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闃块噷浜慻pu浜戞湇鍔″櫒澶氬皯閽憋紵2023骞磋喘涔伴樋閲屼簯gpu浜戞湇鍔″櫒鏈€浣庝粎闇€1500.00鍏?鏈堣捣锛岃喘涔拌交閲忓瀷GPU浜戞湇鍔″櫒鏈€浣?28.56鍏?鏈堣捣銆傞樋閲屼簯GPU浜戞湇鍔″櫒鏄熀浜嶨PU搴旂敤鐨勮绠楁湇鍔★紝澶氶€傜敤浜庤棰戣В鐮侊紝鍥惧舰娓叉煋锛屾繁搴﹀涔狅紝绉戝璁＄畻绛夊簲鐢ㄥ満鏅紝璇ヤ骇鍝佸叿鏈夎秴寮鸿绠楄兘鍔涖€佺綉缁滄€ц兘鍑鸿壊銆佽喘涔版柟寮忕伒娲汇€侀珮鎬ц兘瀹炰緥瀛樺偍( GA1鍜孏N5鐗规湁)绛夌壒鐐广€備笅闈㈠皬缂栨潵浠嬬粛涓嬮樋閲屼簯gpu浜戞湇鍔″櫒鏈€鏂扮殑鏀惰垂鏍囧噯鍙婃椿鍔ㄤ环鏍笺€?/p>
闃块噷浜慻pu浜戞湇鍔″櫒鍥?png
涓€銆侀樋閲屼簯gpu浜戞湇鍔″櫒2023骞存渶鏂版敹璐规爣鍑?/h5>
| 瑙勬牸鏃?/th> | 瀹炰緥瑙勬牸 | vCPU | 鍐呭瓨 | GPU/FPGA | 鏈湴瀛樺偍 | 澶勭悊鍣ㄤ富棰?鐫块 | 鍐呯綉甯﹀ | 鍐呯綉鏀跺彂鍖?/th> | 瀛樺偍IOPS鍩哄噯/宄板€?/th> | 鏀惰垂鏍囧噯鍙傝€冧环鏍?/th> |
|---|---|---|---|---|---|---|---|---|---|---|
| GPU璁＄畻鍨?gn7e | ecs.gn7e-c16g1.4xlarge | 16 vCPU | 125 GiB | 1 * NVIDIA A100 80G | - | 2.9 GHz/3.5 GHz | 鏈€楂?25 Gbps | 300 涓?PPS | 8 涓?11 涓?/td> | 锟?16676.0 /鏈?/td> |
| GPU璁＄畻鍨?gn7e | ecs.gn7e-c16g1.16xlarge | 64 vCPU | 500 GiB | 4 * NVIDIA A100 80G | - | 2.9 GHz/3.5 GHz | 32 Gbps | 1200 涓?PPS | 30 涓?- | 锟?66704.0 /鏈?/td> |
| GPU璁＄畻鍨?gn7e | ecs.gn7e-c16g1.32xlarge | 128 vCPU | 1000 GiB | 8 * NVIDIA A100 80G | - | 2.9 GHz/3.5 GHz | 64 Gbps | 2400 涓?PPS | 60 涓?- | 锟?133408.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn7i | ecs.gn7i-c8g1.2xlarge | 8 vCPU | 30 GiB | 1 * NVIDIA A10 | - | 2.9 GHz/3.5 GHz | 16 Gbps | 160 涓?PPS | 12 涓?- | 锟?6100.88 /鏈?/td> |
| GPU 璁＄畻鍨?gn7i | ecs.gn7i-c16g1.4xlarge | 16 vCPU | 60 GiB | 1 * NVIDIA A10 | - | 2.9 GHz/3.5 GHz | 16 Gbps | 300 涓?PPS | 12 涓?- | 锟?6459.75 /鏈?/td> |
| GPU 璁＄畻鍨?gn7i | ecs.gn7i-c32g1.8xlarge | 32 vCPU | 188 GiB | 1 * NVIDIA A10 | - | 2.9 GHz/3.5 GHz | 16 Gbps | 600 涓?PPS | 12 涓?- | 锟?7177.5 /鏈?/td> |
| GPU 璁＄畻鍨?gn7i | ecs.gn7i-c48g1.12xlarge | 48 vCPU | 310 GiB | 1 * NVIDIA A10 | - | 2.9 GHz/3.5 GHz | 16 Gbps | 900 涓?PPS | 15 涓?- | 锟?8613.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn7i | ecs.gn7i-c56g1.14xlarge | 56 vCPU | 346 GiB | 1 * NVIDIA A10 | - | 2.9 GHz/3.5 GHz | 16 Gbps | 1000 涓?PPS | 15 涓?- | 锟?10335.6 /鏈?/td> |
| GPU 璁＄畻鍨?gn7i | ecs.gn7i-c32g1.16xlarge | 64 vCPU | 376 GiB | 2 * NVIDIA A10 | - | 2.9 GHz/3.5 GHz | 32 Gbps | 1200 涓?PPS | 24 涓?- | 锟?14355.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn7i | ecs.gn7i-c32g1.32xlarge | 128 vCPU | 752 GiB | 4 * NVIDIA A10 | - | 2.9 GHz/3.5 GHz | 64 Gbps | 2400 涓?PPS | 48 涓?- | 锟?28710.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn7 | ecs.gn7-c12g1.3xlarge | 12 vCPU | 94 GiB | 1 * NVIDIA A100 | - | 2.5 GHz/3.2 GHz | 4 Gbps | 250 涓?PPS | 12.5 涓?- | 锟?15160.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6v | ecs.gn6v-c8g1.2xlarge | 8 vCPU | 32 GiB | 1 * NVIDIA V100 | - | 2.5 GHz/2.7 GHz | 2.5 Gbps | 80 涓?PPS | - | 锟?7620.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6v | ecs.gn6v-c8g1.8xlarge | 32 vCPU | 128 GiB | 4 * NVIDIA V100 | - | 2.5 GHz/2.7 GHz | 10 Gbps | 200 涓?PPS | - | 锟?30480.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6v | ecs.gn6v-c8g1.16xlarge | 64 vCPU | 256 GiB | 8 * NVIDIA V100 | - | 2.5 GHz/2.7 GHz | 20 Gbps | 250 涓?PPS | - | 锟?60960.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6v | ecs.gn6v-c10g1.20xlarge | 82 vCPU | 336 GiB | 8 * NVIDIA V100 | - | 2.5 GHz/2.7 GHz | 35 Gbps | 450 涓?PPS | 25 涓?- | 锟?63255.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6i | ecs.gn6i-c4g1.xlarge | 4 vCPU | 15 GiB | 1 * NVIDIA T4 | - | 2.5 GHz/2.7 GHz | 4 Gbps | 250 涓?PPS | - | 锟?3348.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6i | ecs.gn6i-c8g1.2xlarge | 8 vCPU | 31 GiB | 1 * NVIDIA T4 | - | 2.5 GHz/2.7 GHz | 5 Gbps | 250 涓?PPS | - | 锟?4032.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6i | ecs.gn6i-c16g1.4xlarge | 16 vCPU | 62 GiB | 1 * NVIDIA T4 | - | 2.5 GHz/2.7 GHz | 6 Gbps | 250 涓?PPS | - | 锟?4725.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6i | ecs.gn6i-c24g1.6xlarge | 24 vCPU | 93 GiB | 1 * NVIDIA T4 | - | 2.5 GHz/2.7 GHz | 7.5 Gbps | 250 涓?PPS | - | 锟?4950.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6i | ecs.gn6i-c40g1.10xlarge | 40 vCPU | 155 GiB | 1 * NVIDIA T4 | - | 2.5 GHz/2.7 GHz | 10 Gbps | 160 涓?PPS | - | 锟?7112.9 /鏈?/td> |
| GPU 璁＄畻鍨?gn6i | ecs.gn6i-c24g1.12xlarge | 48 vCPU | 186 GiB | 2 * NVIDIA T4 | - | 2.5 GHz/2.7 GHz | 15 Gbps | 450 涓?PPS | - | 锟?9900.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6i | ecs.gn6i-c24g1.24xlarge | 96 vCPU | 372 GiB | 4 * NVIDIA T4 | - | 2.5 GHz/2.7 GHz | 30 Gbps | 450 涓?PPS | 25 涓?- | 锟?19800.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6e | ecs.gn6e-c12g1.3xlarge | 12 vCPU | 92 GiB | 1 * NVIDIA V100 | - | 2.5 GHz/- | 5 Gbps | 80 涓?PPS | - | 锟?9475.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6e | ecs.gn6e-c12g1.12xlarge | 48 vCPU | 368 GiB | 4 * NVIDIA V100 | - | 2.5 GHz/- | 16 Gbps | 240 涓?PPS | - | 锟?37900.0 /鏈?/td> |
| GPU 璁＄畻鍨?gn6e | ecs.gn6e-c12g1.24xlarge | 96 vCPU | 736 GiB | 8 * NVIDIA V100 | - | 2.5 GHz/- | 32 Gbps | 450 涓?PPS | - | 锟?75800.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c4g1.xlarge | 4 vCPU | 30 GiB | 1 * NVIDIA P100 | 1 * 440 GiB | 2.5 GHz/- | 3 Gbps | 30 涓?PPS | - | 锟?3681.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c8g1.2xlarge | 8 vCPU | 60 GiB | 1 * NVIDIA P100 | 1 * 440 GiB | 2.5 GHz/- | 3 Gbps | 40 涓?PPS | - | 锟?4433.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c4g1.2xlarge | 8 vCPU | 60 GiB | 2 * NVIDIA P100 | 1 * 880 GiB | 2.5 GHz/- | 5 Gbps | 100 涓?PPS | - | 锟?7363.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c8g1.4xlarge | 16 vCPU | 120 GiB | 2 * NVIDIA P100 | 1 * 880 GiB | 2.5 GHz/- | 5 Gbps | 100 涓?PPS | - | 锟?8866.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c28g1.7xlarge | 28 vCPU | 112 GiB | 1 * NVIDIA P100 | 1 * 440 GiB | 2.5 GHz/- | 5 Gbps | 225 涓?PPS | - | 锟?6877.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c8g1.8xlarge | 32 vCPU | 240 GiB | 4 * NVIDIA P100 | 1 * 1760 GiB | 2.5 GHz/- | 10 Gbps | 200 涓?PPS | - | 锟?17731.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c8g1.14xlarge | 54 vCPU | 480 GiB | 8 * NVIDIA P100 | 2 * 1760 GiB | 2.5 GHz/- | 25 Gbps | 400 涓?PPS | - | 锟?35462.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5 | ecs.gn5-c28g1.14xlarge | 56 vCPU | 224 GiB | 2 * NVIDIA P100 | 1 * 880 GiB | 2.5 GHz/- | 10 Gbps | 450 涓?PPS | - | 锟?13753.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5i | ecs.gn5i-c2g1.large | 2 vCPU | 8 GiB | 1 * NVIDIA P4 | - | 2.5 GHz/- | 1 Gbps | 10 涓?PPS | - | 锟?2375.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5i | ecs.gn5i-c4g1.xlarge | 4 vCPU | 16 GiB | 1 * NVIDIA P4 | - | 2.5 GHz/- | 1.5 Gbps | 20 涓?PPS | - | 锟?2650.5 /鏈?/td> |
| GPU璁＄畻鍨?gn5i | ecs.gn5i-c8g1.2xlarge | 8 vCPU | 32 GiB | 1 * NVIDIA P4 | - | 2.5 GHz/- | 2 Gbps | 40 涓?PPS | - | 锟?3192.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5i | ecs.gn5i-c16g1.4xlarge | 16 vCPU | 64 GiB | 1 * NVIDIA P4 | - | 2.5 GHz/- | 3 Gbps | 80 涓?PPS | - | 锟?4275.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5i | ecs.gn5i-c16g1.8xlarge | 32 vCPU | 128 GiB | 2 * NVIDIA P4 | - | 2.5 GHz/- | 6 Gbps | 120 涓?PPS | - | 锟?8550.0 /鏈?/td> |
| GPU璁＄畻鍨?gn5i | ecs.gn5i-c28g1.14xlarge | 56 vCPU | 224 GiB | 2 * NVIDIA P4 | - | 2.5 GHz/- | 10 Gbps | 200 涓?PPS | - | 锟?11780.0 /鏈?/td> |
| GPU 寮规€ц８閲戝睘鏈嶅姟鍣?ebmgn7e | ecs.ebmgn7e.32xlarge | 128 vCPU | 1024 GiB | 8 * NVIDIA A100 80G | - | 2.9 GHz/3.5 GHz | 64 Gbps | 2400 涓?PPS | 50 涓?- | 锟?133408.0 /鏈?/td> |
| GPU 璁＄畻鍨嬪脊鎬ц８閲戝睘鏈嶅姟鍣?ebmgn7i | ecs.ebmgn7i.32xlarge | 128 vCPU | 768 GiB | 4 * NVIDIA A10 | - | 2.9 GHz/3.4 GHz | 64 Gbps | 2400 涓?PPS | 48 涓?- | 锟?28710.0 /鏈?/td> |
| GPU 璁＄畻鍨嬪脊鎬ц８閲戝睘鏈嶅姟鍣?ebmgn6v | ecs.ebmgn6v.24xlarge | 96 vCPU | 384 GiB | 8 * Nvidia Tesla V100 | - | 2.5 GHz/- | 30 Gbps | 450 涓?PPS | 25 涓?- | 锟?68292.0 /鏈?/td> |
| GPU 璁＄畻鍨嬪脊鎬ц８閲戝睘鏈嶅姟鍣?ebmgn6i | ecs.ebmgn6i.24xlarge | 96 vCPU | 384 GiB | 4 * NVIDIA T4 | - | 2.5 GHz/- | 30 Gbps | 450 涓?PPS | 25 涓?- | 锟?19800.0 /鏈?/td> |
| GPU 鍨嬭秴绾ц绠楅泦缇?sccgn6 | ecs.sccgn6.24xlarge | 96 vCPU | 384 GiB | 8 * Nvidia Tesla V100 | - | 2.5 GHz/- | 30 Gbps | 450 涓?PPS | - | 锟?71544.0 /鏈?/td> |
璐拱闃块噷浜慻pu浜戞湇鍔″櫒涔嬪墠鎺ㄨ崘鍏堥€氳繃闃块噷浜戝畼鏂瑰皬绔欏钩鍙?/a>棰嗗彇闃块噷浜戞渶鏂颁唬閲戝埜鍜屾姌鎵ｇ爜锛屽湪璐拱鏀粯璁㈠崟鐨勬椂鍊欙紝浣跨敤鎶樻墸鐮佸拰浠ｉ噾鍒歌揪鍒拌妭绾﹁喘涔版垚鏈殑鐩殑銆?br/> 浜戝皬绔欎唬閲戝埜鍥?/p>
浜屻€侀樋閲屼簯gpu浜戞湇鍔″櫒2023骞存椿鍔ㄤ环鏍艰〃
锛岃缁嗛厤缃強娲诲姩浠锋牸琛ㄥ涓嬶細| gpu浜戞湇鍔″櫒瀹炰緥 | 閰嶇疆 | 鏄惧瓨 | 澶囨敞 | 娲诲姩浠锋牸锛?涓湀锛?/th> | 娲诲姩浠锋牸锛?涓湀锛?/th> | 娲诲姩浠锋牸锛?骞达級 | 娲诲姩浠锋牸锛?骞达級 |
|---|---|---|---|---|---|---|---|
| GPU浜戞湇鍔″櫒gn6v | 8鏍?2G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA锛?6G鏄惧瓨V100璁＄畻鍗★紝336G DDR4鍐呭瓨 | 3048.00鍏?鏈堣捣 | 16002.00鍏?6鏈堣捣 | 27432.00鍏?骞磋捣 | 54864.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6v | 32鏍?28G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA锛?6G鏄惧瓨V100璁＄畻鍗★紝336G DDR4鍐呭瓨 | 12192.00鍏?鏈堣捣 | 64008.00鍏?6鏈堣捣 | 109728.00鍏?骞磋捣 | 219456.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6v | 64鏍?56G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA锛?6G鏄惧瓨V100璁＄畻鍗★紝336G DDR4鍐呭瓨 | 24384.00鍏?鏈堣捣 | 128016.00鍏?6鏈堣捣 | 219456.00鍏?骞磋捣 | 438912.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6v | 82鏍?36G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA锛?6G鏄惧瓨V100璁＄畻鍗★紝336G DDR4鍐呭瓨 | 25302.00鍏?鏈堣捣 | 132835.50鍏?6鏈堣捣 | 227718.00鍏?骞磋捣 | 455436.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6i | 4鏍?5G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝372G DDR4鍐呭瓨 | 1339.20鍏?鏈堣捣 | 7030.80鍏?6鏈堣捣 | 12052.80鍏?骞磋捣 | 24105.60鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6i | 8鏍?1G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝372G DDR4鍐呭瓨 | 1612.80鍏?鏈堣捣 | 8467.206鍏?鏈堣捣 | 14515.20鍏?骞磋捣 | 29030.40鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6i | 16鏍?2G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝372G DDR4鍐呭瓨 | 1890.00鍏?鏈堣捣 | 9922.506鍏?鏈堣捣 | 17010.00鍏?骞磋捣 | 34020.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6i | 24鏍?3G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝372G DDR4鍐呭瓨 | 1980.00鍏?鏈堣捣 | 10395.00鍏?6鏈堣捣 | 17820.00鍏?骞磋捣 | 35640.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6i | 40鏍?55G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝372G DDR4鍐呭瓨 | 2845.16鍏?鏈堣捣 | 14937.09鍏?6鏈堣捣 | 25606.44鍏?骞磋捣 | 51212.88鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6i | 48鏍?86G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝372G DDR4鍐呭瓨 | 3960.00鍏?鏈堣捣 | 20790.00鍏?6鏈堣捣 | 35640.00鍏?骞磋捣 | 71280.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6i | 96鏍?72G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝372G DDR4鍐呭瓨 | 7920.00鍏?鏈堣捣 | 41580.00鍏?6鏈堣捣 | 71280.00鍏?骞磋捣 | 142560.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒vgn6i | 4鏍?3G | 4GB鏈€灏忔樉瀛?/td> | 鍒嗙墖铏氭嫙鍖朑PU锛岃绠楄兘鍔涙敮鎸乀4鐨?/4鍜?/2锛孏PU鏄惧瓨鏀寔4GB鍜?GB | 469.46鍏?鏈堣捣 | 2464.67鍏?6鏈堣捣 | 4225.14鍏?骞磋捣 | 8450.28鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒vgn6i | 10鏍?4G | 4GB鏈€灏忔樉瀛?/td> | 鍒嗙墖铏氭嫙鍖朑PU锛岃绠楄兘鍔涙敮鎸乀4鐨?/4鍜?/2锛孏PU鏄惧瓨鏀寔4GB鍜?GB | 970.22鍏?鏈堣捣 | 5093.68鍏?6鏈堣捣 | 8732.02鍏?骞磋捣 | 17464.03鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒vgn6i | 4鏍?3G(vws) | 4GB鏈€灏忔樉瀛?/td> | 鍒嗙墖铏氭嫙鍖朑PU锛岃绠楄兘鍔涙敮鎸乀4鐨?/4鍜?/2锛孏PU鏄惧瓨鏀寔4GB鍜?GB | 628.56鍏?鏈堣捣 | 3299.92鍏?6鏈堣捣 | 5657.00鍏?骞磋捣 | 11314.01鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒vgn6i | 10鏍?6G(vws) | 4GB鏈€灏忔樉瀛?/td> | 鍒嗙墖铏氭嫙鍖朑PU锛岃绠楄兘鍔涙敮鎸乀4鐨?/4鍜?/2锛孏PU鏄惧瓨鏀寔4GB鍜?GB | 1134.62鍏?鏈堣捣 | 5956.78鍏?6鏈堣捣 | 10211.62鍏?骞磋捣 | 20423.23鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6e | 12鏍?2G | 32G鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 32G鏄惧瓨V100璁＄畻鍗★紝736G DDR4鍐呭瓨 | 3790.00鍏?鏈堣捣 | 19897.50鍏?6鏈堣捣 | 68220.00鍏?骞磋捣 | 68220.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6e | 48鏍?68G | 32G鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 32G鏄惧瓨V100璁＄畻鍗★紝736G DDR4鍐呭瓨 | 15160.00鍏?鏈堣捣 | 79590.00鍏?6鏈堣捣 | 136440.00鍏?骞磋捣 | 272880.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn6e | 96鏍?36G | 32G鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 32G鏄惧瓨V100璁＄畻鍗★紝736G DDR4鍐呭瓨 | 30320.00鍏?鏈堣捣 | 159180.00鍏?6鏈堣捣 | 272880.00鍏?骞磋捣 | 545760.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒ebmgn6i | 96鏍?84G | 64GB鏄惧瓨 | 閰嶇疆4寮燦VIDIA 16G鏄惧瓨T4璁＄畻鍗★紝384G DDR4鍐呭瓨 | 7920.00鍏?鏈堣捣 | 41580.00鍏?6鏈堣捣 | 71280.00鍏?骞磋捣 | 142560.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒ebmgn6v | 96鏍?84G | 128GB鏄惧瓨 | 閰嶇疆8寮燦VIDIA 16G鏄惧瓨V100璁＄畻鍗★紝384G DDR4鍐呭瓨 | 27316.80鍏?鏈堣捣 | 143413.20鍏?6鏈堣捣 | 245851.20鍏?骞磋捣 | 491702.40鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒ebmgn6e | 96鏍?88G | 256GB鏄惧瓨 | 閰嶇疆8寮燦VIDIA 32G鏄惧瓨V100璁＄畻鍗★紝768G DDR4鍐呭瓨 | 30320.00鍏?鏈堣捣 | 159180.00鍏?6鏈堣捣 | 272880.00鍏?骞磋捣 | 545760.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn5i | 2鏍?G | 8GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 8G鏄惧瓨P4璁＄畻鍗★紝224G DDR4鍐呭瓨 | 1500.00鍏?鏈堣捣 | 6750.00鍏?6鏈堣捣 | 12000.00鍏?骞磋捣 | 24000.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn5i | 4鏍?6G | 8GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 8G鏄惧瓨P4璁＄畻鍗★紝224G DDR4鍐呭瓨 | 1674.00鍏?鏈堣捣 | 7533.00鍏?6鏈堣捣 | 13392.00鍏?骞磋捣 | 26784.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn5i | 8鏍?2G | 8GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 8G鏄惧瓨P4璁＄畻鍗★紝224G DDR4鍐呭瓨 | 2016.00鍏?鏈堣捣 | 9072.00鍏?6鏈堣捣 | 16128.00鍏?骞磋捣 | 32256.00鍏?2骞磋捣 |
| GPU浜戞湇鍔″櫒gn5 | 4鏍?0G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨P100璁＄畻鍗★紝楂樻€ц兘NVMe SSD鏈湴鐩?/td> | 2222.60鍏?鏈堣捣 | 10022.70鍏?6鏈堣捣 | 17836.80鍏?骞磋捣 | - |
| GPU浜戞湇鍔″櫒gn5 | 8鏍?0G | 16GB鍗曞潡鏄惧瓨 | 鏈€楂橀厤缃?寮燦VIDIA 16G鏄惧瓨P100璁＄畻鍗★紝楂樻€ц兘NVMe SSD鏈湴鐩?/td> | 2673.80鍏?鏈堣捣 | 12053.10鍏?6鏈堣捣 | 21446.40鍏?骞磋捣 | - |
浠ヤ笂灏辨槸灏忕紪鎬荤粨鐨勯樋閲屼簯gpu浜戞湇鍔″櫒2023骞存渶鏂版敹璐规爣鍑嗗強娲诲姩浠锋牸琛紝濡傛灉浣犳槸鏂扮敤鎴凤紝闃块噷浜戣繕鎻愪緵gpu浜戞湇鍔″櫒璇曠敤鏈嶅姟锛屼釜浜烘柊鐢ㄦ埛鍙厤璐硅瘯鐢℅PU浜戞湇鍔″櫒gn6i瀹炰緥4鏍?5G閰嶇疆锛屽厤璐硅瘯鐢?鍛紝浼佷笟鏂扮敤鎴峰彲鍏嶈垂璇曠敤GPU浜戞湇鍔″櫒gn6v瀹炰緥8鏍?2G閰嶇疆鍜孏PU浜戞湇鍔″櫒gn6i瀹炰緥8鏍?1G閰嶇疆锛屽厤璐硅瘯鐢?鍛ㄣ€傞渶瑕佽瘯鐢ㄧ殑鐢ㄦ埛鍙繘鍏?a href="https://www.aliyun.com/daily-act/ecs/free?source=5176.11533457&userCode=mvsk1hl5" target="_blank">闃块噷浜戞湇鍔″櫒璇曠敤娲诲姩鐢宠璇曠敤銆?br/>
2023骞磄pu浜戞湇鍔″櫒璇曠敤鍥?png
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