阿里云4核CPU云服务器收费标准与活动价格分享（4核4G、4核8G、4核16G、4核32G等）

谷哨扇

阿里云4核CPU云服务器多少钱？一般来说个人用户选择4核4G和4核8G配置比较多，企业用户通常会选择4核8G以上，例如4核16G、4核32G等。我们在实际购买中会发现，相同cpu核数的云服务器，还有不同的云服务器实例可选，价格差别也比较大，今天小编整理一份阿里云服务器4核CPU活动价格表，供大有参考：






<div class="image-caption">阿里云服务器优势图.png

阿里云服务器核数是指虚拟出来的CPU处理器的核心数量，准确来讲应该是vCPU。CPU核心数的大小代表了云服务器的运算能力，CPU越高，云服务器的性能越好。阿里云服务器1核CPU就是一个超线程，2核CPU2个超线程，4核CPU4个超线程，这样云服务器可以同时处理多个任务，计算性能更强。如果网站流程较小，少量图片展示的企业网站，建议选择2核及以上CPU；如果网站流量较大，动态页面比较多，有视频等，建议选择4核、8核以上CPU。
<h5>一、阿里云4核CPU云服务器可选实例规格及收费标准</h5>
阿里云4核CPU的云服务器除了目前活动中可以看到的经济型e和通用算力型u1等实例之外，还有共享标准型s6、AMD 计算型 c7a、内存型 r7p、高主频计算型 hfc7、计算平衡增强型 c6e、通用型 g6等50几种实例规格可选，cpu与内存搭配的配置有4核4G、4核8G、4核16G和4核32G，具体的可选实例规格及收费标准如下表所示：
<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>192.24</td>
<td>121.75</td>
<td>121.75</td>
</tr>
<tr>
<td>通用型 ecs.u1-c1m8.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.1925</td>
<td>572.4</td>
<td>572.4</td>
<td>343.44</td>
<td>217.51</td>
<td>217.51</td>
</tr>
<tr>
<td>通用型 ecs.u1-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.702</td>
<td>336.96</td>
<td>336.96</td>
<td>202.18</td>
<td>128.04</td>
<td>128.04</td>
</tr>
<tr>
<td>通用型 ecs.u1-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.9</td>
<td>432</td>
<td>432</td>
<td>259.2</td>
<td>164.16</td>
<td>164.16</td>
</tr>
<tr>
<td>ARM 内存型 ecs.r8y.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.085175</td>
<td>520.88</td>
<td>520.88</td>
<td>375.04</td>
<td>244.82</td>
<td>166.68</td>
</tr>
<tr>
<td>ARM 通用型 ecs.g8y.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.8</td>
<td>384</td>
<td>384</td>
<td>276.48</td>
<td>180.48</td>
<td>122.88</td>
</tr>
<tr>
<td>ARM 计算型 ecs.c8y.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.533866</td>
<td>256.26</td>
<td>256.26</td>
<td>184.5</td>
<td>120.44</td>
<td>82</td>
</tr>
<tr>
<td>AMD 内存平衡增强型 ecs.r8ae.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.5502</td>
<td>744.12</td>
<td>744.12</td>
<td>632.5</td>
<td>409.27</td>
<td>282.77</td>
</tr>
<tr>
<td>AMD 计算平衡增强型 ecs.c8ae.xlarge</td>
<td>4</td>
<td>8</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>AMD 通用平衡增强型 ecs.g8ae.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.1528</td>
<td>553.34</td>
<td>553.34</td>
<td>470.34</td>
<td>304.34</td>
<td>210.27</td>
</tr>
<tr>
<td>AMD 内存型 ecs.r8a.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.3595</td>
<td>652.54</td>
<td>652.54</td>
<td>554.66</td>
<td>358.89</td>
<td>247.96</td>
</tr>
<tr>
<td>AMD 计算型 ecs.c8a.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.7744</td>
<td>371.71</td>
<td>371.71</td>
<td>315.95</td>
<td>204.44</td>
<td>141.25</td>
</tr>
<tr>
<td>AMD 通用型 ecs.g8a.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.0208</td>
<td>489.98</td>
<td>489.98</td>
<td>416.49</td>
<td>269.49</td>
<td>186.19</td>
</tr>
<tr>
<td>内存型 ecs.r8i.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.4621</td>
<td>701.79</td>
<td>701.79</td>
<td>596.52</td>
<td>385.98</td>
<td>266.68</td>
</tr>
<tr>
<td>计算型 ecs.c8i.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.8562</td>
<td>410.96</td>
<td>410.96</td>
<td>349.32</td>
<td>226.03</td>
<td>156.17</td>
</tr>
<tr>
<td>通用型 ecs.g8i.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.0988</td>
<td>527.44</td>
<td>527.44</td>
<td>448.32</td>
<td>290.09</td>
<td>200.43</td>
</tr>
<tr>
<td>高主频计算型 ecs.hfc8i.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.9418</td>
<td>452.06</td>
<td>452.06</td>
<td>452.06</td>
<td>452.06</td>
<td>452.06</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>通用网络增强型 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>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>361.67</td>
<td>236.09</td>
<td>160.74</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>481.23</td>
<td>314.13</td>
<td>213.88</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>281.8</td>
<td>183.95</td>
<td>125.25</td>
</tr>
<tr>
<td>安全增强内存型 ecs.r7t.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.572112</td>
<td>754.61</td>
<td>754.61</td>
<td>641.42</td>
<td>415.04</td>
<td>286.75</td>
</tr>
<tr>
<td>安全增强通用型 ecs.g7t.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.2075</td>
<td>579.6</td>
<td>579.6</td>
<td>492.66</td>
<td>318.78</td>
<td>220.25</td>
</tr>
<tr>
<td>安全增强计算型 ecs.c7t.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.940843</td>
<td>451.61</td>
<td>451.61</td>
<td>383.86</td>
<td>248.38</td>
<td>171.61</td>
</tr>
<tr>
<td>AMD 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>AMD 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>AMD 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>存储增强内存型 ecs.r7se.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.721837</td>
<td>826.48</td>
<td>826.48</td>
<td>702.51</td>
<td>454.56</td>
<td>314.06</td>
</tr>
<tr>
<td>存储增强计算型 ecs.c7se.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.030447</td>
<td>494.62</td>
<td>494.62</td>
<td>420.42</td>
<td>272.04</td>
<td>187.95</td>
</tr>
<tr>
<td>存储增强通用型 ecs.g7se.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.3225</td>
<td>634.8</td>
<td>634.8</td>
<td>539.58</td>
<td>349.14</td>
<td>241.22</td>
</tr>
<tr>
<td>持久内存型 ecs.re7p.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.978</td>
<td>949.5</td>
<td>949.5</td>
<td>807.07</td>
<td>522.22</td>
<td>360.81</td>
</tr>
<tr>
<td>轻量级GPU ecs.vgn7i-vws-m4.xlarge</td>
<td>4</td>
<td>30</td>
<td>3.076559</td>
<td>1476.75</td>
<td>1476.75</td>
<td>1255.24</td>
<td>812.21</td>
<td>561.16</td>
</tr>
<tr>
<td>内存型 ecs.r7p.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.564</td>
<td>750.75</td>
<td>750.75</td>
<td>638.14</td>
<td>412.91</td>
<td>285.28</td>
</tr>
<tr>
<td>GPU共享型 ecs.sgn7i-vws-m2.xlarge</td>
<td>4</td>
<td>15.5</td>
<td>1.871086</td>
<td>898.12</td>
<td>898.12</td>
<td>763.4</td>
<td>493.97</td>
<td>341.29</td>
</tr>
<tr>
<td>GPU共享型 ecs.sgn7i-vws-m2s.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.831</td>
<td>878.99</td>
<td>878.99</td>
<td>747.14</td>
<td>483.44</td>
<td>334.02</td>
</tr>
<tr>
<td>计算网络增强型 ecs.c7nex.xlarge</td>
<td>4</td>
<td>8</td>
<td>1.0192</td>
<td>489.24</td>
<td>489.24</td>
<td>415.85</td>
<td>269.08</td>
<td>185.91</td>
</tr>
<tr>
<td>通用网络增强型 ecs.g7nex.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.3081</td>
<td>627.9</td>
<td>627.9</td>
<td>533.72</td>
<td>345.35</td>
<td>238.6</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>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>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>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>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>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>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>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>轻量级GPU ecs.vgn6i-m4.xlarge</td>
<td>4</td>
<td>23</td>
<td>2.445</td>
<td>1173.65</td>
<td>1173.65</td>
<td>997.6</td>
<td>645.51</td>
<td>445.99</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>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>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>持久内存型 ecs.re6p.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.978125</td>
<td>949.5</td>
<td>949.5</td>
<td>807.07</td>
<td>522.22</td>
<td>360.81</td>
</tr>
<tr>
<td>持久内存型 ecs.re6p-redis.xlarge</td>
<td>4</td>
<td>16</td>
<td>1.978</td>
<td>949.5</td>
<td>949.5</td>
<td>807.07</td>
<td>522.22</td>
<td>360.81</td>
</tr>
<tr>
<td>AMD 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>AMD 内存型 ecs.r6a.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>AMD 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>ARM 计算型 ecs.c6r.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.623333</td>
<td>299.2</td>
<td>299.2</td>
<td>254.32</td>
<td>164.56</td>
<td>113.7</td>
</tr>
<tr>
<td>ARM 通用型 ecs.g6r.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.8</td>
<td>384</td>
<td>384</td>
<td>326.4</td>
<td>211.2</td>
<td>145.92</td>
</tr>
<tr>
<td>轻量级GPU ecs.vgn6i-m4-vws.xlarge</td>
<td>4</td>
<td>23</td>
<td>3.273719</td>
<td>1571.39</td>
<td>1571.39</td>
<td>1335.68</td>
<td>864.26</td>
<td>597.13</td>
</tr>
<tr>
<td>GPU计算型 ecs.gn5-c4g1.xlarge</td>
<td>4</td>
<td>30</td>
<td>12.78</td>
<td>3681</td>
<td>3681</td>
<td>3128.85</td>
<td>1914.12</td>
<td>1288.35</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>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>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>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>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>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>本地SSD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>通用网络增强型 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>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.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>本地SSD型 ecs.i4.xlarge</td>
<td>4</td>
<td>32</td>
<td>1.914583</td>
<td>919</td>
<td>919</td>
<td>781.15</td>
<td>505.45</td>
<td>349.22</td>
</tr>
<tr>
<td>FPGA计算型 ecs.f3-c4f1.xlarge</td>
<td>4</td>
<td>16</td>
<td>7.312</td>
<td>3510</td>
<td>3510</td>
<td>2983.5</td>
<td>1930.5</td>
<td>3510</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>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>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>806.82</td>
<td>522.06</td>
<td>360.7</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>本地SSD型 ecs.i1.xlarge</td>
<td>4</td>
<td>16</td>
<td>2.94</td>
<td>649</td>
<td>616.55</td>
<td>486.75</td>
<td>292.05</td>
<td>194.7</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>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>通用平衡增强型 ecs.e-c1m4.xlarge</td>
<td>4</td>
<td>16</td>
<td>0.675</td>
<td>324</td>
<td>324</td>
<td>243</td>
<td>155.52</td>
<td>123.12</td>
</tr>
<tr>
<td>通用平衡增强型 ecs.e-c1m2.xlarge</td>
<td>4</td>
<td>8</td>
<td>0.45</td>
<td>216</td>
<td>216</td>
<td>162</td>
<td>103.68</td>
<td>82.08</td>
</tr>
</tbody>
</table>
<h5>二、阿里云4核CPU云服务器活动价格表</h5>
目前阿里云活动中4核cpu的云服务器有经济型e实例4核8G、4核16G；通用算力型u1实例4核4G、4核8G、4核16G、4核32G；计算型c7和c8y实例4核8G；通用型g7和g8y实例4核16G；内存型r7和r8y实例4核32G，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>1M带宽活动价格</th>
<th>2M带宽活动价格</th>
<th>3M带宽活动价格</th>
<th>4M带宽活动价格</th>
<th>5M带宽活动价格</th>
<th>活动价格（按量带宽）</th>
</tr>
</thead>
<tbody>
<tr>
<td>经济型e</td>
<td>4核8G</td>
<td>按量或1M-100M</td>
<td>20G ESSD Entry</td>
<td>1450.08元</td>
<td>1684.68元</td>
<td>1919.28元</td>
<td>2174.28元</td>
<td>2429.28元</td>
<td>2725.08元</td>
</tr>
<tr>
<td>经济型e</td>
<td>4核16G</td>
<td>按量或1M-100M</td>
<td>20G ESSD Entry</td>
<td>2149.92元</td>
<td>2384.52元</td>
<td>2619.12元</td>
<td>2874.12元</td>
<td>3129.12元</td>
<td>3424.92元</td>
</tr>
<tr>
<td>经济型e</td>
<td>4核8G</td>
<td>按量或1M-100M</td>
<td>20G ESSD云盘</td>
<td>1543.68元</td>
<td>1778.28元</td>
<td>2012.88元</td>
<td>2267.88元</td>
<td>2522.88元</td>
<td>2818.68元</td>
</tr>
<tr>
<td>经济型e</td>
<td>4核16G</td>
<td>按量或1M-100M</td>
<td>20G ESSD云盘</td>
<td>2243.52元</td>
<td>2478.12元</td>
<td>2712.72元</td>
<td>2967.72元</td>
<td>3222.72元</td>
<td>3518.52元</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核4G</td>
<td>1M-5M</td>
<td>40G ESSD Entry云盘</td>
<td>1916.52元</td>
<td>2151.12元</td>
<td>2406.12元</td>
<td>2661.12元</td>
<td>2956.92元</td>
<td>-</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核8G</td>
<td>1M-5M</td>
<td>40G ESSD Entry云盘</td>
<td>2030.57元</td>
<td>2265.17元</td>
<td>2520.17元</td>
<td>2775.17元</td>
<td>3070.97元</td>
<td>-</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核16G</td>
<td>1M-5M</td>
<td>40G ESSD Entry云盘</td>
<td>2512.68元</td>
<td>2747.28元</td>
<td>3002.28元</td>
<td>3257.28元</td>
<td>3553.08元</td>
<td>-</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核32G</td>
<td>1M-5M</td>
<td>40G ESSD Entry云盘</td>
<td>3181.42元</td>
<td>3416.02元</td>
<td>3671.02元</td>
<td>3926.02元</td>
<td>4221.82元</td>
<td>-</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核4G</td>
<td>1M-5M</td>
<td>40G ESSD云盘</td>
<td>1959.72元</td>
<td>2194.32元</td>
<td>2449.32元</td>
<td>2704.32元</td>
<td>3000.12元</td>
<td>-</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核8G</td>
<td>1M-5M</td>
<td>40G ESSD云盘</td>
<td>2073.77元</td>
<td>2308.37元</td>
<td>2563.37元</td>
<td>2818.37元</td>
<td>3114.17元</td>
<td>-</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核16G</td>
<td>1M-5M</td>
<td>40G ESSD云盘</td>
<td>2555.88元</td>
<td>2790.48元</td>
<td>3045.48元</td>
<td>3300.48元</td>
<td>3596.28元</td>
<td>-</td>
</tr>
<tr>
<td>通用算力型u1</td>
<td>4核32G</td>
<td>1M-5M</td>
<td>40G ESSD云盘</td>
<td>3224.62元</td>
<td>3459.22元</td>
<td>3714.22元</td>
<td>3969.22元</td>
<td>4265.02元</td>
<td>-</td>
</tr>
<tr>
<td>计算型c7</td>
<td>4核8G</td>
<td>1M-5M</td>
<td>40G ESSD云盘</td>
<td>3820.22元</td>
<td>4054.82元</td>
<td>4309.82元</td>
<td>4564.82元</td>
<td>4860.62元</td>
<td>-</td>
</tr>
<tr>
<td>通用型g7</td>
<td>4核16G</td>
<td>1M-5M</td>
<td>40G ESSD云盘</td>
<td>4778.64元</td>
<td>5013.24元</td>
<td>5268.24元</td>
<td>5523.24元</td>
<td>5819.04元</td>
<td>-</td>
</tr>
<tr>
<td>内存型r7</td>
<td>4核32G</td>
<td>1M-5M</td>
<td>40G ESSD云盘</td>
<td>6213.34元</td>
<td>6447.94元</td>
<td>6702.94元</td>
<td>6957.94元</td>
<td>7253.74元</td>
<td>-</td>
</tr>
</tbody>
</table>

购买活动直达：
1、阿里云服务器新人特惠：可购买阿里云最新活动云服务器。
2、阿里云活动中心：可查询阿里云实时活动及免费领取各种优惠券与代金券。
<h5>三、阿里云服务器CPU与内存选择建议</h5>

1、CPU核心数选择：
一般小型网站，如个人网站、中小型企业网站等，使用2核已经足够。而一些并发数据较多，中等网站的，使用4核大多能满足。像商城类、大型门户等，建议使用8核、16核及以上。

2、内存选择建议
内存-决定网站打开速度  内存是数据的中转站，也是决定网站打开速度的重要因素。内存越大，可用缓存越大，打开速度也就越快。可以根据网站的规模选择合适的配置，一般应用选择1G内存，超过50g的硬盘配置是足够的。如果对云服务器租用配置要求较高，你可以选择4G内存以上，建议和CPU同比例增长，比如1核选2G内存，2核选4G内存，4核选8G内存，8核选16G内存，大多数服务可以按这样来算，除了特殊性应用场景除外。
<h5>四、阿里云服务器实例规格选择建议</h5>

1、轻量应用服务器：属于轻量及云服务器产品，适用于各种轻负载场景，例如个人博客，企业展示型官网等。
2、经济型e实例：适用于Web应用及网站，企业办公类应用，数据分析和计算等大多数通用的对vCPU算力和性能要求不高的应用场景。
3、通用算力型u1实例：适用于Web应用及网站，企业办公类应用，数据分析和计算等大多数通用的对vCPU算力和性能要求不高的应用场景。
4、计算型c7、通用型g7、内存型r7实例：适用于企业级通用应用，视频编解码，游戏开发，高网络包收发场景，网站和应用服务器，中小型数据库系统、搜索集群等。
5、计算型c8y、通用型g8y、内存型r8y实例：适用于网站应用、各种类型和规模的企业级应用和容器、微服务、视频编解码、高性能计算、基于CPU的机器学习等场景的应用。