论坛 › 技术前沿 › 阿里云服务器、轻量应用服务器、gpu云服务器收费标准及活动价格表

弗里 发表于 2024-10-5 22:52:00

阿里云服务器、轻量应用服务器、gpu云服务器收费标准及活动价格表

阿里云服务器、轻量应用服务器、gpu云服务器活动价格出炉，云服务器最低19.17元/3个月起，轻量应用服务器最低99元起，gpu云服务器最低901.26元/1个月起，下面是简书小编为大家整理汇总的阿里云服务器、轻量应用服务器、gpu云服务器最新收费标准及详细活动价格表，以供大家了解阿里云服务器产品是如何收费的，当下有哪些优惠云服务器可选，活动价格是多少。
<h2>一、阿里云服务器收费标准及活动价格表</h2>
<h5>1、阿里云服务器收费标准</h5>
云服务器ECS收费标准是由CPU内存配置+公网带宽价格+磁盘存储价格组成，下面主要为大家展示CPU内存配置的收费标准，因为相同配置的云服务器有多种实例规格可选，不同实例之间的收费标准是相差很大的，同时不同区域和操作系统的云服务器收费标准也有所不同，下面以华南3（广州地域）Windows操作系统为例为大家展示阿里云服务器收费标准。
<table>
<thead>
<tr>
<th>实例规格</th>
<th>vCPU</th>
<th>内存(GB)</th>
<th>按量(小时)</th>
<th>标准目录月价</th>
<th>优惠月价</th>
<th>年付月价</th>
<th>3年付月价</th>
<th>5年付月价</th>
</tr>
</thead>
<tbody>
<tr>
<td>通用型 ecs.g7a.large</td>
<td>2</td>
<td>8</td>
<td>0.44</td>
<td>211.2</td>
<td>211.2</td>
<td>179.52</td>
<td>116.16</td>
<td>80.26</td>
</tr>
<tr>
<td>通用型 ecs.g7a.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.88</td>
<td>422.4</td>
<td>422.4</td>
<td>359.04</td>
<td>232.32</td>
<td>160.51</td>
</tr>
<tr>
<td>通用型 ecs.g7a.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.76</td>
<td>844.8</td>
<td>844.8</td>
<td>718.08</td>
<td>464.64</td>
<td>321.02</td>
</tr>
<tr>
<td>通用型 ecs.g7a.4xlarge</td>
<td>16</td>
<td>64</td>
<td>3.52</td>
<td>1689.6</td>
<td>1689.6</td>
<td>1436.16</td>
<td>929.28</td>
<td>642.05</td>
</tr>
<tr>
<td>通用型 ecs.g7a.8xlarge</td>
<td>32</td>
<td>128</td>
<td>7.04</td>
<td>3379.2</td>
<td>3379.2</td>
<td>2872.32</td>
<td>1858.56</td>
<td>1284.1</td>
</tr>
<tr>
<td>通用型 ecs.g7a.16xlarge</td>
<td>64</td>
<td>256</td>
<td>14.08</td>
<td>6758.4</td>
<td>6758.4</td>
<td>5744.64</td>
<td>3717.12</td>
<td>2568.19</td>
</tr>
<tr>
<td>通用型 ecs.g7a.32xlarge</td>
<td>128</td>
<td>512</td>
<td>28.16</td>
<td>13516.8</td>
<td>13516.8</td>
<td>11489.28</td>
<td>7434.24</td>
<td>5136.38</td>
</tr>
<tr>
<td>通用型 ecs.g7.large</td>
<td>2</td>
<td>8</td>
<td>0.52325</td>
<td>251.16</td>
<td>251.16</td>
<td>213.49</td>
<td>138.14</td>
<td>95.44</td>
</tr>
<tr>
<td>通用型 ecs.g7.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.0465</td>
<td>502.32</td>
<td>502.32</td>
<td>426.97</td>
<td>276.28</td>
<td>190.88</td>
</tr>
<tr>
<td>通用型 ecs.g7.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.093</td>
<td>1004.64</td>
<td>1004.64</td>
<td>853.94</td>
<td>552.55</td>
<td>381.76</td>
</tr>
<tr>
<td>通用型 ecs.g7.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.1395</td>
<td>1506.96</td>
<td>1506.96</td>
<td>1280.92</td>
<td>828.83</td>
<td>572.64</td>
</tr>
<tr>
<td>通用型 ecs.g7.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.186</td>
<td>2009.28</td>
<td>2009.28</td>
<td>1707.89</td>
<td>1105.1</td>
<td>763.53</td>
</tr>
<tr>
<td>通用型 ecs.g7.6xlarge</td>
<td>24</td>
<td>96</td>
<td>6.279</td>
<td>3013.92</td>
<td>3013.92</td>
<td>2561.83</td>
<td>1657.66</td>
<td>1145.29</td>
</tr>
<tr>
<td>通用型 ecs.g7.8xlarge</td>
<td>32</td>
<td>128</td>
<td>8.372</td>
<td>4018.56</td>
<td>4018.56</td>
<td>3415.78</td>
<td>2210.21</td>
<td>1527.05</td>
</tr>
<tr>
<td>通用型 ecs.g7.16xlarge</td>
<td>64</td>
<td>256</td>
<td>16.744</td>
<td>8037.12</td>
<td>8037.12</td>
<td>6831.55</td>
<td>4420.42</td>
<td>3054.11</td>
</tr>
<tr>
<td>网络增强型 ecs.g7ne.large</td>
<td>2</td>
<td>8</td>
<td>0.725</td>
<td>348</td>
<td>348</td>
<td>295.8</td>
<td>191.4</td>
<td>132.24</td>
</tr>
<tr>
<td>网络增强型 ecs.g7ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.45</td>
<td>696</td>
<td>696</td>
<td>591.6</td>
<td>382.8</td>
<td>264.48</td>
</tr>
<tr>
<td>网络增强型 ecs.g7ne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.9</td>
<td>1392</td>
<td>1392</td>
<td>1183.2</td>
<td>765.6</td>
<td>528.96</td>
</tr>
<tr>
<td>网络增强型 ecs.g7ne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.8</td>
<td>2784</td>
<td>2784</td>
<td>2366.4</td>
<td>1531.2</td>
<td>1057.92</td>
</tr>
<tr>
<td>网络增强型 ecs.g7ne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.6</td>
<td>5568</td>
<td>5568</td>
<td>4732.8</td>
<td>3062.4</td>
<td>2115.84</td>
</tr>
<tr>
<td>网络增强型 ecs.g7ne.12xlarge</td>
<td>48</td>
<td>192</td>
<td>17.4</td>
<td>8352</td>
<td>8352</td>
<td>7099.2</td>
<td>4593.6</td>
<td>3173.76</td>
</tr>
<tr>
<td>网络增强型 ecs.g7ne.24xlarge</td>
<td>96</td>
<td>384</td>
<td>34.8</td>
<td>16704</td>
<td>16704</td>
<td>14198.4</td>
<td>9187.2</td>
<td>6347.52</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>204</td>
<td>132</td>
<td>91.2</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>408</td>
<td>264</td>
<td>182.4</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>816</td>
<td>528</td>
<td>364.8</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>1224</td>
<td>792</td>
<td>547.2</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>1632</td>
<td>1056</td>
<td>729.6</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>2448</td>
<td>1584</td>
<td>1094.4</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>3264</td>
<td>2112</td>
<td>1459.2</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>5304</td>
<td>3432</td>
<td>2371.2</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>10608</td>
<td>6864</td>
<td>4742.4</td>
</tr>
<tr>
<td>通用型 ecs.g6a.large</td>
<td>2</td>
<td>8</td>
<td>0.44</td>
<td>211.2</td>
<td>211.2</td>
<td>179.52</td>
<td>116.16</td>
<td>80.26</td>
</tr>
<tr>
<td>通用型 ecs.g6a.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.88</td>
<td>422.4</td>
<td>422.4</td>
<td>359.04</td>
<td>232.32</td>
<td>160.51</td>
</tr>
<tr>
<td>通用型 ecs.g6a.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.76</td>
<td>844.8</td>
<td>844.8</td>
<td>718.08</td>
<td>464.64</td>
<td>321.02</td>
</tr>
<tr>
<td>通用型 ecs.g6a.4xlarge</td>
<td>16</td>
<td>64</td>
<td>3.52</td>
<td>1689.6</td>
<td>1689.6</td>
<td>1436.16</td>
<td>929.28</td>
<td>642.05</td>
</tr>
<tr>
<td>通用型 ecs.g6a.8xlarge</td>
<td>32</td>
<td>128</td>
<td>7.04</td>
<td>3379.2</td>
<td>3379.2</td>
<td>2872.32</td>
<td>1858.56</td>
<td>1284.1</td>
</tr>
<tr>
<td>通用型 ecs.g6a.16xlarge</td>
<td>64</td>
<td>256</td>
<td>14.08</td>
<td>6758.4</td>
<td>6758.4</td>
<td>5744.64</td>
<td>3717.12</td>
<td>2568.19</td>
</tr>
<tr>
<td>通用型 ecs.g6a.32xlarge</td>
<td>128</td>
<td>512</td>
<td>28.16</td>
<td>13516.8</td>
<td>13516.8</td>
<td>11489.28</td>
<td>7434.24</td>
<td>5136.38</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.large</td>
<td>2</td>
<td>8</td>
<td>0.55</td>
<td>264</td>
<td>264</td>
<td>224.4</td>
<td>145.2</td>
<td>100.32</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.1</td>
<td>528</td>
<td>528</td>
<td>448.8</td>
<td>290.4</td>
<td>200.64</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.2</td>
<td>1056</td>
<td>1056</td>
<td>897.6</td>
<td>580.8</td>
<td>401.28</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.4</td>
<td>2112</td>
<td>2112</td>
<td>1795.2</td>
<td>1161.6</td>
<td>802.56</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.8xlarge</td>
<td>32</td>
<td>128</td>
<td>8.8</td>
<td>4224</td>
<td>4224</td>
<td>3590.4</td>
<td>2323.2</td>
<td>1605.12</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.g6e.13xlarge</td>
<td>52</td>
<td>192</td>
<td>14.3</td>
<td>6864</td>
<td>6864</td>
<td>5834.4</td>
<td>3775.2</td>
<td>2608.32</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.large</td>
<td>2</td>
<td>8</td>
<td>0.649479</td>
<td>311.75</td>
<td>311.75</td>
<td>264.99</td>
<td>171.46</td>
<td>118.46</td>
</tr>
<tr>
<td>网络增强型 ecs.g5ne.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.298958</td>
<td>623.5</td>
<td>623.5</td>
<td>529.98</td>
<td>342.92</td>
<td>236.93</td>
</tr>
<tr>
<td>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>1059.95</td>
<td>685.85</td>
<td>473.86</td>
</tr>
<tr>
<td>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>2119.9</td>
<td>1371.7</td>
<td>947.72</td>
</tr>
<tr>
<td>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>4239.8</td>
<td>2743.4</td>
<td>1895.44</td>
</tr>
<tr>
<td>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>8479.6</td>
<td>5486.8</td>
<td>3790.88</td>
</tr>
<tr>
<td>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>9539.55</td>
<td>6172.65</td>
<td>4264.74</td>
</tr>
<tr>
<td>计算型 ecs.c7a.large</td>
<td>2</td>
<td>4</td>
<td>0.293</td>
<td>140.8</td>
<td>140.8</td>
<td>119.68</td>
<td>77.44</td>
<td>53.5</td>
</tr>
<tr>
<td>计算型 ecs.c7a.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.587</td>
<td>281.6</td>
<td>281.6</td>
<td>239.36</td>
<td>154.88</td>
<td>107.01</td>
</tr>
<tr>
<td>计算型 ecs.c7a.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.173</td>
<td>563.2</td>
<td>563.2</td>
<td>478.72</td>
<td>309.76</td>
<td>214.02</td>
</tr>
<tr>
<td>计算型 ecs.c7a.4xlarge</td>
<td>16</td>
<td>32</td>
<td>2.347</td>
<td>1126.4</td>
<td>1126.4</td>
<td>957.44</td>
<td>619.52</td>
<td>428.03</td>
</tr>
<tr>
<td>计算型 ecs.c7a.8xlarge</td>
<td>32</td>
<td>64</td>
<td>4.693</td>
<td>2252.8</td>
<td>2252.8</td>
<td>1914.88</td>
<td>1239.04</td>
<td>856.06</td>
</tr>
<tr>
<td>计算型 ecs.c7a.16xlarge</td>
<td>64</td>
<td>128</td>
<td>9.387</td>
<td>4505.6</td>
<td>4505.6</td>
<td>3829.76</td>
<td>2478.08</td>
<td>1712.13</td>
</tr>
<tr>
<td>计算型 ecs.c7a.32xlarge</td>
<td>128</td>
<td>256</td>
<td>18.773</td>
<td>9011.2</td>
<td>9011.2</td>
<td>7659.52</td>
<td>4956.16</td>
<td>3424.26</td>
</tr>
<tr>
<td>计算型 ecs.c7.large</td>
<td>2</td>
<td>4</td>
<td>0.407698</td>
<td>195.7</td>
<td>195.7</td>
<td>166.34</td>
<td>107.63</td>
<td>74.36</td>
</tr>
<tr>
<td>计算型 ecs.c7.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.815397</td>
<td>391.39</td>
<td>391.39</td>
<td>332.68</td>
<td>215.26</td>
<td>148.73</td>
</tr>
<tr>
<td>计算型 ecs.c7.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.630795</td>
<td>782.78</td>
<td>782.78</td>
<td>665.36</td>
<td>430.53</td>
<td>297.46</td>
</tr>
<tr>
<td>计算型 ecs.c7.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.446193</td>
<td>1174.17</td>
<td>1174.17</td>
<td>998.05</td>
<td>645.8</td>
<td>446.19</td>
</tr>
<tr>
<td>计算型 ecs.c7.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.261591</td>
<td>1565.56</td>
<td>1565.56</td>
<td>1330.73</td>
<td>861.06</td>
<td>594.91</td>
</tr>
<tr>
<td>计算型 ecs.c7.6xlarge</td>
<td>24</td>
<td>48</td>
<td>4.892387</td>
<td>2348.35</td>
<td>2348.35</td>
<td>1996.09</td>
<td>1291.59</td>
<td>892.37</td>
</tr>
<tr>
<td>计算型 ecs.c7.8xlarge</td>
<td>32</td>
<td>64</td>
<td>6.523183</td>
<td>3131.13</td>
<td>3131.13</td>
<td>2661.46</td>
<td>1722.12</td>
<td>1189.83</td>
</tr>
<tr>
<td>计算型 ecs.c7.16xlarge</td>
<td>64</td>
<td>128</td>
<td>13.046366</td>
<td>6262.26</td>
<td>6262.26</td>
<td>5322.92</td>
<td>3444.24</td>
<td>2379.66</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>158.95</td>
<td>102.85</td>
<td>71.06</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>317.9</td>
<td>205.7</td>
<td>142.12</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>635.8</td>
<td>411.4</td>
<td>284.24</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>953.7</td>
<td>617.1</td>
<td>426.36</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>1271.6</td>
<td>822.8</td>
<td>568.48</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>1907.4</td>
<td>1234.2</td>
<td>852.72</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>2543.2</td>
<td>1645.6</td>
<td>1136.96</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>4132.7</td>
<td>2674.1</td>
<td>1847.56</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>8265.4</td>
<td>5348.2</td>
<td>3695.12</td>
</tr>
<tr>
<td>计算型 ecs.c6a.large</td>
<td>2</td>
<td>4</td>
<td>0.293</td>
<td>140.8</td>
<td>140.8</td>
<td>119.68</td>
<td>77.44</td>
<td>53.5</td>
</tr>
<tr>
<td>计算型 ecs.c6a.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.587</td>
<td>281.6</td>
<td>281.6</td>
<td>239.36</td>
<td>154.88</td>
<td>107.01</td>
</tr>
<tr>
<td>计算型 ecs.c6a.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.173</td>
<td>563.2</td>
<td>563.2</td>
<td>478.72</td>
<td>309.76</td>
<td>214.02</td>
</tr>
<tr>
<td>计算型 ecs.c6a.4xlarge</td>
<td>16</td>
<td>32</td>
<td>2.347</td>
<td>1126.4</td>
<td>1126.4</td>
<td>957.44</td>
<td>619.52</td>
<td>428.03</td>
</tr>
<tr>
<td>计算型 ecs.c6a.8xlarge</td>
<td>32</td>
<td>64</td>
<td>4.693</td>
<td>2252.8</td>
<td>2252.8</td>
<td>1914.88</td>
<td>1239.04</td>
<td>856.06</td>
</tr>
<tr>
<td>计算型 ecs.c6a.16xlarge</td>
<td>64</td>
<td>128</td>
<td>9.387</td>
<td>4505.6</td>
<td>4505.6</td>
<td>3829.76</td>
<td>2478.08</td>
<td>1712.13</td>
</tr>
<tr>
<td>计算型 ecs.c6a.32xlarge</td>
<td>128</td>
<td>256</td>
<td>18.773</td>
<td>9011.2</td>
<td>9011.2</td>
<td>7659.52</td>
<td>4956.16</td>
<td>3424.26</td>
</tr>
<tr>
<td>安全增强计算型 ecs.c6t.large</td>
<td>2</td>
<td>4</td>
<td>0.422916</td>
<td>203</td>
<td>203</td>
<td>172.55</td>
<td>111.65</td>
<td>77.14</td>
</tr>
<tr>
<td>安全增强计算型 ecs.c6t.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.845833</td>
<td>406</td>
<td>406</td>
<td>345.1</td>
<td>223.3</td>
<td>154.28</td>
</tr>
<tr>
<td>安全增强计算型 ecs.c6t.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.691666</td>
<td>812</td>
<td>812</td>
<td>690.2</td>
<td>446.6</td>
<td>308.56</td>
</tr>
<tr>
<td>安全增强计算型 ecs.c6t.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.383333</td>
<td>1624</td>
<td>1624</td>
<td>1380.4</td>
<td>893.2</td>
<td>617.12</td>
</tr>
<tr>
<td>安全增强计算型 ecs.c6t.8xlarge</td>
<td>32</td>
<td>64</td>
<td>6.764583</td>
<td>3247</td>
<td>3247</td>
<td>2759.95</td>
<td>1785.85</td>
<td>1233.86</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.large</td>
<td>2</td>
<td>4</td>
<td>0.41</td>
<td>197</td>
<td>197</td>
<td>167.45</td>
<td>108.35</td>
<td>74.86</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.821</td>
<td>394</td>
<td>394</td>
<td>334.9</td>
<td>216.7</td>
<td>149.72</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.642</td>
<td>788</td>
<td>788</td>
<td>669.8</td>
<td>433.4</td>
<td>299.44</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.283</td>
<td>1576</td>
<td>1576</td>
<td>1339.6</td>
<td>866.8</td>
<td>598.88</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.8xlarge</td>
<td>32</td>
<td>64</td>
<td>6.567</td>
<td>3152</td>
<td>3152</td>
<td>2679.2</td>
<td>1733.6</td>
<td>1197.76</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.13xlarge</td>
<td>52</td>
<td>96</td>
<td>10.671</td>
<td>5122</td>
<td>5122</td>
<td>4353.7</td>
<td>2817.1</td>
<td>1946.36</td>
</tr>
<tr>
<td>计算平衡增强型 ecs.c6e.26xlarge</td>
<td>104</td>
<td>192</td>
<td>21.342</td>
<td>10244</td>
<td>10244</td>
<td>8707.4</td>
<td>5634.2</td>
<td>3892.72</td>
</tr>
<tr>
<td>内存型 ecs.r7a.large</td>
<td>2</td>
<td>16</td>
<td>0.596</td>
<td>286.2</td>
<td>286.2</td>
<td>243.27</td>
<td>157.41</td>
<td>108.76</td>
</tr>
<tr>
<td>内存型 ecs.r7a.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.192</td>
<td>572.4</td>
<td>572.4</td>
<td>486.54</td>
<td>314.82</td>
<td>217.51</td>
</tr>
<tr>
<td>内存型 ecs.r7a.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.385</td>
<td>1144.8</td>
<td>1144.8</td>
<td>973.08</td>
<td>629.64</td>
<td>435.02</td>
</tr>
<tr>
<td>内存型 ecs.r7a.4xlarge</td>
<td>16</td>
<td>128</td>
<td>4.77</td>
<td>2289.6</td>
<td>2289.6</td>
<td>1946.16</td>
<td>1259.28</td>
<td>870.05</td>
</tr>
<tr>
<td>内存型 ecs.r7a.8xlarge</td>
<td>32</td>
<td>256</td>
<td>9.54</td>
<td>4579.2</td>
<td>4579.2</td>
<td>3892.32</td>
<td>2518.56</td>
<td>1740.1</td>
</tr>
<tr>
<td>内存型 ecs.r7a.16xlarge</td>
<td>64</td>
<td>512</td>
<td>19.08</td>
<td>9158.4</td>
<td>9158.4</td>
<td>7784.64</td>
<td>5037.12</td>
<td>3480.19</td>
</tr>
<tr>
<td>内存型 ecs.r7a.32xlarge</td>
<td>128</td>
<td>1024</td>
<td>38.16</td>
<td>18316.8</td>
<td>18316.8</td>
<td>15569.28</td>
<td>10074.24</td>
<td>6960.38</td>
</tr>
<tr>
<td>内存型 ecs.r7.large</td>
<td>2</td>
<td>16</td>
<td>0.696221</td>
<td>334.19</td>
<td>334.19</td>
<td>284.06</td>
<td>183.8</td>
<td>126.99</td>
</tr>
<tr>
<td>内存型 ecs.r7.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.392442</td>
<td>668.37</td>
<td>668.37</td>
<td>568.12</td>
<td>367.61</td>
<td>253.98</td>
</tr>
<tr>
<td>内存型 ecs.r7.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.784885</td>
<td>1336.74</td>
<td>1336.74</td>
<td>1136.23</td>
<td>735.21</td>
<td>507.96</td>
</tr>
<tr>
<td>内存型 ecs.r7.3xlarge</td>
<td>12</td>
<td>96</td>
<td>4.177327</td>
<td>2005.12</td>
<td>2005.12</td>
<td>1704.35</td>
<td>1102.81</td>
<td>761.94</td>
</tr>
<tr>
<td>内存型 ecs.r7.4xlarge</td>
<td>16</td>
<td>128</td>
<td>5.56977</td>
<td>2673.49</td>
<td>2673.49</td>
<td>2272.47</td>
<td>1470.42</td>
<td>1015.93</td>
</tr>
<tr>
<td>内存型 ecs.r7.6xlarge</td>
<td>24</td>
<td>192</td>
<td>8.354655</td>
<td>4010.23</td>
<td>4010.23</td>
<td>3408.7</td>
<td>2205.63</td>
<td>1523.89</td>
</tr>
<tr>
<td>内存型 ecs.r7.8xlarge</td>
<td>32</td>
<td>256</td>
<td>11.13954</td>
<td>5346.98</td>
<td>5346.98</td>
<td>4544.93</td>
<td>2940.84</td>
<td>2031.85</td>
</tr>
<tr>
<td>内存型 ecs.r7.16xlarge</td>
<td>64</td>
<td>512</td>
<td>22.27908</td>
<td>10693.96</td>
<td>10693.96</td>
<td>9089.86</td>
<td>5881.68</td>
<td>4063.7</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>270.3</td>
<td>174.9</td>
<td>120.84</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>540.6</td>
<td>349.8</td>
<td>241.68</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>1081.2</td>
<td>699.6</td>
<td>483.36</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>1621.8</td>
<td>1049.4</td>
<td>725.04</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>2162.4</td>
<td>1399.2</td>
<td>966.72</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>3243.6</td>
<td>2098.8</td>
<td>1450.08</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>4324.8</td>
<td>2798.4</td>
<td>1933.44</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>7027.8</td>
<td>4547.4</td>
<td>3141.84</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>14055.6</td>
<td>9094.8</td>
<td>6283.68</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.large</td>
<td>2</td>
<td>16</td>
<td>0.729</td>
<td>350</td>
<td>350</td>
<td>297.5</td>
<td>192.5</td>
<td>133</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.458</td>
<td>700</td>
<td>700</td>
<td>595</td>
<td>385</td>
<td>266</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.917</td>
<td>1400</td>
<td>1400</td>
<td>1190</td>
<td>770</td>
<td>532</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.4xlarge</td>
<td>16</td>
<td>128</td>
<td>5.833</td>
<td>2800</td>
<td>2800</td>
<td>2380</td>
<td>1540</td>
<td>1064</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.8xlarge</td>
<td>32</td>
<td>256</td>
<td>11.667</td>
<td>5600</td>
<td>5600</td>
<td>4760</td>
<td>3080</td>
<td>2128</td>
</tr>
<tr>
<td>内存平衡增强型 ecs.r6e.13xlarge</td>
<td>52</td>
<td>384</td>
<td>18.958</td>
<td>9100</td>
<td>9100</td>
<td>7735</td>
<td>5005</td>
<td>3458</td>
</tr>
<tr>
<td>大数据计算密集型 ecs.d3c.3xlarge</td>
<td>14</td>
<td>56</td>
<td>7.103</td>
<td>3409.6</td>
<td>3409.6</td>
<td>2898.16</td>
<td>1875.28</td>
<td>1295.65</td>
</tr>
<tr>
<td>大数据计算密集型 ecs.d3c.7xlarge</td>
<td>28</td>
<td>112</td>
<td>14.207</td>
<td>6819.2</td>
<td>6819.2</td>
<td>5796.32</td>
<td>3750.56</td>
<td>2591.3</td>
</tr>
<tr>
<td>大数据计算密集型 ecs.d3c.14xlarge</td>
<td>56</td>
<td>224</td>
<td>28.413</td>
<td>13638.41</td>
<td>13638.41</td>
<td>11592.65</td>
<td>7501.12</td>
<td>5182.59</td>
</tr>
<tr>
<td>大数据存储密集型 ecs.d2s.5xlarge</td>
<td>20</td>
<td>88</td>
<td>14.73</td>
<td>4242</td>
<td>4242</td>
<td>3605.7</td>
<td>2333.1</td>
<td>1611.96</td>
</tr>
<tr>
<td>大数据存储密集型 ecs.d2s.10xlarge</td>
<td>40</td>
<td>176</td>
<td>29.46</td>
<td>8484</td>
<td>8484</td>
<td>7211.4</td>
<td>4666.2</td>
<td>3223.92</td>
</tr>
<tr>
<td>大数据存储密集型 ecs.d2s.20xlarge</td>
<td>80</td>
<td>352</td>
<td>58.92</td>
<td>16968</td>
<td>16968</td>
<td>14422.8</td>
<td>9332.4</td>
<td>6447.84</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.xlarge</td>
<td>4</td>
<td>32</td>
<td>2.059</td>
<td>988</td>
<td>988</td>
<td>839.8</td>
<td>543.4</td>
<td>375.44</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.2xlarge</td>
<td>8</td>
<td>64</td>
<td>4.117</td>
<td>1976</td>
<td>1976</td>
<td>1679.6</td>
<td>1086.8</td>
<td>750.88</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.4xlarge</td>
<td>16</td>
<td>128</td>
<td>8.234</td>
<td>3952</td>
<td>3952</td>
<td>3359.2</td>
<td>2173.6</td>
<td>1501.76</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.8xlarge</td>
<td>32</td>
<td>256</td>
<td>16.467</td>
<td>7904</td>
<td>7904</td>
<td>6718.4</td>
<td>4347.2</td>
<td>3003.52</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.13xlarge</td>
<td>52</td>
<td>384</td>
<td>24.7</td>
<td>11856</td>
<td>11856</td>
<td>10077.6</td>
<td>6520.8</td>
<td>4505.28</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3.26xlarge</td>
<td>104</td>
<td>768</td>
<td>49.4</td>
<td>23712</td>
<td>23712</td>
<td>20155.2</td>
<td>13041.6</td>
<td>9010.56</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.8</td>
<td>1344</td>
<td>1344</td>
<td>1142.4</td>
<td>739.2</td>
<td>510.72</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.4xlarge</td>
<td>16</td>
<td>64</td>
<td>5.6</td>
<td>2688</td>
<td>2688</td>
<td>2284.8</td>
<td>1478.4</td>
<td>1021.44</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.8xlarge</td>
<td>32</td>
<td>128</td>
<td>11.2</td>
<td>5376</td>
<td>5376</td>
<td>4569.6</td>
<td>2956.8</td>
<td>2042.88</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.13xlarge</td>
<td>52</td>
<td>192</td>
<td>16.8</td>
<td>8064</td>
<td>8064</td>
<td>6854.4</td>
<td>4435.2</td>
<td>3064.32</td>
</tr>
<tr>
<td>本地SSD型 ecs.i3g.26xlarge</td>
<td>104</td>
<td>384</td>
<td>33.6</td>
<td>16128</td>
<td>16128</td>
<td>13708.8</td>
<td>8870.4</td>
<td>6128.64</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>768.4</td>
<td>497.2</td>
<td>343.52</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>1536.8</td>
<td>994.4</td>
<td>687.04</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>3073.6</td>
<td>1988.8</td>
<td>1374.08</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>6147.2</td>
<td>3977.6</td>
<td>2748.16</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>12294.4</td>
<td>7955.2</td>
<td>5496.32</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>1253.75</td>
<td>811.25</td>
<td>1475</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>2507.5</td>
<td>1622.5</td>
<td>2950</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>5015</td>
<td>3245</td>
<td>5900</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>10030</td>
<td>6490</td>
<td>11800</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.975049</td>
<td>949.2</td>
<td>949.2</td>
<td>806.82</td>
<td>522.06</td>
<td>360.7</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.951</td>
<td>1898.4</td>
<td>1898.4</td>
<td>1613.64</td>
<td>1044.12</td>
<td>721.39</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.4xlarge</td>
<td>16</td>
<td>128</td>
<td>7.901</td>
<td>3796.8</td>
<td>3796.8</td>
<td>3227.28</td>
<td>2088.24</td>
<td>1442.78</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.8xlarge</td>
<td>32</td>
<td>256</td>
<td>15.801</td>
<td>7593.6</td>
<td>7593.6</td>
<td>6454.56</td>
<td>4176.48</td>
<td>2885.57</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2ne.16xlarge</td>
<td>64</td>
<td>512</td>
<td>31.601</td>
<td>15187.2</td>
<td>15187.2</td>
<td>12909.12</td>
<td>8352.96</td>
<td>5771.14</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.2xlarge</td>
<td>8</td>
<td>32</td>
<td>3.227</td>
<td>1549</td>
<td>1549</td>
<td>1316.65</td>
<td>851.95</td>
<td>588.62</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.4xlarge</td>
<td>16</td>
<td>64</td>
<td>6.454</td>
<td>3098</td>
<td>3098</td>
<td>2633.3</td>
<td>1703.9</td>
<td>1177.24</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.8xlarge</td>
<td>32</td>
<td>128</td>
<td>12.907</td>
<td>6196</td>
<td>6196</td>
<td>5266.6</td>
<td>3407.8</td>
<td>2354.48</td>
</tr>
<tr>
<td>本地SSD型 ecs.i2gne.16xlarge</td>
<td>64</td>
<td>256</td>
<td>25.816</td>
<td>12392</td>
<td>12392</td>
<td>10533.2</td>
<td>6815.6</td>
<td>4708.96</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.large</td>
<td>2</td>
<td>4</td>
<td>0.470833</td>
<td>226</td>
<td>226</td>
<td>192.1</td>
<td>124.3</td>
<td>85.88</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.941666</td>
<td>452</td>
<td>452</td>
<td>384.2</td>
<td>248.6</td>
<td>171.76</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.883333</td>
<td>904</td>
<td>904</td>
<td>768.4</td>
<td>497.2</td>
<td>343.52</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.825</td>
<td>1356</td>
<td>1356</td>
<td>1152.6</td>
<td>745.8</td>
<td>515.28</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.766666</td>
<td>1808</td>
<td>1808</td>
<td>1536.8</td>
<td>994.4</td>
<td>687.04</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.6xlarge</td>
<td>24</td>
<td>48</td>
<td>5.65</td>
<td>2712</td>
<td>2712</td>
<td>2305.2</td>
<td>1491.6</td>
<td>1030.56</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.8xlarge</td>
<td>32</td>
<td>64</td>
<td>7.533333</td>
<td>3616</td>
<td>3616</td>
<td>3073.6</td>
<td>1988.8</td>
<td>1374.08</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.12xlarge</td>
<td>48</td>
<td>96</td>
<td>11.3</td>
<td>5424</td>
<td>5424</td>
<td>4610.4</td>
<td>2983.2</td>
<td>2061.12</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc7.24xlarge</td>
<td>96</td>
<td>192</td>
<td>22.6</td>
<td>10848</td>
<td>10848</td>
<td>9220.8</td>
<td>5966.4</td>
<td>4122.24</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.large</td>
<td>2</td>
<td>4</td>
<td>0.447916</td>
<td>215</td>
<td>215</td>
<td>182.75</td>
<td>118.25</td>
<td>81.7</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.895833</td>
<td>430</td>
<td>430</td>
<td>365.5</td>
<td>236.5</td>
<td>163.4</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.791666</td>
<td>860</td>
<td>860</td>
<td>731</td>
<td>473</td>
<td>326.8</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.3xlarge</td>
<td>12</td>
<td>24</td>
<td>2.6875</td>
<td>1290</td>
<td>1290</td>
<td>1096.5</td>
<td>709.5</td>
<td>490.2</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.4xlarge</td>
<td>16</td>
<td>32</td>
<td>3.583333</td>
<td>1720</td>
<td>1720</td>
<td>1462</td>
<td>946</td>
<td>653.6</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.6xlarge</td>
<td>24</td>
<td>48</td>
<td>5.375</td>
<td>2580</td>
<td>2580</td>
<td>2193</td>
<td>1419</td>
<td>980.4</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.8xlarge</td>
<td>32</td>
<td>64</td>
<td>7.166666</td>
<td>3440</td>
<td>3440</td>
<td>2924</td>
<td>1892</td>
<td>1307.2</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.10xlarge</td>
<td>40</td>
<td>96</td>
<td>8.958333</td>
<td>4300</td>
<td>4300</td>
<td>3655</td>
<td>2365</td>
<td>1634</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.16xlarge</td>
<td>64</td>
<td>128</td>
<td>14.333333</td>
<td>6880</td>
<td>6880</td>
<td>5848</td>
<td>3784</td>
<td>2614.4</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc6.20xlarge</td>
<td>80</td>
<td>192</td>
<td>17.916666</td>
<td>8600</td>
<td>8600</td>
<td>7310</td>
<td>4730</td>
<td>3268</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.large</td>
<td>2</td>
<td>8</td>
<td>0.579166</td>
<td>278</td>
<td>278</td>
<td>236.3</td>
<td>152.9</td>
<td>105.64</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.158333</td>
<td>556</td>
<td>556</td>
<td>472.6</td>
<td>305.8</td>
<td>211.28</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.316666</td>
<td>1112</td>
<td>1112</td>
<td>945.2</td>
<td>611.6</td>
<td>422.56</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.475</td>
<td>1668</td>
<td>1668</td>
<td>1417.8</td>
<td>917.4</td>
<td>633.84</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.633333</td>
<td>2224</td>
<td>2224</td>
<td>1890.4</td>
<td>1223.2</td>
<td>845.12</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.6xlarge</td>
<td>24</td>
<td>96</td>
<td>6.95</td>
<td>3336</td>
<td>3336</td>
<td>2835.6</td>
<td>1834.8</td>
<td>1267.68</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.8xlarge</td>
<td>32</td>
<td>128</td>
<td>9.266666</td>
<td>4448</td>
<td>4448</td>
<td>3780.8</td>
<td>2446.4</td>
<td>1690.24</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.12xlarge</td>
<td>48</td>
<td>192</td>
<td>13.9</td>
<td>6672</td>
<td>6672</td>
<td>5671.2</td>
<td>3669.6</td>
<td>2535.36</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg7.24xlarge</td>
<td>96</td>
<td>384</td>
<td>27.8</td>
<td>13344</td>
<td>13344</td>
<td>11342.4</td>
<td>7339.2</td>
<td>5070.72</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.large</td>
<td>2</td>
<td>8</td>
<td>0.55</td>
<td>264</td>
<td>264</td>
<td>224.4</td>
<td>145.2</td>
<td>100.32</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.1</td>
<td>528</td>
<td>528</td>
<td>448.8</td>
<td>290.4</td>
<td>200.64</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.2</td>
<td>1056</td>
<td>1056</td>
<td>897.6</td>
<td>580.8</td>
<td>401.28</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.3xlarge</td>
<td>12</td>
<td>48</td>
<td>3.3</td>
<td>1584</td>
<td>1584</td>
<td>1346.4</td>
<td>871.2</td>
<td>601.92</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.4xlarge</td>
<td>16</td>
<td>64</td>
<td>4.4</td>
<td>2112</td>
<td>2112</td>
<td>1795.2</td>
<td>1161.6</td>
<td>802.56</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.6xlarge</td>
<td>24</td>
<td>96</td>
<td>6.6</td>
<td>3168</td>
<td>3168</td>
<td>2692.8</td>
<td>1742.4</td>
<td>1203.84</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.8xlarge</td>
<td>32</td>
<td>128</td>
<td>8.8</td>
<td>4224</td>
<td>4224</td>
<td>3590.4</td>
<td>2323.2</td>
<td>1605.12</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.10xlarge</td>
<td>40</td>
<td>192</td>
<td>11</td>
<td>5280</td>
<td>5280</td>
<td>4488</td>
<td>2904</td>
<td>2006.4</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.16xlarge</td>
<td>64</td>
<td>256</td>
<td>17.6</td>
<td>8448</td>
<td>8448</td>
<td>7180.8</td>
<td>4646.4</td>
<td>3210.24</td>
</tr>
<tr>
<td>高主频通用型 ecs.hfg6.20xlarge</td>
<td>80</td>
<td>384</td>
<td>22</td>
<td>10560</td>
<td>10560</td>
<td>8976</td>
<td>5808</td>
<td>4012.8</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.large</td>
<td>2</td>
<td>16</td>
<td>0.766666</td>
<td>368</td>
<td>368</td>
<td>312.8</td>
<td>202.4</td>
<td>139.84</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.533333</td>
<td>736</td>
<td>736</td>
<td>625.6</td>
<td>404.8</td>
<td>279.68</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.2xlarge</td>
<td>8</td>
<td>64</td>
<td>3.066666</td>
<td>1472</td>
<td>1472</td>
<td>1251.2</td>
<td>809.6</td>
<td>559.36</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.3xlarge</td>
<td>12</td>
<td>96</td>
<td>4.6</td>
<td>2208</td>
<td>2208</td>
<td>1876.8</td>
<td>1214.4</td>
<td>839.04</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.4xlarge</td>
<td>16</td>
<td>128</td>
<td>6.133333</td>
<td>2944</td>
<td>2944</td>
<td>2502.4</td>
<td>1619.2</td>
<td>1118.72</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.6xlarge</td>
<td>24</td>
<td>192</td>
<td>9.2</td>
<td>4416</td>
<td>4416</td>
<td>3753.6</td>
<td>2428.8</td>
<td>1678.08</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.8xlarge</td>
<td>32</td>
<td>256</td>
<td>12.266666</td>
<td>5888</td>
<td>5888</td>
<td>5004.8</td>
<td>3238.4</td>
<td>2237.44</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.12xlarge</td>
<td>48</td>
<td>384</td>
<td>18.4</td>
<td>8832</td>
<td>8832</td>
<td>7507.2</td>
<td>4857.6</td>
<td>3356.16</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr7.24xlarge</td>
<td>96</td>
<td>768</td>
<td>36.8</td>
<td>17664</td>
<td>17664</td>
<td>15014.4</td>
<td>9715.2</td>
<td>6712.32</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.large</td>
<td>2</td>
<td>16</td>
<td>0.729166</td>
<td>350</td>
<td>350</td>
<td>297.5</td>
<td>192.5</td>
<td>133</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.458333</td>
<td>700</td>
<td>700</td>
<td>595</td>
<td>385</td>
<td>266</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.2xlarge</td>
<td>8</td>
<td>64</td>
<td>2.916666</td>
<td>1400</td>
<td>1400</td>
<td>1190</td>
<td>770</td>
<td>532</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.3xlarge</td>
<td>12</td>
<td>96</td>
<td>4.375</td>
<td>2100</td>
<td>2100</td>
<td>1785</td>
<td>1155</td>
<td>798</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.4xlarge</td>
<td>16</td>
<td>128</td>
<td>5.833333</td>
<td>2800</td>
<td>2800</td>
<td>2380</td>
<td>1540</td>
<td>1064</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.6xlarge</td>
<td>24</td>
<td>192</td>
<td>8.75</td>
<td>4200</td>
<td>4200</td>
<td>3570</td>
<td>2310</td>
<td>1596</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.8xlarge</td>
<td>32</td>
<td>256</td>
<td>11.666666</td>
<td>5600</td>
<td>5600</td>
<td>4760</td>
<td>3080</td>
<td>2128</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.10xlarge</td>
<td>40</td>
<td>384</td>
<td>14.583333</td>
<td>7000</td>
<td>7000</td>
<td>5950</td>
<td>3850</td>
<td>2660</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.16xlarge</td>
<td>64</td>
<td>512</td>
<td>23.333333</td>
<td>11200</td>
<td>11200</td>
<td>9520</td>
<td>6160</td>
<td>4256</td>
</tr>
<tr>
<td>高主频内存型 ecs.hfr6.20xlarge</td>
<td>80</td>
<td>768</td>
<td>29.166666</td>
<td>14000</td>
<td>14000</td>
<td>11900</td>
<td>7700</td>
<td>5320</td>
</tr>
<tr>
<td>GPU虚拟化型 ecs.sgn7i-vws-m2.xlarge</td>
<td>4</td>
<td>15.5</td>
<td>1.866512</td>
<td>895.93</td>
<td>895.93</td>
<td>761.54</td>
<td>492.76</td>
<td>340.45</td>
</tr>
<tr>
<td>GPU虚拟化型 ecs.sgn7i-vws-m4.2xlarge</td>
<td>8</td>
<td>31</td>
<td>3.117293</td>
<td>1496.3</td>
<td>1496.3</td>
<td>1271.86</td>
<td>822.97</td>
<td>568.59</td>
</tr>
<tr>
<td>GPU虚拟化型 ecs.sgn7i-vws-m8.4xlarge</td>
<td>16</td>
<td>62</td>
<td>5.618855</td>
<td>2697.05</td>
<td>2697.05</td>
<td>2292.49</td>
<td>1483.38</td>
<td>1024.88</td>
</tr>
<tr>
<td>GPU虚拟化型 ecs.sgn7i-vws-m2s.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.827</td>
<td>877.15</td>
<td>877.15</td>
<td>745.57</td>
<td>482.43</td>
<td>333.32</td>
</tr>
<tr>
<td>GPU虚拟化型 ecs.sgn7i-vws-m4s.2xlarge</td>
<td>8</td>
<td>16</td>
<td>3.078</td>
<td>1477.52</td>
<td>1477.52</td>
<td>1255.89</td>
<td>812.64</td>
<td>561.46</td>
</tr>
<tr>
<td>GPU虚拟化型 ecs.sgn7i-vws-m8s.4xlarge</td>
<td>16</td>
<td>32</td>
<td>5.58</td>
<td>2678.27</td>
<td>2678.27</td>
<td>2276.53</td>
<td>1473.05</td>
<td>1017.74</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c8g1.2xlarge</td>
<td>8</td>
<td>30</td>
<td>12.710156</td>
<td>6100.88</td>
<td>6100.88</td>
<td>5185.74</td>
<td>3355.48</td>
<td>2318.33</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c16g1.4xlarge</td>
<td>16</td>
<td>60</td>
<td>13.457812</td>
<td>6459.75</td>
<td>6459.75</td>
<td>5490.79</td>
<td>3552.86</td>
<td>2454.7</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c32g1.8xlarge</td>
<td>32</td>
<td>188</td>
<td>14.953125</td>
<td>7177.5</td>
<td>7177.5</td>
<td>6100.88</td>
<td>3947.63</td>
<td>2727.45</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c32g1.16xlarge</td>
<td>64</td>
<td>376</td>
<td>29.90625</td>
<td>14355</td>
<td>14355</td>
<td>12201.75</td>
<td>7895.25</td>
<td>5454.9</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn7i-c32g1.32xlarge</td>
<td>128</td>
<td>752</td>
<td>59.8125</td>
<td>28710</td>
<td>28710</td>
<td>24403.5</td>
<td>15790.5</td>
<td>10909.8</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>2845.8</td>
<td>1841.4</td>
<td>1272.24</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>3427.2</td>
<td>2217.6</td>
<td>1532.16</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>4016.25</td>
<td>2598.75</td>
<td>1795.5</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>4207.5</td>
<td>2722.5</td>
<td>1881</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>8415</td>
<td>5445</td>
<td>3762</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>16830</td>
<td>10890</td>
<td>7524</td>
</tr>
<tr>
<td>计算型弹性裸金属服务器 ecs.ebmc6.26xlarge</td>
<td>104</td>
<td>192</td>
<td>20.26</td>
<td>9724</td>
<td>9724</td>
<td>8265.4</td>
<td>5348.2</td>
<td>3695.12</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>26</td>
<td>12480</td>
<td>12480</td>
<td>10608</td>
<td>6864</td>
<td>4742.4</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>突发性能型 ecs.t6-c2m1.large</td>
<td>2</td>
<td>1</td>
<td>0.059</td>
<td>17</td>
<td>17</td>
<td>14.45</td>
<td>9.35</td>
<td>6.46</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m1.large</td>
<td>2</td>
<td>2</td>
<td>0.118</td>
<td>34</td>
<td>34</td>
<td>28.9</td>
<td>18.7</td>
<td>12.92</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.236</td>
<td>68</td>
<td>68</td>
<td>57.8</td>
<td>37.4</td>
<td>25.84</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.472</td>
<td>136</td>
<td>136</td>
<td>115.6</td>
<td>74.8</td>
<td>51.68</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.944</td>
<td>272</td>
<td>272</td>
<td>231.2</td>
<td>149.6</td>
<td>103.36</td>
</tr>
<tr>
<td>突发性能型 ecs.t6-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>1.889</td>
<td>544</td>
<td>544</td>
<td>462.4</td>
<td>299.2</td>
<td>206.72</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m1.small</td>
<td>1</td>
<td>1</td>
<td>0.115</td>
<td>33</td>
<td>33</td>
<td>28.05</td>
<td>18.15</td>
<td>12.54</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m2.small</td>
<td>1</td>
<td>2</td>
<td>0.208</td>
<td>60</td>
<td>60</td>
<td>51</td>
<td>33</td>
<td>22.8</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m4.small</td>
<td>1</td>
<td>4</td>
<td>0.312</td>
<td>90</td>
<td>90</td>
<td>76.5</td>
<td>49.5</td>
<td>34.2</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m2.large</td>
<td>2</td>
<td>4</td>
<td>0.417</td>
<td>120</td>
<td>120</td>
<td>102</td>
<td>66</td>
<td>45.6</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m4.large</td>
<td>2</td>
<td>8</td>
<td>0.625</td>
<td>180</td>
<td>180</td>
<td>153</td>
<td>99</td>
<td>68.4</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.833</td>
<td>240</td>
<td>240</td>
<td>204</td>
<td>132</td>
<td>91.2</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.25</td>
<td>360</td>
<td>360</td>
<td>306</td>
<td>198</td>
<td>136.8</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m2.2xlarge</td>
<td>8</td>
<td>16</td>
<td>1.667</td>
<td>480</td>
<td>480</td>
<td>408</td>
<td>264</td>
<td>182.4</td>
</tr>
<tr>
<td>共享标准型 ecs.s6-c1m4.2xlarge</td>
<td>8</td>
<td>32</td>
<td>2.5</td>
<td>720</td>
<td>720</td>
<td>612</td>
<td>396</td>
<td>273.6</td>
</tr>
<tr>
<td>共享基本型 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>共享计算型 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>共享计算型 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>共享计算型 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>共享计算型 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>共享计算型 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>共享计算型 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>共享通用型 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>共享通用型 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>共享通用型 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>共享通用型 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>共享通用型 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>共享通用型 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>共享内存型 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>共享内存型 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>共享内存型 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>共享内存型 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>共享内存型 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>
</tbody>
</table>
<h5>2、阿里云服务器活动价格表</h5>
目前阿里云服务器产品国内地域有共享型s6、计算型c6/c7、通用型g6/g7、内存型r6/r7系列云服务器参与活动，国外地域有计算优化型c6、通用算力型g6和内存优化型r6系列云服务器参与活动。活动价格最低的是共享型s6实例1核1配置，19.17元/3个月、306.72元/1年。在实际购买过程中，还可以使用阿里云赠送的满减优惠券再减免20元-1000元，详细活动价格及券后价格表如下：
<table>
<thead>
<tr>
<th>云服务器实例</th>
<th>配置</th>
<th>带宽</th>
<th>系统盘容量</th>
<th>活动价格</th>
<th>可使用满减优惠券金额</th>
<th>券后价格</th>
</tr>
</thead>
<tbody>
<tr>
<td>共享型s6</td>
<td>1核1G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>19.17元/3个月起、306.72元/1年起</td>
<td>20元</td>
<td>286.72元/1年起</td>
</tr>
<tr>
<td>共享型s6</td>
<td>1核2G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>26.46元/3个月起、423.36元/1年起</td>
<td>20元</td>
<td>403.36元/1年起</td>
</tr>
<tr>
<td>共享型s6</td>
<td>2核4G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>42.66元/3个月起、682.56元/1年起</td>
<td>35元</td>
<td>647.56元/1年起</td>
</tr>
<tr>
<td>共享型s6</td>
<td>2核8G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>58.86元/3个月起、941.76元/1年起</td>
<td>60元</td>
<td>881.76元/1年起</td>
</tr>
<tr>
<td>共享型s6</td>
<td>4核8G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>75.06元/3个月起、1200.96元/1年起</td>
<td>80元</td>
<td>1120.96元/1年起</td>
</tr>
<tr>
<td>共享型s6</td>
<td>4核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>107.46元/3个月起、1719.36元/1年起</td>
<td>120元</td>
<td>1599.36元/1年起</td>
</tr>
<tr>
<td>共享型s6</td>
<td>8核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>139.86元/3个月起、2237.76元/1年起</td>
<td>160元</td>
<td>2077.76元/1年起</td>
</tr>
<tr>
<td>共享型s6</td>
<td>8核32G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>204.66元/3个月起、3274.56元/1年起</td>
<td>240元</td>
<td>3034.56元/1年起</td>
</tr>
<tr>
<td>计算型c6</td>
<td>2核4G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>892.80元/1年起</td>
<td>60元</td>
<td>832.80元/1年起</td>
</tr>
<tr>
<td>计算型c6</td>
<td>4核8G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>1521.60元/1年起</td>
<td>120元</td>
<td>1401.60元/1年起</td>
</tr>
<tr>
<td>计算型c6</td>
<td>8核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>2779.20元/1年起</td>
<td>160元</td>
<td>2619.20元/1年起</td>
</tr>
<tr>
<td>通用型g6</td>
<td>2核8G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>1329.60元/1年起</td>
<td>80元</td>
<td>962.80元/1年起</td>
</tr>
<tr>
<td>通用型g6</td>
<td>4核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>2481.60元/1年起</td>
<td>160元</td>
<td>2321.60元/1年起</td>
</tr>
<tr>
<td>通用型g6</td>
<td>8核32G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>4785.60元/1年起</td>
<td>240元</td>
<td>4545.60元/1年起</td>
</tr>
<tr>
<td>内存型r6</td>
<td>2核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>1704.00元/1年起</td>
<td>120元</td>
<td>1584.00元/1年起</td>
</tr>
<tr>
<td>内存型r6</td>
<td>4核32G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>3230.40元/1年起</td>
<td>240元</td>
<td>2990.40元/1年起</td>
</tr>
<tr>
<td>内存型r6</td>
<td>8核64G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>6283.0元/1年起</td>
<td>500元</td>
<td>5783.20元/1年起</td>
</tr>
<tr>
<td>计算型c7</td>
<td>2核4G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>1145.74元/1年起</td>
<td>80元</td>
<td>1065.74元/1年起</td>
</tr>
<tr>
<td>计算型c7</td>
<td>4核8G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>2085.08元/1年起</td>
<td>160元</td>
<td>2069.08元/1年起</td>
</tr>
<tr>
<td>计算型c7</td>
<td>8核16G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>3963.75元/1年起</td>
<td>240元</td>
<td>3723.75元/1年起</td>
</tr>
<tr>
<td>通用型g7</td>
<td>2核8G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>1411.97元/1年起</td>
<td>80元</td>
<td>1331.97元/1年起</td>
</tr>
<tr>
<td>通用型g7</td>
<td>4核16G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>2617.54元/1年起</td>
<td>160元</td>
<td>2457.54元/1年起</td>
</tr>
<tr>
<td>通用型g7</td>
<td>8核32G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>5028.67元/1年起</td>
<td>500元</td>
<td>4528.67元/1年起</td>
</tr>
<tr>
<td>内存型r7</td>
<td>2核16G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>1810.49元/1年起</td>
<td>120元</td>
<td>1690.49元/1年起</td>
</tr>
<tr>
<td>内存型r7</td>
<td>4核32G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>3414.59元/1年起</td>
<td>240元</td>
<td>3174.59元/1年起</td>
</tr>
<tr>
<td>内存型r7</td>
<td>8核64G</td>
<td>1M-10M</td>
<td>40-100G ESSD云盘</td>
<td>6622.78元/1年起</td>
<td>500元</td>
<td>6122.78元/1年起</td>
</tr>
<tr>
<td>计算优化型c6（国外地域）</td>
<td>2核4G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>1797.36元/1年起</td>
<td>120元</td>
<td>1677.36元/1年起</td>
</tr>
<tr>
<td>计算优化型c6（国外地域）</td>
<td>4核8G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>3383元/1年起</td>
<td>240元</td>
<td>3143.52元/1年起</td>
</tr>
<tr>
<td>计算优化型c6（国外地域）</td>
<td>8核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>6555.84元/1年起</td>
<td>500元</td>
<td>6055.84元/1年起</td>
</tr>
<tr>
<td>通用算力型g6（国外地域）</td>
<td>2核8G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>2223.36元/1年起</td>
<td>160元</td>
<td>2063.36元/1年起</td>
</tr>
<tr>
<td>通用算力型g6（国外地域）</td>
<td>4核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>4235.52元/1年起</td>
<td>240元</td>
<td>3995.52元/1年起</td>
</tr>
<tr>
<td>通用算力型g6（国外地域）</td>
<td>8核32G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>8259.84元/1年起</td>
<td>500元</td>
<td>7759.84元/1年起</td>
</tr>
<tr>
<td>内存优化型r6（国外地域）</td>
<td>2核16G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>2696.78元/1年起</td>
<td>160元</td>
<td>2536.78元/1年起</td>
</tr>
<tr>
<td>内存优化型r6（国外地域）</td>
<td>4核32G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>5182.37元/1年起</td>
<td>500元</td>
<td>4682.37元/1年起</td>
</tr>
<tr>
<td>内存优化型r6（国外地域）</td>
<td>8核64G</td>
<td>1M-5M</td>
<td>40-100G</td>
<td>10153.54元/1年起</td>
<td>1000元</td>
<td>9153.54元/1年起</td>
</tr>
</tbody>
</table>

活动直达：点此进入阿里云服务器新人特惠活动
领券直达：点此进入阿里云官网领券中心



https://upload-images.jianshu.io/upload_images/19316870-1ddce38e5877a0bd.png



<h2>二、阿里云轻量应用服务器收费标准及活动价格表</h2>
<h5>1、阿里云轻量应用服务器收费标准</h5>
轻量应用服务器价格主要有配置、带宽、系统盘容量和流量决定，目前阿里云轻量应用服务器最低配置为1核1G，最高配置为2核8G，最新收费标准如下：
<table>
<thead>
<tr>
<th>云服务器实例</th>
<th>配置</th>
<th>带宽</th>
<th>系统盘容量</th>
<th>流量</th>
<th>收费标准</th>
</tr>
</thead>
<tbody>
<tr>
<td>轻量应用服务器</td>
<td>1核1G</td>
<td>1Mbps</td>
<td>20GB SSD云盘</td>
<td>-</td>
<td>60元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>1核1G</td>
<td>3Mbps</td>
<td>40GB SSD云盘</td>
<td>500GB</td>
<td>95元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>1核2G</td>
<td>5Mbps</td>
<td>40GB SSD云盘</td>
<td>1000GB</td>
<td>145元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核1G</td>
<td>3Mbps</td>
<td>40GB ESSD</td>
<td>400GB</td>
<td>60元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核1G</td>
<td>4Mbps</td>
<td>50GB ESSD</td>
<td>600GB</td>
<td>70元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核2G</td>
<td>4Mbps</td>
<td>50GB ESSD</td>
<td>800GB</td>
<td>90元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核2G</td>
<td>5Mbps</td>
<td>60GB ESSD</td>
<td>1000GB</td>
<td>100元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核4G</td>
<td>5Mbps</td>
<td>60GB ESSD</td>
<td>1100GB</td>
<td>130元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核4G</td>
<td>6Mbps</td>
<td>80GB ESSD</td>
<td>1200GB</td>
<td>140元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核4G</td>
<td>8Mbps</td>
<td>100GB ESSD</td>
<td>1500GB</td>
<td>255元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核8G</td>
<td>10Mbps</td>
<td>120GB ESSD</td>
<td>2000GB</td>
<td>350元/月</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核8G</td>
<td>10Mbps</td>
<td>80GB ESSD</td>
<td>2000GB</td>
<td>360元/月</td>
</tr>
</tbody>
</table>
<h5>2、阿里云轻量应用服务器活动价格表</h5>
目前阿里云轻量应用服务器有2核2G和2核4G配置参与活动，2核2G活动价格99元1年，每天仅需0.27元；2核4G活动价格196.8元1年，每天只要0.53元，由于活动价格较低，因此，轻量应用服务器不支持使用满减优惠券，具体活动价格表如下：
<table>
<thead>
<tr>
<th>云服务器实例</th>
<th>配置</th>
<th>带宽</th>
<th>系统盘容量</th>
<th>活动价格</th>
</tr>
</thead>
<tbody>
<tr>
<td>轻量应用服务器</td>
<td>2核2G</td>
<td>3M</td>
<td>50GB ESSD</td>
<td>99.00元/1年起</td>
</tr>
<tr>
<td>轻量应用服务器</td>
<td>2核4G</td>
<td>4M</td>
<td>60GB ESSD</td>
<td>196.00元/1年起</td>
</tr>
</tbody>
</table>

购买直达：点此进入阿里云官方云小站平台
说明：云小站平台会不定期发布云产品通用代金券以供新用户领取，实时的代金券金额以云小站平台展示为准。



https://upload-images.jianshu.io/upload_images/19316870-4bdfc920114c52c2.png

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

<h2>三、阿里云gpu云服务器收费标准及活动价格表</h2>
<h5>1、阿里云gpu云服务器收费标准</h5>
GPU云服务器计费相关功能与云服务器ECS一致，一台GPU实例包括计算资源（vCPU和内存）、镜像、块存储等资源，最新收费标准如下表所示：
<table>
<thead>
<tr>
<th>规格族</th>
<th>实例规格</th>
<th>vCPU</th>
<th>内存</th>
<th>GPU/FPGA</th>
<th>本地存储</th>
<th>处理器主频/睿频</th>
<th>内网带宽</th>
<th>内网收发包</th>
<th>存储IOPS基准/峰值</th>
<th>收费标准参考</th>
</tr>
</thead>
<tbody>
<tr>
<td>GPU计算型 gn7e</td>
<td>ecs.gn7e-c16g1.4xlarge</td>
<td>16 vCPU</td>
<td>125 GiB</td>
<td>1 * NVIDIA A100 80G</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>最高 25 Gbps</td>
<td>300 万 PPS</td>
<td>8 万/11 万</td>
<td>￥ 16676.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn7e</td>
<td>ecs.gn7e-c16g1.16xlarge</td>
<td>64 vCPU</td>
<td>500 GiB</td>
<td>4 * NVIDIA A100 80G</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>32 Gbps</td>
<td>1200 万 PPS</td>
<td>30 万/-</td>
<td>￥ 66704.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn7i</td>
<td>ecs.gn7i-c8g1.2xlarge</td>
<td>8 vCPU</td>
<td>30 GiB</td>
<td>1 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>16 Gbps</td>
<td>160 万 PPS</td>
<td>12 万/-</td>
<td>￥ 6100.88 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn7i</td>
<td>ecs.gn7i-c16g1.4xlarge</td>
<td>16 vCPU</td>
<td>60 GiB</td>
<td>1 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>16 Gbps</td>
<td>300 万 PPS</td>
<td>12 万/-</td>
<td>￥ 6459.75 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn7i</td>
<td>ecs.gn7i-c32g1.8xlarge</td>
<td>32 vCPU</td>
<td>188 GiB</td>
<td>1 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>16 Gbps</td>
<td>600 万 PPS</td>
<td>12 万/-</td>
<td>￥ 7177.5 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn7i</td>
<td>ecs.gn7i-c48g1.12xlarge</td>
<td>48 vCPU</td>
<td>310 GiB</td>
<td>1 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>16 Gbps</td>
<td>900 万 PPS</td>
<td>15 万/-</td>
<td>￥ 8613.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn7i</td>
<td>ecs.gn7i-c56g1.14xlarge</td>
<td>56 vCPU</td>
<td>346 GiB</td>
<td>1 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>16 Gbps</td>
<td>1000 万 PPS</td>
<td>15 万/-</td>
<td>￥ 10335.6 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn7i</td>
<td>ecs.gn7i-c32g1.16xlarge</td>
<td>64 vCPU</td>
<td>376 GiB</td>
<td>2 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>32 Gbps</td>
<td>1200 万 PPS</td>
<td>24 万/-</td>
<td>￥ 14355.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn7i</td>
<td>ecs.gn7i-c32g1.32xlarge</td>
<td>128 vCPU</td>
<td>752 GiB</td>
<td>4 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>64 Gbps</td>
<td>2400 万 PPS</td>
<td>48 万/-</td>
<td>￥ 28710.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6v</td>
<td>ecs.gn6v-c8g1.2xlarge</td>
<td>8 vCPU</td>
<td>32 GiB</td>
<td>1 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>2.5 Gbps</td>
<td>80 万 PPS</td>
<td>-</td>
<td>￥ 7620.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6v</td>
<td>ecs.gn6v-c8g1.8xlarge</td>
<td>32 vCPU</td>
<td>128 GiB</td>
<td>4 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>10 Gbps</td>
<td>200 万 PPS</td>
<td>-</td>
<td>￥ 30480.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6v</td>
<td>ecs.gn6v-c8g1.16xlarge</td>
<td>64 vCPU</td>
<td>256 GiB</td>
<td>8 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>20 Gbps</td>
<td>250 万 PPS</td>
<td>-</td>
<td>￥ 60960.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6v</td>
<td>ecs.gn6v-c10g1.20xlarge</td>
<td>82 vCPU</td>
<td>336 GiB</td>
<td>8 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>35 Gbps</td>
<td>450 万 PPS</td>
<td>25 万/-</td>
<td>￥ 63255.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6i</td>
<td>ecs.gn6i-c4g1.xlarge</td>
<td>4 vCPU</td>
<td>15 GiB</td>
<td>1 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>4 Gbps</td>
<td>250 万 PPS</td>
<td>-</td>
<td>￥ 3348.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6i</td>
<td>ecs.gn6i-c8g1.2xlarge</td>
<td>8 vCPU</td>
<td>31 GiB</td>
<td>1 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>5 Gbps</td>
<td>250 万 PPS</td>
<td>-</td>
<td>￥ 4032.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6i</td>
<td>ecs.gn6i-c16g1.4xlarge</td>
<td>16 vCPU</td>
<td>62 GiB</td>
<td>1 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>6 Gbps</td>
<td>250 万 PPS</td>
<td>-</td>
<td>￥ 4725.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6i</td>
<td>ecs.gn6i-c24g1.6xlarge</td>
<td>24 vCPU</td>
<td>93 GiB</td>
<td>1 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>7.5 Gbps</td>
<td>250 万 PPS</td>
<td>-</td>
<td>￥ 4950.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6i</td>
<td>ecs.gn6i-c40g1.10xlarge</td>
<td>40 vCPU</td>
<td>155 GiB</td>
<td>1 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>10 Gbps</td>
<td>160 万 PPS</td>
<td>-</td>
<td>￥ 7112.9 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6i</td>
<td>ecs.gn6i-c24g1.12xlarge</td>
<td>48 vCPU</td>
<td>186 GiB</td>
<td>2 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>15 Gbps</td>
<td>450 万 PPS</td>
<td>-</td>
<td>￥ 9900.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6i</td>
<td>ecs.gn6i-c24g1.24xlarge</td>
<td>96 vCPU</td>
<td>372 GiB</td>
<td>4 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/2.7 GHz</td>
<td>30 Gbps</td>
<td>450 万 PPS</td>
<td>25 万/-</td>
<td>￥ 19800.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6e</td>
<td>ecs.gn6e-c12g1.3xlarge</td>
<td>12 vCPU</td>
<td>92 GiB</td>
<td>1 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>5 Gbps</td>
<td>80 万 PPS</td>
<td>-</td>
<td>￥ 9475.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6e</td>
<td>ecs.gn6e-c12g1.12xlarge</td>
<td>48 vCPU</td>
<td>368 GiB</td>
<td>4 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>16 Gbps</td>
<td>240 万 PPS</td>
<td>-</td>
<td>￥ 37900.0 /月</td>
</tr>
<tr>
<td>GPU 计算型 gn6e</td>
<td>ecs.gn6e-c12g1.24xlarge</td>
<td>96 vCPU</td>
<td>736 GiB</td>
<td>8 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>32 Gbps</td>
<td>450 万 PPS</td>
<td>-</td>
<td>￥ 75800.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c4g1.xlarge</td>
<td>4 vCPU</td>
<td>30 GiB</td>
<td>1 * NVIDIA P100</td>
<td>1 * 440 GiB</td>
<td>2.5 GHz/-</td>
<td>3 Gbps</td>
<td>30 万 PPS</td>
<td>-</td>
<td>￥ 3681.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c8g1.2xlarge</td>
<td>8 vCPU</td>
<td>60 GiB</td>
<td>1 * NVIDIA P100</td>
<td>1 * 440 GiB</td>
<td>2.5 GHz/-</td>
<td>3 Gbps</td>
<td>40 万 PPS</td>
<td>-</td>
<td>￥ 4433.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c4g1.2xlarge</td>
<td>8 vCPU</td>
<td>60 GiB</td>
<td>2 * NVIDIA P100</td>
<td>1 * 880 GiB</td>
<td>2.5 GHz/-</td>
<td>5 Gbps</td>
<td>100 万 PPS</td>
<td>-</td>
<td>￥ 7363.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c8g1.4xlarge</td>
<td>16 vCPU</td>
<td>120 GiB</td>
<td>2 * NVIDIA P100</td>
<td>1 * 880 GiB</td>
<td>2.5 GHz/-</td>
<td>5 Gbps</td>
<td>100 万 PPS</td>
<td>-</td>
<td>￥ 8866.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c28g1.7xlarge</td>
<td>28 vCPU</td>
<td>112 GiB</td>
<td>1 * NVIDIA P100</td>
<td>1 * 440 GiB</td>
<td>2.5 GHz/-</td>
<td>5 Gbps</td>
<td>225 万 PPS</td>
<td>-</td>
<td>￥ 6877.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c8g1.8xlarge</td>
<td>32 vCPU</td>
<td>240 GiB</td>
<td>4 * NVIDIA P100</td>
<td>1 * 1760 GiB</td>
<td>2.5 GHz/-</td>
<td>10 Gbps</td>
<td>200 万 PPS</td>
<td>-</td>
<td>￥ 17731.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c8g1.14xlarge</td>
<td>54 vCPU</td>
<td>480 GiB</td>
<td>8 * NVIDIA P100</td>
<td>2 * 1760 GiB</td>
<td>2.5 GHz/-</td>
<td>25 Gbps</td>
<td>400 万 PPS</td>
<td>-</td>
<td>￥ 35462.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5</td>
<td>ecs.gn5-c28g1.14xlarge</td>
<td>56 vCPU</td>
<td>224 GiB</td>
<td>2 * NVIDIA P100</td>
<td>1 * 880 GiB</td>
<td>2.5 GHz/-</td>
<td>10 Gbps</td>
<td>450 万 PPS</td>
<td>-</td>
<td>￥ 13753.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5i</td>
<td>ecs.gn5i-c2g1.large</td>
<td>2 vCPU</td>
<td>8 GiB</td>
<td>1 * NVIDIA P4</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>1 Gbps</td>
<td>10 万 PPS</td>
<td>-</td>
<td>￥ 2375.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5i</td>
<td>ecs.gn5i-c4g1.xlarge</td>
<td>4 vCPU</td>
<td>16 GiB</td>
<td>1 * NVIDIA P4</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>1.5 Gbps</td>
<td>20 万 PPS</td>
<td>-</td>
<td>￥ 2650.5 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5i</td>
<td>ecs.gn5i-c8g1.2xlarge</td>
<td>8 vCPU</td>
<td>32 GiB</td>
<td>1 * NVIDIA P4</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>2 Gbps</td>
<td>40 万 PPS</td>
<td>-</td>
<td>￥ 3192.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5i</td>
<td>ecs.gn5i-c16g1.4xlarge</td>
<td>16 vCPU</td>
<td>64 GiB</td>
<td>1 * NVIDIA P4</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>3 Gbps</td>
<td>80 万 PPS</td>
<td>-</td>
<td>￥ 4275.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5i</td>
<td>ecs.gn5i-c16g1.8xlarge</td>
<td>32 vCPU</td>
<td>128 GiB</td>
<td>2 * NVIDIA P4</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>6 Gbps</td>
<td>120 万 PPS</td>
<td>-</td>
<td>￥ 8550.0 /月</td>
</tr>
<tr>
<td>GPU计算型 gn5i</td>
<td>ecs.gn5i-c28g1.14xlarge</td>
<td>56 vCPU</td>
<td>224 GiB</td>
<td>2 * NVIDIA P4</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>10 Gbps</td>
<td>200 万 PPS</td>
<td>-</td>
<td>￥ 11780.0 /月</td>
</tr>
<tr>
<td>GPU 弹性裸金属服务器 ebmgn7e</td>
<td>ecs.ebmgn7e.32xlarge</td>
<td>128 vCPU</td>
<td>1024 GiB</td>
<td>8 * NVIDIA A100 80G</td>
<td>-</td>
<td>2.9 GHz/3.5 GHz</td>
<td>64 Gbps</td>
<td>2400 万 PPS</td>
<td>50 万/-</td>
<td>￥ 133408.0 /月</td>
</tr>
<tr>
<td>GPU 计算型弹性裸金属服务器 ebmgn7i</td>
<td>ecs.ebmgn7i.32xlarge</td>
<td>128 vCPU</td>
<td>768 GiB</td>
<td>4 * NVIDIA A10</td>
<td>-</td>
<td>2.9 GHz/3.4 GHz</td>
<td>64 Gbps</td>
<td>2400 万 PPS</td>
<td>48 万/-</td>
<td>￥ 28710.0 /月</td>
</tr>
<tr>
<td>GPU 计算型弹性裸金属服务器 ebmgn6ia</td>
<td>ecs.ebmgn6ia.20xlarge</td>
<td>80 vCPU</td>
<td>256 GiB</td>
<td>2 * NVIDIA T4</td>
<td>-</td>
<td>2.8 GHz/3.0 GHz</td>
<td>32 Gbps</td>
<td>2400 万 PPS</td>
<td>48 万/-</td>
<td>￥ 15842.97 /月</td>
</tr>
<tr>
<td>GPU图形计算型 gi6s</td>
<td>ecs.ebmgi6s.24xlarge</td>
<td>96 vCPU</td>
<td>384 GiB</td>
<td>1 * intel SG1</td>
<td>-</td>
<td>2.5 GHz/3.2 GHz</td>
<td>32 Gbps</td>
<td>480 万 PPS</td>
<td>25 万/-</td>
<td>￥ 7245.0 /月</td>
</tr>
<tr>
<td>GPU 计算型弹性裸金属服务器 ebmgn6v</td>
<td>ecs.ebmgn6v.24xlarge</td>
<td>96 vCPU</td>
<td>384 GiB</td>
<td>8 * Nvidia Tesla V100</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>30 Gbps</td>
<td>450 万 PPS</td>
<td>25 万/-</td>
<td>￥ 68292.0 /月</td>
</tr>
<tr>
<td>GPU 计算型弹性裸金属服务器 ebmgn6i</td>
<td>ecs.ebmgn6i.24xlarge</td>
<td>96 vCPU</td>
<td>384 GiB</td>
<td>4 * NVIDIA T4</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>30 Gbps</td>
<td>450 万 PPS</td>
<td>25 万/-</td>
<td>￥ 19800.0 /月</td>
</tr>
<tr>
<td>GPU 计算型弹性裸金属服务器 ebmgn6e</td>
<td>ecs.ebmgn6e.24xlarge</td>
<td>96 vCPU</td>
<td>768 GiB</td>
<td>8 * NVIDIA V100</td>
<td>-</td>
<td>2.5 GHz/-</td>
<td>32 Gbps</td>
<td>480 万 PPS</td>
<td>25 万/-</td>
<td>￥ 75800.0 /月</td>
</tr>
</tbody>
</table>
<h5>2、阿里云gpu云服务器活动价格表</h5>
目前阿里云gpu云服务器有gn6v、gn6i、vgn6i-vws、gn7i、gn7e等实例参与活动，活动价格最低的是vgn6i-vws实例4核23G配置，901.26元/1个月，完整的活动价格表如下：
<table>
<thead>
<tr>
<th>gpu云服务器实例</th>
<th>配置</th>
<th>显存</th>
<th>内存</th>
<th>活动价格（1个月）</th>
<th>活动价格（6个月）</th>
<th>活动价格（1年）</th>
<th>活动价格（2年）</th>
<th>活动价格（3年）</th>
</tr>
</thead>
<tbody>
<tr>
<td>gn6v</td>
<td>8核32G</td>
<td>16G显存V100计算卡</td>
<td>最高配置336G DDR4内存</td>
<td>4685.20元/1个月</td>
<td>25368.00元/6个月</td>
<td>36753.60元/1年</td>
<td>92144.40元/2年</td>
<td>83251.80元/3年</td>
</tr>
<tr>
<td>gn6v</td>
<td>32核128G</td>
<td>16G显存V100计算卡</td>
<td>最高配置336G DDR4内存</td>
<td>18629.80元/1个月</td>
<td>100806.00元/6个月</td>
<td>146481.60元/1年</td>
<td>366464.40元/2年</td>
<td>330139.80元/3年</td>
</tr>
<tr>
<td>gn6v</td>
<td>64核256G</td>
<td>16G显存V100计算卡</td>
<td>最高配置336G DDR4内存</td>
<td>37222.60元/1个月</td>
<td>201390.00元/6个月</td>
<td>292785.60元/1年</td>
<td>732224.40元/2年</td>
<td>659323.80元/3年</td>
</tr>
<tr>
<td>gn6v</td>
<td>82核336G</td>
<td>16G显存V100计算卡</td>
<td>最高配置336G DDR4内存</td>
<td>38615.55元/1个月</td>
<td>208963.50元/6个月</td>
<td>303801.60元/1年</td>
<td>759764.40元/2年</td>
<td>684109.80元/3年</td>
</tr>
<tr>
<td>gn6i</td>
<td>4核15G</td>
<td>16G显存T4计算卡</td>
<td>最高配置372G DDR4内存</td>
<td>1878.40元/1个月</td>
<td>9261.60元/6个月</td>
<td>14439.00元/1年</td>
<td>28827.60元/2年</td>
<td>37114.20元/3年</td>
</tr>
<tr>
<td>gn6i</td>
<td>8核31G</td>
<td>16G显存T4计算卡</td>
<td>最高配置372G DDR4内存</td>
<td>2254.60元/1个月</td>
<td>11108.40元/6个月</td>
<td>17311.80元/1年</td>
<td>34573.20元/2年</td>
<td>44501.40元/3年</td>
</tr>
<tr>
<td>gn6i</td>
<td>16核62G</td>
<td>16G显存T4计算卡</td>
<td>最高配置372G DDR4内存</td>
<td>2635.75元/1个月</td>
<td>12979.50元/6个月</td>
<td>20222.40元/1年</td>
<td>40394.40元/2年</td>
<td>51985.80元/3年</td>
</tr>
<tr>
<td>gn6i</td>
<td>24核93G</td>
<td>16G显存T4计算卡</td>
<td>最高配置372G DDR4内存</td>
<td>2759.50元/1个月</td>
<td>13587.00元/6个月</td>
<td>21167.40元/1年</td>
<td>42284.40元/2年</td>
<td>54415.80元/3年</td>
</tr>
<tr>
<td>gn6i</td>
<td>48核186G</td>
<td>16G显存T4计算卡</td>
<td>最高配置372G DDR4内存</td>
<td>5482.00元/1个月</td>
<td>26952.00元/6个月</td>
<td>41957.40元/1年</td>
<td>83864.40元/2年</td>
<td>107875.80元/3年</td>
</tr>
<tr>
<td>gn6i</td>
<td>96核372G</td>
<td>16G显存T4计算卡</td>
<td>最高配置372G DDR4内存</td>
<td>10927.00元/1个月</td>
<td>53682.00元/6个月</td>
<td>83537.40元/1年</td>
<td>167024.40元/2年</td>
<td>214092.00元/3年</td>
</tr>
<tr>
<td>gn6i</td>
<td>40核155G</td>
<td>16G显存T4计算卡</td>
<td>最高配置372G DDR4内存</td>
<td>3949.09元/1个月</td>
<td>19426.84元/6个月</td>
<td>30251.59元/1年</td>
<td>60452.78元/2年</td>
<td>77775.15元/3年</td>
</tr>
<tr>
<td>vgn6i-vws</td>
<td>4核23G</td>
<td>计算能力支持T4的1/4和1/2</td>
<td>GPU显存支持4GB和8GB</td>
<td>901.26元/1个月</td>
<td>4464.74元/6个月</td>
<td>6977.22元/1年</td>
<td>13904.04元/2年</td>
<td>17926.76元/3年</td>
</tr>
<tr>
<td>vgn6i-vws</td>
<td>10核46G</td>
<td>计算能力支持T4的1/4和1/2</td>
<td>GPU显存支持4GB和8GB</td>
<td>1597.11元/1个月</td>
<td>7880.70元/6个月</td>
<td>12290.93元/1年</td>
<td>24531.47元/2年</td>
<td>31590.60元/3年</td>
</tr>
<tr>
<td>gn7i</td>
<td>8核30G</td>
<td>24G显存A10计算卡</td>
<td>最高配置752G DDR4内存</td>
<td>5643.88元/1个月</td>
<td>35863.25元/6个月</td>
<td>29490.60元/1年</td>
<td>103299.90元/2年</td>
<td>121861.12元/3年</td>
</tr>
<tr>
<td>gn7i</td>
<td>16核60G</td>
<td>24G显存A10计算卡</td>
<td>最高配置752G DDR4内存</td>
<td>6002.75元/1个月</td>
<td>37878.50元/6个月</td>
<td>65093.45元/1年</td>
<td>108859.80元/2年</td>
<td>128263.05元/3年</td>
</tr>
<tr>
<td>gn7i</td>
<td>32核188G</td>
<td>24G显存A10计算卡</td>
<td>最高配置752G DDR4内存</td>
<td>6720.50元/1个月</td>
<td>42323.00元/6个月</td>
<td>34658.40元/1年</td>
<td>121387.20元/2年</td>
<td>143178.30元/3年</td>
</tr>
<tr>
<td>gn7i</td>
<td>56核346G</td>
<td>24G显存A10计算卡</td>
<td>最高配置752G DDR4内存</td>
<td>9378.60元/1个月</td>
<td>61271.60元/6个月</td>
<td>49817.28元/1年</td>
<td>174443.28元/2年</td>
<td>205708.68元/3年</td>
</tr>
<tr>
<td>gn7i</td>
<td>48核310G</td>
<td>24G显存A10计算卡</td>
<td>最高配置752G DDR4内存</td>
<td>8156.00元/1个月</td>
<td>50936.00元/6个月</td>
<td>41548.80元/1年</td>
<td>145503.60元/2年</td>
<td>171601.20元/3年</td>
</tr>
<tr>
<td>gn7i</td>
<td>64核376G</td>
<td>24G显存A10计算卡</td>
<td>最高配置752G DDR4内存</td>
<td>13398.00元/1个月</td>
<td>85388.00元/6个月</td>
<td>69110.40元/1年</td>
<td>241969.20元/2年</td>
<td>285292.80元/3年</td>
</tr>
<tr>
<td>gn7i</td>
<td>128核752G</td>
<td>24G显存A10计算卡</td>
<td>最高配置752G DDR4内存</td>
<td>27753.00元/1个月</td>
<td>171518.00元/6个月</td>
<td>138014.40元/1年</td>
<td>483133.20元/2年</td>
<td>569521.80元/3年</td>
</tr>
<tr>
<td>gn7e</td>
<td>16核125G</td>
<td>80G显存A100计算卡</td>
<td>最高配置1000G DDR4内存</td>
<td>15719.00元/1个月</td>
<td>99314.00元/6个月</td>
<td>80251.20元/1年</td>
<td>280962.00元/2年</td>
<td>331248.60元/3年</td>
</tr>
<tr>
<td>gn7e</td>
<td>64核500G</td>
<td>80G显存A100计算卡</td>
<td>最高配置1000G DDR4内存</td>
<td>65747.00元/1个月</td>
<td>399482.00元/6个月</td>
<td>320385.60元/1年</td>
<td>1121432.40元/2年</td>
<td>1321803.00元/3年</td>
</tr>
<tr>
<td>gn7e</td>
<td>128核1000G</td>
<td>80G显存A100计算卡</td>
<td>最高配置1000G DDR4内存</td>
<td>132451.00元/1个月</td>
<td>799706.00元/6个月</td>
<td>640564.80元/1年</td>
<td>2242059.60元/2年</td>
<td>2642542.20元/3年</td>
</tr>
</tbody>
</table>

购买直达：点此进入阿里云gpu云服务器特惠



https://upload-images.jianshu.io/upload_images/19316870-9eb9730c8542c1e2.png

<div class="image-caption">采购季gpu云服务器图.png

以上就是简书小编整理汇总的阿里云服务器、轻量应用服务器、gpu云服务器收费标准及活动价格表，随着时间的推移，活动价格可能会有所变换，实时的活动价格以阿里云官网活动中心展示为准。

查看完整版本: 阿里云服务器、轻量应用服务器、gpu云服务器收费标准及活动价格表