c6.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.56</td>
<td>748</td>
<td>748</td>
<td>486.2</td>
<td>321.64</td>
<td>224.4</td>
</tr>
<tr>
<td>计算型 ecs.c6.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.34</td>
<td>1122</td>
<td>1122</td>
<td>729.3</td>
<td>482.46</td>
<td>336.6</td>
</tr>
<tr>
<td>计算型 ecs.c6.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.12</td>
<td>1496</td>
<td>1496</td>
<td>972.4</td>
<td>643.28</td>
<td>448.8</td>
</tr>
<tr>
<td>计算型 ecs.c6.6xlarge</td>
<td>24</td>
<td>48</td>
<td>4.68</td>
<td>2244</td>
<td>2244</td>
<td>1458.6</td>
<td>964.92</td>
<td>673.2</td>
</tr>
<tr>
<td>计算型 ecs.c6.8xlarge</td>
<td>32</td>
<td>64</td>
<td>6.23</td>
<td>2992</td>
<td>2992</td>
<td>1944.8</td>
<td>1286.56</td>
<td>897.6</td>
</tr>
<tr>
<td>计算型 ecs.c6.13xlarge</td>
<td>52</td>
<td>96</td>
<td>10.13</td>
<td>4862</td>
<td>4862</td>
<td>3160.3</td>
<td>2090.66</td>
<td>1458.6</td>
</tr>
<tr>
<td>计算型 ecs.c6.26xlarge</td>
<td>104</td>
<td>192</td>
<td>20.26</td>
<td>9724</td>
<td>9724</td>
<td>6320.6</td>
<td>4181.32</td>
<td>2917.2</td>
</tr>
<tr>
<td>内存型 ecs.r6.large</td>
<td>2</td>
<td>16</td>
<td>0.66</td>
<td>318</td>
<td>318</td>
<td>206.7</td>
<td>136.74</td>
<td>95.4</td>
</tr>
<tr>
<td>内存型 ecs.r6.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.33</td>
<td>636</td>
<td>636</td>
<td>413.4</td>
<td>273.48</td>
<td>190.8</td>
</tr>
<tr>
<td>内存型 ecs.r6.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.65</td>
<td>1272</td>
<td>1272</td>
<td>826.8</td>
<td>546.96</td>
<td>381.6</td>
</tr>
<tr>
<td>内存型 ecs.r6.3xlarge</td>
<td>12</td>
<td>96</td>
<td>3.98</td>
<td>1908</td>
<td>1908</td>
<td>1240.2</td>
<td>820.44</td>
<td>572.4</td>
</tr>
<tr>
<td>内存型 ecs.r6.4xlarge</td>
<td>16</td>
<td>128</td>
<td>5.3</td>
<td>2544</td>
<td>2544</td>
<td>1653.6</td>
<td>1093.92</td>
<td>763.2</td>
</tr>
<tr>
<td>内存型 ecs.r6.6xlarge</td>
<td>24</td>
<td>192</td>
<td>7.95</td>
<td>3816</td>
<td>3816</td>
<td>2480.4</td>
<td>1640.88</td>
<td>1144.8</td>
</tr>
<tr>
<td>内存型 ecs.r6.8xlarge</td>
<td>32</td>
<td>256</td>
<td>10.6</td>
<td>5088</td>
<td>5088</td>
<td>3307.2</td>
<td>2187.84</td>
<td>1526.4</td>
</tr>
<tr>
<td>内存型 ecs.r6.13xlarge</td>
<td>52</td>
<td>384</td>
<td>17.23</td>
<td>8268</td>
<td>8268</td>
<td>5374.2</td>
<td>3555.24</td>
<td>2480.4</td>
</tr>
<tr>
<td>内存型 ecs.r6.26xlarge</td>
<td>104</td>
<td>768</td>
<td>34.45</td>
<td>16536</td>
<td>16536</td>
<td>10748.4</td>
<td>7110.48</td>
<td>4960.8</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>34.45</td>
<td>16536</td>
<td>16536</td>
<td>14055.6</td>
<td>9094.8</td>
<td>6283.68</td>
</tr>
<tr>
<td>计算型 ecs.c5.large</td>
<td>2</td>
<td>4</td>
<td>0.62</td>
<td>179</td>
<td>179</td>
<td>152.15</td>
<td>98.45</td>
<td>68.02</td>
</tr>
<tr>
<td>计算型 ecs.c5.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.24</td>
<td>358</td>
<td>358</td>
<td>304.3</td>
<td>196.9</td>
<td>136.04</td>
</tr>
<tr>
<td>计算型 ecs.c5.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.49</td>
<td>716</td>
<td>716</td>
<td>608.6</td>
<td>393.8</td>
<td>272.08</td>
</tr>
<tr>
<td>计算型 ecs.c5.3xlarge</td>
<td>12</td>
<td>24</td>
<td>3.73</td>
<td>1074</td>
<td>1074</td>
<td>912.9</td>
<td>590.7</td>
<td>408.12</td>
</tr>
<tr>
<td>计算型 ecs.c5.4xlarge</td>
<td>16</td>
<td>32</td>
<td>4.97</td>
<td>1432</td>
<td>1432</td>
<td>1217.2</td>
<td>787.6</td>
<td>544.16</td>
</tr>
<tr>
<td>计算型 ecs.c5.6xlarge</td>
<td>24</td>
<td>48</td>
<td>7.46</td>
<td>2148</td>
<td>2148</td>
<td>1825.8</td>
<td>1181.4</td>
<td>816.24</td>
</tr>
<tr>
<td>计算型 ecs.c5.8xlarge</td>
<td>32</td>
<td>64</td>
<td>9.94</td>
<td>2864</td>
<td>2864</td>
<td>2434.4</td>
<td>1575.2</td>
<td>1088.32</td>
</tr>
<tr>
<td>计算型 ecs.c5.16xlarge</td>
<td>64</td>
<td>128</td>
<td>19.89</td>
<td>5728</td>
<td>5728</td>
<td>4868.8</td>
<td>3150.4</td>
<td>2176.64</td>
</tr>
<tr>
<td>通用型 ecs.g5.large</td>
<td>2</td>
<td>8</td>
<td>0.89</td>
<td>255</td>
<td>255</td>
<td>216.75</td>
<td>140.25</td>
<td>96.9</td>
</tr>
<tr>
<td>通用型 ecs.g5.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.77</td>
<td>510</td>
<td>510</td>
<td>433.5</td>
<td>280.5</td>
<td>193.8</td>
</tr>
<tr>
<td>通用型 ecs.g5.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.54</td>
<td>1020</td>
<td>1020</td>
<td>867</td>
<td>561</td>
<td>387.6</td>
</tr>
<tr>
<td>通用型 ecs.g5.3xlarge</td>
<td>12</td>
<td>48</td>
<td>5.31</td>
<td>1530</td>
<td>1530</td>
<td>1300.5</td>
<td>841.5</td>
<td>581.4</td>
</tr>
<tr>
<td>通用型 ecs.g5.4xlarge</td>
<td>16</td>
<td>64</td>
<td>7.08</td>
<td>2040</td>
<td>2040</td>
<td>1734</td>
<td>1122</td>
<td>775.2</td>
</tr>
<tr>
<td>通用型 ecs.g5.6xlarge</td>
<td>24</td>
<td>96</td>
<td>10.63</td>
<td>3060</td>
<td>3060</td>
<td>2601</td>
<td>1683</td>
<td>1162.8</td>
</tr>
<tr>
<td>通用型 ecs.g5.8xlarge</td>
<td>32</td>
<td>128</td>
<td>14.17</td>
<td>4080</td>
<td>4080</td>
<td>3468</td>
<td>2244</td>
<td>1550.4</td>
</tr>
<tr>
<td>通用型 ecs.g5.16xlarge</td>
<td>64</td>
<td>256</td>
<td>28.33</td>
<td>8160</td>
<td>8160</td>
<td>6936</td>
<td>4488</td>
<td>3100.8</td>
</tr>
<tr>
<td>内存型 ecs.r5.large</td>
<td>2</td>
<td>16</td>
<td>1.13</td>
<td>326</td>
<td>326</td>
<td>277.1</td>
<td>179.3</td>
<td>123.88</td>
</tr>
<tr>
<td>内存型 ecs.r5.xlarge</td>
<td>4</td>
<td>32</td>
<td>2.26</td>
<td>652</td>
<td>652</td>
<td>554.2</td>
<td>358.6</td>
<td>247.76</td>
</tr>
<tr>
<td>内存型 ecs.r5.2xlarge</td>
<td>8</td>
<td>64</td>
<td>4.53</td>
<td>1304</td>
<td>1304</td>
<td>1108.4</td>
<td>717.2</td>
<td>495.52</td>
</tr>
<tr>
<td>内存型 ecs.r5.3xlarge</td>
<td>12</td>
<td>96</td>
<td>6.79</td>
<td>1956</td>
<td>1956</td>
<td>1662.6</td>
<td>1075.8</td>
<td>743.28</td>
</tr>
<tr>
<td>内存型 ecs.r5.4xlarge</td>
<td>16</td>
<td>128</td>
<td>9.06</td>
<td>2608</td>
<td>2608</td>
<td>2216.8</td>
<td>1434.4</td>
<td>991.04</td>
</tr>
<tr>
<td>内存型 ecs.r5.6xlarge</td>
<td>24</td>
<td>192</td>
<td>13.58</td>
<td>3912</td>
<td>3912</td>
<td>3325.2</td>
<td>2151.6</td>
<td>1486.56</td>
</tr>
<tr>
<td>内存型 ecs.r5.8xlarge</td>
<td>32</td>
<td>256</td>
<td>18.11</td>
<td>5216</td>
<td>5216</td>
<td>4433.6</td>
<td>2868.8</td>
<td>1982.08</td>
</tr>
<tr>
<td>内存型 ecs.r5.16xlarge</td>
<td>64</td>
<td>512</td>
<td>36.22</td>
<td>10432</td>
<td>10432</td>
<td>8867.2</td>
<td>5737.6</td>
<td>3964.16</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.large</td>
<td>2</td>
<td>4</td>
<td>0.87</td>
<td>251</td>
<td>251</td>
<td>208.33</td>
<td>125.5</td>
<td>82.83</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.74</td>
<td>502</td>
<td>502</td>
<td>416.66</td>
<td>251</td>
<td>165.66</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.2xlarge</td>
<td>8</td>
<td>16</td>
<td>3.49</td>
<td>1004</td>
<td>1004</td>
<td>833.32</td>
<td>502</td>
<td>331.32</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.3xlarge</td>
<td>12</td>
<td>24</td>
<td>5.23</td>
<td>1506</td>
<td>1506</td>
<td>1249.98</td>
<td>753</td>
<td>496.98</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.4xlarge</td>
<td>16</td>
<td>32</td>
<td>6.97</td>
<td>2008</td>
<td>2008</td>
<td>1666.64</td>
<td>1004</td>
<td>662.64</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.6xlarge</td>
<td>24</td>
<td>48</td>
<td>10.46</td>
<td>3012</td>
<td>3012</td>
<td>2499.96</td>
<td>1506</td>
<td>993.96</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc5.8xlarge</td>
<td>32</td>
<td>64</td>
<td>13.94</td>
<td>4016</td>
<td>4016</td>
<td>3333.28</td>
<td>2008</td>
<td>1325.28</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.large</td>
<td>2</td>
<td>8</td>
<td>1.15</td>
<td>332</td>
<td>332</td>
<td>268.92</td>
<td>162.68</td>
<td>106.24</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.xlarge</td>
<td>4</td>
<td>16</td>
<td>2.31</td>
<td>664</td>
<td>664</td>
<td>537.84</td>
<td>325.36</td>
<td>212.48</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.2xlarge</td>
<td>8</td>
<td>32</td>
<td>4.61</td>
<td>1328</td>
<td>1328</td>
<td>1075.68</td>
<td>650.72</td>
<td>424.96</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.3xlarge</td>
<td>12</td>
<td>48</td>
<td>6.92</td>
<td>1992</td>
<td>1992</td>
<td>1613.52</td>
<td>976.08</td>
<td>637.44</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.4xlarge</td>
<td>16</td>
<td>64</td>
<td>9.22</td>
<td>2656</td>
<td>2656</td>
<td>2151.36</td>
<td>1301.44</td>
<td>849.92</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.6xlarge</td>
<td>24</td>
<td>96</td>
<td>13.83</td>
<td>3984</td>
<td>3984</td>
<td>3227.04</td>
<td>1952.16</td>
<td>1274.88</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.8xlarge</td>
<td>32</td>
<td>128</td>
<td>18.44</td>
<td>5312</td>
<td>5312</td>
<td>4302.72</td>
<td>2602.88</td>
<td>1699.84</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg5.14xlarge</td>
<td>56</td>
<td>160</td>
<td>30.58</td>
<td>8808</td>
<td>8808</td>
<td>7134.48</td>
<td>4315.92</td>
<td>2818.56</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5i-c2g1.large</td>
<td>2</td>
<td>8</td>
<td>8.68</td>
<td>2500</td>
<td>2375</td>
<td>1875</td>
<td>1125</td>
<td>750</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5i-c4g1.xlarge</td>
<td>4</td>
<td>16</td>
<td>9.69</td>
<td>2790</td>
<td>2650.5</td>
<td>2092.5</td>
<td>1255.5</td>
<td>837</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5i-c8g1.2xlarge</td>
<td>8</td>
<td>32</td>
<td>11.67</td>
<td>3360</td>
<td>3192</td>
<td>2520</td>
<td>1512</td>
<td>1008</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5i-c16g1.4xlarge</td>
<td>16</td>
<td>64</td>
<td>15.63</td>
<td>4500</td>
<td>4275</td>
<td>3375</td>
<td>2025</td>
<td>1350</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5i-c16g1.8xlarge</td>
<td>32</td>
<td>128</td>
<td>31.25</td>
<td>9000</td>
<td>8550</td>
<td>6750</td>
<td>4050</td>
<td>2700</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5i-c28g1.14xlarge</td>
<td>56</td>
<td>224</td>
<td>43.06</td>
<td>12400</td>
<td>11780</td>
<td>9300</td>
<td>5580</td>
<td>3720</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc2m1.nano</td>
<td>1</td>
<td>0.5</td>
<td>0.063</td>
<td>18</td>
<td>17.1</td>
<td>13.5</td>
<td>8.1</td>
<td>5.4</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m1.small</td>
<td>1</td>
<td>1</td>
<td>0.083</td>
<td>24</td>
<td>22.8</td>
<td>18</td>
<td>10.8</td>
<td>7.2</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m2.small</td>
<td>1</td>
<td>2</td>
<td>0.167</td>
<td>48</td>
<td>45.6</td>
<td>36</td>
<td>21.6</td>
<td>14.4</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.29</td>
<td>83</td>
<td>78.85</td>
<td>62.25</td>
<td>37.35</td>
<td>24.9</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.4</td>
<td>116</td>
<td>110.2</td>
<td>87</td>
<td>52.2</td>
<td>34.8</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.63</td>
<td>180</td>
<td>171</td>
<td>135</td>
<td>81</td>
<td>54</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.333</td>
<td>96</td>
<td>91.2</td>
<td>72</td>
<td>43.2</td>
<td>28.8</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-lc1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.55</td>
<td>159</td>
<td>151.05</td>
<td>119.25</td>
<td>71.55</td>
<td>47.7</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.xlarge</td>
<td>4</td>
<td>4</td>
<td>0.58</td>
<td>167</td>
<td>158.65</td>
<td>125.25</td>
<td>75.15</td>
<td>50.1</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.8</td>
<td>231</td>
<td>219.45</td>
<td>173.25</td>
<td>103.95</td>
<td>69.3</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.25</td>
<td>360</td>
<td>342</td>
<td>270</td>
<td>162</td>
<td>108</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.2xlarge</td>
<td>8</td>
<td>8</td>
<td>1.16</td>
<td>333</td>
<td>316.35</td>
<td>249.75</td>
<td>149.85</td>
<td>99.9</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.6</td>
<td>462</td>
<td>438.9</td>
<td>346.5</td>
<td>207.9</td>
<td>138.6</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.5</td>
<td>720</td>
<td>684</td>
<td>540</td>
<td>324</td>
<td>216</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m1.4xlarge</td>
<td>16</td>
<td>16</td>
<td>2.31</td>
<td>666</td>
<td>632.7</td>
<td>499.5</td>
<td>299.7</td>
<td>199.8</td>
</tr>
<tr>
<td>突发性能型 ecs.t5-c1m2.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.21</td>
<td>924</td>
<td>877.8</td>
<td>693</td>
<td>415.8</td>
<td>277.2</td>
</tr>
<tr>
<td>高主频型超级计算集群 ecs.scch5.16xlarge</td>
<td>64</td>
<td>192</td>
<td>42.36</td>
<td>12200</td>
<td>11590</td>
<td>9150</td>
<td>5490</td>
<td>3660</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.large</td>
<td>2</td>
<td>2</td>
<td>0.59</td>
<td>170</td>
<td>170</td>
<td>144.5</td>
<td>93.5</td>
<td>64.6</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.xlarge</td>
<td>4</td>
<td>4</td>
<td>1.18</td>
<td>340</td>
<td>340</td>
<td>289</td>
<td>187</td>
<td>129.2</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.2xlarge</td>
<td>8</td>
<td>8</td>
<td>2.36</td>
<td>680</td>
<td>680</td>
<td>578</td>
<td>374</td>
<td>258.4</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.3xlarge</td>
<td>12</td>
<td>12</td>
<td>3.54</td>
<td>1020</td>
<td>1020</td>
<td>867</td>
<td>561</td>
<td>387.6</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.4xlarge</td>
<td>16</td>
<td>16</td>
<td>4.72</td>
<td>1360</td>
<td>1360</td>
<td>1156</td>
<td>748</td>
<td>516.8</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.6xlarge</td>
<td>24</td>
<td>24</td>
<td>7.09</td>
<td>2041</td>
<td>2041</td>
<td>1734.85</td>
<td>1122.55</td>
<td>775.58</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.8xlarge</td>
<td>32</td>
<td>32</td>
<td>9.45</td>
<td>2721</td>
<td>2721</td>
<td>2312.85</td>
<td>1496.55</td>
<td>1033.98</td>
</tr>
<tr>
<td>密集计算型 ecs.ic5.16xlarge</td>
<td>64</td>
<td>64</td>
<td>18.9</td>
<td>5442</td>
<td>5442</td>
<td>4625.7</td>
<td>2993.1</td>
<td>2067.96</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.large</td>
<td>2</td>
<td>8</td>
<td>0.649</td>
<td>311.75</td>
<td>311.75</td>
<td>202.64</td>
<td>134.05</td>
<td>93.53</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.299</td>
<td>623.5</td>
<td>623.5</td>
<td>405.28</td>
<td>268.11</td>
<td>187.05</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>4.33</td>
<td>1247</td>
<td>1247</td>
<td>810.55</td>
<td>536.21</td>
<td>374.1</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>8.66</td>
<td>2494</td>
<td>2494</td>
<td>1621.1</td>
<td>1072.42</td>
<td>748.2</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>17.32</td>
<td>4988</td>
<td>4988</td>
<td>3242.2</td>
<td>2144.84</td>
<td>1496.4</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.16xlarge</td>
<td>64</td>
<td>256</td>
<td>34.64</td>
<td>9976</td>
<td>9976</td>
<td>6484.4</td>
<td>4289.68</td>
<td>2992.8</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g5ne.18xlarge</td>
<td>72</td>
<td>288</td>
<td>38.97</td>
<td>11223</td>
<td>11223</td>
<td>7294.95</td>
<td>4825.89</td>
<td>3366.9</td>
</tr>
<tr>
<td>通用型 ecs.n4.small</td>
<td>1</td>
<td>2</td>
<td>0.29</td>
<td>84</td>
<td>84</td>
<td>71.4</td>
<td>42</td>
<td>42</td>
</tr>
<tr>
<td>通用型 ecs.n4.large</td>
<td>2</td>
<td>4</td>
<td>0.71</td>
<td>204</td>
<td>204</td>
<td>173.4</td>
<td>102</td>
<td>102</td>
</tr>
<tr>
<td>通用型 ecs.n4.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.42</td>
<td>408</td>
<td>408</td>
<td>346.8</td>
<td>204</td>
<td>204</td>
</tr>
<tr>
<td>通用型 ecs.n4.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.83</td>
<td>816</td>
<td>816</td>
<td>693.6</td>
<td>408</td>
<td>408</td>
</tr>
<tr>
<td>通用型 ecs.n4.4xlarge</td>
<td>16</td>
<td>32</td>
<td>5.67</td>
<td>1632</td>
<td>1632</td>
<td>1387.2</td>
<td>816</td>
<td>816</td>
</tr>
<tr>
<td>通用型 ecs.n4.8xlarge</td>
<td>32</td>
<td>64</td>
<td>11.33</td>
<td>3264</td>
<td>3264</td>
<td>2774.4</td>
<td>1632</td>
<td>1632</td>
</tr>
<tr>
<td>通用型 ecs.mn4.small</td>
<td>1</td>
<td>4</td>
<td>0.54</td>
<td>155</td>
<td>155</td>
<td>131.75</td>
<td>77.5</td>
<td>77.5</td>
</tr>
<tr>
<td>通用型 ecs.mn4.large</td>
<td>2</td>
<td>8</td>
<td>1.08</td>
<td>310</td>
<td>310</td>
<td>263.5</td>
<td>155</td>
<td>155</td>
</tr>
<tr>
<td>通用型 ecs.mn4.xlarge</td>
<td>4</td>
<td>16</td>
<td>2.15</td>
<td>620</td>
<td>620</td>
<td>527</td>
<td>310</td>
<td>310</td>
</tr>
<tr>
<td>通用型 ecs.mn4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>4.3</td>
<td>1240</td>
<td>1240</td>
<td>1054</td>
<td>620</td>
<td>620</td>
</tr>
<tr>
<td>通用型 ecs.mn4.4xlarge</td>
<td>16</td>
<td>64</td>
<td>8.61</td>
<td>2480</td>
<td>2480</td>
<td>2108</td>
<td>1240</td>
<td>1240</td>
</tr>
<tr>
<td>通用型 ecs.mn4.8xlarge</td>
<td>32</td>
<td>128</td>
<td>17.22</td>
<td>4960</td>
<td>4960</td>
<td>4216</td>
<td>2480</td>
<td>2480</td>
</tr>
<tr>
<td>通用型 ecs.xn4.small</td>
<td>1</td>
<td>1</td>
<td>0.16</td>
<td>45</td>
<td>45</td>
<td>38.25</td>
<td>22.5</td>
<td>22.5</td>
</tr>
<tr>
<td>经济型 ecs.e4.small</td>
<td>1</td>
<td>8</td>
<td>0.9</td>
<td>260</td>
<td>260</td>
<td>221</td>
<td>130</td>
<td>130</td>
</tr>
<tr>
<td>经济型 ecs.e4.large</td>
<td>2</td>
<td>16</td>
<td>1.81</td>
<td>520</td>
<td>520</td>
<td>442</td>
<td>260</td>
<td>260</td>
</tr>
<tr>
<td>经济型 ecs.e4.xlarge</td>
<td>4</td>
<td>32</td>
<td>3.61</td>
<td>1040</td>
<td>1040</td>
<td>884</td>
<td>520</td>
<td>520</td>
</tr>
<tr>
<td>经济型 ecs.e4.2xlarge</td>
<td>8</td>
<td>64</td>
<td>7.22</td>
<td>2080</td>
<td>2080</td>
<td>1768</td>
<td>1040</td>
<td>1040</td>
</tr>
<tr>
<td>经济型 ecs.e4.4xlarge</td>
<td>16</td>
<td>128</td>
<td>14.44</td>
<td>4160</td>
<td>4160</td>
<td>3536</td>
<td>2080</td>
<td>2080</td>
</tr>
<tr>
<td>持久内存型 ecs.re4.10xlarge</td>
<td>40</td>
<td>480</td>
<td>34.375</td>
<td>9900</td>
<td>9900</td>
<td>8415</td>
<td>4950</td>
<td>4950</td>
</tr>
<tr>
<td>持久内存型 ecs.re4.20xlarge</td>
<td>80</td>
<td>960</td>
<td>68.75</td>
<td>19800</td>
<td>19800</td>
<td>16830</td>
<td>9900</td>
<td>9900</td>
</tr>
<tr>
<td>持久内存型 ecs.re4.40xlarge</td>
<td>160</td>
<td>1920</td>
<td>137.5</td>
<td>39600</td>
<td>39600</td>
<td>33660</td>
<td>19800</td>
<td>19800</td>
</tr>
<tr>
<td>ecs.sn2ne.large</td>
<td>2</td>
<td>8</td>
<td>0.99</td>
<td>286</td>
<td>286</td>
<td>243.1</td>
<td>157.3</td>
<td>108.68</td>
</tr>
<tr>
<td>ecs.sn2ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.99</td>
<td>572</td>
<td>572</td>
<td>486.2</td>
<td>314.6</td>
<td>217.36</td>
</tr>
<tr>
<td>ecs.sn2ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.97</td>
<td>1144</td>
<td>1144</td>
<td>972.4</td>
<td>629.2</td>
<td>434.72</td>
</tr>
<tr>
<td>ecs.sn2ne.3xlarge</td>
<td>12</td>
<td>48</td>
<td>5.96</td>
<td>1716</td>
<td>1716</td>
<td>1458.6</td>
<td>943.8</td>
<td>652.08</td>
</tr>
<tr>
<td>ecs.sn2ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>7.94</td>
<td>2288</td>
<td>2288</td>
<td>1944.8</td>
<td>1258.4</td>
<td>869.44</td>
</tr>
<tr>
<td>ecs.sn2ne.6xlarge</td>
<td>24</td>
<td>96</td>
<td>11.92</td>
<td>3432</td>
<td>3432</td>
<td>2917.2</td>
<td>1887.6</td>
<td>1304.16</td>
</tr>
<tr>
<td>ecs.sn2ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>15.89</td>
<td>4576</td>
<td>4576</td>
<td>3889.6</td>
<td>2516.8</td>
<td>1738.88</td>
</tr>
<tr>
<td>ecs.sn2ne.14xlarge</td>
<td>56</td>
<td>224</td>
<td>27.81</td>
<td>8008</td>
<td>8008</td>
<td>6806.8</td>
<td>4404.4</td>
<td>3043.04</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.88</td>
<td>904</td>
<td>904</td>
<td>587.6</td>
<td>388.72</td>
<td>271.2</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.77</td>
<td>1808</td>
<td>1808</td>
<td>1175.2</td>
<td>777.44</td>
<td>542.4</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.53</td>
<td>3616</td>
<td>3616</td>
<td>2350.4</td>
<td>1554.88</td>
<td>1084.8</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.8xlarge</td>
<td>32</td>
<td>256</td>
<td>15.07</td>
<td>7232</td>
<td>7232</td>
<td>4700.8</td>
<td>3109.76</td>
<td>2169.6</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2.16xlarge</td>
<td>64</td>
<td>512</td>
<td>30.13</td>
<td>14464</td>
<td>14464</td>
<td>9401.6</td>
<td>6219.52</td>
<td>4339.2</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.073</td>
<td>1475</td>
<td>1475</td>
<td>958.75</td>
<td>634.25</td>
<td>442.5</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.4xlarge</td>
<td>16</td>
<td>64</td>
<td>6.146</td>
<td>2950</td>
<td>2950</td>
<td>1917.5</td>
<td>1268.5</td>
<td>885</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.8xlarge</td>
<td>32</td>
<td>128</td>
<td>12.292</td>
<td>5900</td>
<td>5900</td>
<td>3835</td>
<td>2537</td>
<td>1770</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2g.16xlarge</td>
<td>64</td>
<td>256</td>
<td>24.584</td>
<td>11800</td>
<td>11800</td>
<td>7670</td>
<td>5074</td>
<td>3540</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.974</td>
<td>949.2</td>
<td>949.2</td>
<td>616.98</td>
<td>408.16</td>
<td>284.76</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.948</td>
<td>1898.4</td>
<td>1898.4</td>
<td>1233.96</td>
<td>816.31</td>
<td>569.52</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.896</td>
<td>3796.8</td>
<td>3796.8</td>
<td>2467.92</td>
<td>1632.62</td>
<td>1139.04</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.8xlarge</td>
<td>32</td>
<td>256</td>
<td>15.792</td>
<td>7593.6</td>
<td>7593.6</td>
<td>4935.84</td>
<td>3265.25</td>
<td>2278.08</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.16xlarge</td>
<td>64</td>
<td>512</td>
<td>31.584</td>
<td>15187.2</td>
<td>15187.2</td>
<td>9871.68</td>
<td>6530.5</td>
<td>4556.16</td>
</tr>
<tr>
<td>本地SSD网络增强型 ecs.i2ne.20xlarge</td>
<td>80</td>
<td>704</td>
<td>39.48</td>
<td>18984</td>
<td>18984</td>
<td>12339.6</td>
<td>8163.12</td>
<td>5695.2</td>
</tr>
<tr>
<td>大数据存储型 ecs.d2s.5xlarge</td>
<td>20</td>
<td>88</td>
<td>14.73</td>
<td>4242</td>
<td>4242</td>
<td>2757.3</td>
<td>1824.06</td>
<td>1272.6</td>
</tr>
<tr>
<td>大数据存储型 ecs.d2s.10xlarge</td>
<td>40</td>
<td>176</td>
<td>29.46</td>
<td>8484</td>
<td>8484</td>
<td>5514.6</td>
<td>3648.12</td>
<td>2545.2</td>
</tr>
<tr>
<td>大数据存储型 ecs.d2s.20xlarge</td>
<td>80</td>
<td>352</td>
<td>58.92</td>
<td>16968</td>
<td>16968</td>
<td>11029.2</td>
<td>7296.24</td>
<td>5090.4</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.large</td>
<td>2</td>
<td>16</td>
<td>1.53</td>
<td>366</td>
<td>366</td>
<td>311.1</td>
<td>183</td>
<td>183</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.xlarge</td>
<td>4</td>
<td>32</td>
<td>3.07</td>
<td>732</td>
<td>732</td>
<td>622.2</td>
<td>366</td>
<td>366</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.2xlarge</td>
<td>8</td>
<td>64</td>
<td>6.14</td>
<td>1464</td>
<td>1464</td>
<td>1244.4</td>
<td>732</td>
<td>732</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.4xlarge</td>
<td>16</td>
<td>128</td>
<td>12.28</td>
<td>2928</td>
<td>2928</td>
<td>2488.8</td>
<td>1464</td>
<td>1464</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.8xlarge</td>
<td>32</td>
<td>256</td>
<td>24.56</td>
<td>5856</td>
<td>5856</td>
<td>4977.6</td>
<td>2928</td>
<td>2928</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1.14xlarge</td>
<td>56</td>
<td>480</td>
<td>44.29</td>
<td>10248</td>
<td>10248</td>
<td>8710.8</td>
<td>5124</td>
<td>5124</td>
</tr>
<tr>
<td>ecs.sn1ne.large</td>
<td>2</td>
<td>4</td>
<td>0.68</td>
<td>197</td>
<td>197</td>
<td>167.45</td>
<td>108.35</td>
<td>74.86</td>
</tr>
<tr>
<td>ecs.sn1ne.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.37</td>
<td>394</td>
<td>394</td>
<td>334.9</td>
<td>216.7</td>
<td>149.72</td>
</tr>
<tr>
<td>ecs.sn1ne.2xlarge</td>
<td>8</td>
<td>16</td>
<td>2.74</td>
<td>788</td>
<td>788</td>
<td>669.8</td>
<td>433.4</td>
<td>299.44</td>
</tr>
<tr>
<td>ecs.sn1ne.3xlarge</td>
<td>12</td>
<td>24</td>
<td>4.1</td>
<td>1182</td>
<td>1182</td>
<td>1004.7</td>
<td>650.1</td>
<td>449.16</td>
</tr>
<tr>
<td>ecs.sn1ne.4xlarge</td>
<td>16</td>
<td>32</td>
<td>5.47</td>
<td>1576</td>
<td>1576</td>
<td>1339.6</td>
<td>866.8</td>
<td>598.88</td>
</tr>
<tr>
<td>ecs.sn1ne.6xlarge</td>
<td>24</td>
<td>48</td>
<td>8.21</td>
<td>2364</td>
<td>2364</td>
<td>2009.4</td>
<td>1300.2</td>
<td>898.32</td>
</tr>
<tr>
<td>ecs.sn1ne.8xlarge</td>
<td>32</td>
<td>64</td>
<td>10.94</td>
<td>3152</td>
<td>3152</td>
<td>2679.2</td>
<td>1733.6</td>
<td>1197.76</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.large</td>
<td>2</td>
<td>16</td>
<td>1.27</td>
<td>366</td>
<td>366</td>
<td>311.1</td>
<td>201.3</td>
<td>139.08</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>2.54</td>
<td>732</td>
<td>732</td>
<td>622.2</td>
<td>402.6</td>
<td>278.16</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>5.08</td>
<td>1464</td>
<td>1464</td>
<td>1244.4</td>
<td>805.2</td>
<td>556.32</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.3xlarge</td>
<td>12</td>
<td>96</td>
<td>7.63</td>
<td>2196</td>
<td>2196</td>
<td>1866.6</td>
<td>1207.8</td>
<td>834.48</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>10.17</td>
<td>2928</td>
<td>2928</td>
<td>2488.8</td>
<td>1610.4</td>
<td>1112.64</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.6xlarge</td>
<td>24</td>
<td>192</td>
<td>15.25</td>
<td>4392</td>
<td>4392</td>
<td>3733.2</td>
<td>2415.6</td>
<td>1668.96</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.8xlarge</td>
<td>32</td>
<td>256</td>
<td>20.33</td>
<td>5856</td>
<td>5856</td>
<td>4977.6</td>
<td>3220.8</td>
<td>2225.28</td>
</tr>
<tr>
<td>存储增强内存型 ecs.se1ne.14xlarge</td>
<td>56</td>
<td>480</td>
<td>35.58</td>
<td>10248</td>
<td>10248</td>
<td>8710.8</td>
<td>5636.4</td>
<td>3894.24</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>6.68</td>
<td>1925</td>
<td>1828.75</td>
<td>1443.75</td>
<td>866.25</td>
<td>577.5</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>13.37</td>
<td>3850</td>
<td>3657.5</td>
<td>2887.5</td>
<td>1732.5</td>
<td>1155</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.6xlarge</td>
<td>24</td>
<td>96</td>
<td>20.05</td>
<td>5775</td>
<td>5486.25</td>
<td>4331.25</td>
<td>2598.75</td>
<td>1732.5</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>26.74</td>
<td>7700</td>
<td>7315</td>
<td>5775</td>
<td>3465</td>
<td>2310</td>
</tr>
<tr>
<td>大数据网络增强型 ecs.d1ne.14xlarge</td>
<td>56</td>
<td>224</td>
<td>46.79</td>
<td>13475</td>
<td>12801.25</td>
<td>10106.25</td>
<td>6063.75</td>
<td>4042.5</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.225</td>
<td>108</td>
<td>108</td>
<td>36.72</td>
<td>22.68</td>
<td>22.68</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.3375</td>
<td>162</td>
<td>162</td>
<td>55.08</td>
<td>34.02</td>
<td>34.02</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.094</td>
<td>45.14</td>
<td>45.14</td>
<td>15.35</td>
<td>9.48</td>
<td>9.48</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.675</td>
<td>324</td>
<td>324</td>
<td>220.32</td>
<td>142.56</td>
<td>97.2</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.45</td>
<td>216</td>
<td>216</td>
<td>146.88</td>
<td>95.04</td>
<td>64.8</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.35</td>
<td>648</td>
<td>648</td>
<td>440.64</td>
<td>285.12</td>
<td>194.4</td>
</tr>
<tr>
<td>经济型 ecs.e-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>0.9</td>
<td>432</td>
<td>432</td>
<td>293.76</td>
<td>190.08</td>
<td>129.6</td>
</tr>
</tbody>
</table>

三、阿里云服务器便宜购买技巧（比活动价格更便宜）
了解完阿里云服务器青岛地域收费标准之后，我们再来说说如何购买阿里云服务器能比活动价格还低，2024年阿里云活动中的云服务器有多种配置和实例规格的云服务器可选，其中轻量应用服务器2核2G3M最低61元/1年，云服务器2核2G3M最低仅需99元/1年，云服务器2核4G5M最低仅需199元/1年。在阿里云活动中购买云服务器时，很多新用户会问，阿里云活动中的云服务器价格还能便宜吗？答案是肯定的，现在我们可以通过领取新用户满减优惠券，在购买阿里云活动中的云服务器时享受更多优惠，实际购买价格比活动价格更便宜。

第一步：领取新用户满减优惠券或代金券
首先，我们需要领取新用户满减优惠券或代金券，阿里云官方会不定期为个人和企业新用户推出各种满减优惠券或者代金券，您可以从以下两个活动中领取优惠券：

阿里云活动中心的“领券中心”。官网地址为：https://www.aliyun.com/activity
阿里云官方云小站平台内的“云产品通用代金券”。官网地址为：https://www.aliyun.com/minisite/goods
</ol>

<div class="image-caption">云小站代金券图.png

我们随便进入一个活动领取优惠券即可。为了方便起见，小编建议您直接通过云小站平台领取优惠券，因为领取后可以直接在活动内购买云服务器使用。

第二步：比较活动内云服务器不同地域的活动价格
在相同实例规格和配置的情况下，不同地域的阿里云服务器活动价格是不一样的，我们在购买时候可以先比较一下不同地域之间的云服务器活动价格，然后选择价格更低的，这样也能达到更便宜购买的目的，例如同样是计算型c7实例2核4G1M带宽配置，目前阿里云活动内显示的价格是2129.41元1年，这个价格只是北京、杭州、上海、深圳等地域的价格，如果我们选择乌兰察布、河源等地域，活动价格则是1875.79元1年，价格要便宜253.62元，如下图所示：

<div class="image-caption">1875.79图.png

第三步：下单购买并使用满减优惠券
当我们领取完满减优惠券并选择好云服务器配置之后，可以看下这款云服务器是否支持叠加使用优惠券，如下图所示：

<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：

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