This topic describes how Elastic Algorithm Service (EAS) of Machine Learning Platform for AI (PAI) is billed.
- You can deploy model services in shared resource groups and dedicated resource groups. Bills are generated based on the used resources of resource groups. For more information about the differences between the two types of resource groups, see Dedicated resource groups.
- If you deploy a model service in a shared resource group and a dedicated resource group, you are charged for using the resources of both resource groups.
Resource | Billable item | Billing method | Billing rule | Method to stop billing |
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Shared resource group | The amount of time for which a model service has been running. The value equals the amount of time for which the model services have occupied the shared resources. | Pay-as-you-go | Bills are generated based on the amount of time for which the model services have occupied shared resources. The billing starts immediately after model services are created. | Stop model services |
Dedicated resource group | The amount of time for which the resource groups have been running. | Pay-as-you-go | Only dedicated resource groups are billed. Model services deployed in dedicated resource groups are not charged. The billing starts immediately after pay-as-you-go dedicated resource groups are created. | Stop dedicated resource groups |
Subscription | N/A |
Billing rules for shared resource groups
Item | Default instance type | Specified instance type |
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Billing formula |
Note Usage duration is measured in minutes.
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Note Usage duration is measured in minutes.
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Unit price | For more information about the prices, see Prices of shared resource groups with the default instance type. | For more information about the prices, see Prices of shared resource groups with the specified instance type. |
Usage duration |
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Scaling |
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Notes |
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Prices of shared resource groups with the default instance type
Resource type | Unit price | Region |
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CPU | USD 0.03 per vCPU-hour |
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Memory | USD 0.004 per GB-hour |
Prices of shared resource groups with the specified instance type
Instance type | Instance family | Number of vCPUs | Memory (GiB) | Unit price (USD per hour) | Region |
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ecs.c5.6xlarge | c5, compute-optimized instance family | 24 | 48 | 1.08 |
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1.26 |
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1.2 |
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0.96 | China (Zhangjiakou) | ||||
1.14 | Germany (Frankfurt) | ||||
ecs.c6.2xlarge | c6, compute-optimized instance family | 8 | 16 | 0.36 |
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0.42 |
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0.24 |
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0.48 | China (Hong Kong) | ||||
0.18 | China (Zhangjiakou) | ||||
ecs.c6.4xlarge | c6, compute-optimized instance family | 16 | 32 | 0.72 |
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0.84 |
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0.54 |
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0.9 | China (Hong Kong) | ||||
0.36 | China (Zhangjiakou) | ||||
ecs.c6.6xlarge | c6, compute-optimized instance family | 24 | 48 | 1.08 |
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1.26 |
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0.78 |
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1.38 | China (Hong Kong) | ||||
0.54 | China (Zhangjiakou) | ||||
1.2 | Germany (Frankfurt) | ||||
ecs.c6.8xlarge | c6, compute-optimized instance family | 32 | 64 | 1.44 |
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1.68 |
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1.08 |
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1.8 | China (Hong Kong) | ||||
0.72 | China (Zhangjiakou) | ||||
1.62 | Germany (Frankfurt) | ||||
ecs.g5.6xlarge | g5, general-purpose instance family | 24 | 96 | 1.8 |
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1.38 |
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1.68 | China (Hong Kong) | ||||
1.32 | India (Mumbai) | ||||
1.74 | Singapore (Singapore) | ||||
1.62 | Indonesia (Jakarta) | ||||
1.56 | Germany (Frankfurt) | ||||
ecs.g6.2xlarge | g6, general-purpose instance family | 8 | 32 | 0.48 | India (Mumbai) |
0.54 |
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0.36 |
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0.6 | China (Hong Kong) | ||||
0.24 | China (Zhangjiakou) | ||||
0.42 |
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ecs.g6.4xlarge | g6, general-purpose instance family | 16 | 64 | 0.9 |
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1.08 |
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0.66 |
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1.2 | China (Hong Kong) | ||||
0.48 | China (Zhangjiakou) | ||||
ecs.g6.6xlarge | g6, general-purpose instance family | 24 | 96 | 1.38 | India (Mumbai) |
1.68 |
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1.02 |
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1.8 | China (Hong Kong) | ||||
0.72 | China (Zhangjiakou) | ||||
1.62 | Germany (Frankfurt) | ||||
1.32 |
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ecs.g6.8xlarge | g6, general-purpose instance family | 32 | 128 | 1.86 | India (Mumbai) |
2.22 |
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1.38 |
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2.4 | China (Hong Kong) | ||||
0.96 | China (Zhangjiakou) | ||||
1.8 |
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ecs.gn5-c28g1.7xlarge | gn5, GPU-accelerated compute-optimized instance family (NVIDIA P100 × 1) | 28 | 112 | 3.78 | India (Mumbai) |
3.72 |
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4.08 |
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3.54 | China (Hong Kong) | ||||
3.84 | Germany (Frankfurt) | ||||
3.48 |
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ecs.gn5-c4g1.xlarge | gn5, GPU-accelerated compute-optimized instance family (NVIDIA P100 × 1) | 4 | 30 | 2.04 |
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2.16 |
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1.98 | China (Zhangjiakou) | ||||
1.92 | Germany (Frankfurt) | ||||
1.86 | US (Virginia) | ||||
ecs.gn5-c8g1.2xlarge | gn5, GPU-accelerated compute-optimized instance family (NVIDIA P100 × 1) | 8 | 60 | 2.46 |
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2.58 |
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2.64 |
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2.34 | China (Zhangjiakou) | ||||
2.28 | Germany (Frankfurt) | ||||
2.22 | US (Virginia) | ||||
ecs.gn5-c8g1.4xlarge | gn5, GPU-accelerated compute-optimized instance family (NVIDIA P100 × 2) | 16 | 120 | 4.92 |
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5.16 |
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5.22 |
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4.74 | China (Zhangjiakou) | ||||
4.62 | Germany (Frankfurt) | ||||
4.44 | US (Virginia) | ||||
4.86 | US (Silicon Valley) | ||||
ecs.gn5i-c4g1.xlarge | gn5i, GPU-accelerated compute-optimized instance family (NVIDIA P4 × 1) | 4 | 16 | 1.68 |
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1.26 | China (Zhangjiakou) | ||||
ecs.gn5i-c8g1.2xlarge | gn5i, GPU-accelerated compute-optimized instance family (NVIDIA P4 × 1) | 8 | 32 | 1.98 |
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1.5 | China (Zhangjiakou) | ||||
ecs.gn6i-c16g1.4xlarge | gn6i, GPU-accelerated compute-optimized instance family (NVIDIA T4 × 1) | 16 | 62 | 2.28 |
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2.34 | Singapore (Singapore) | ||||
2.22 | Indonesia (Jakarta) | ||||
2.82 |
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2.1 | China (Hong Kong) | ||||
2.52 | China (Zhangjiakou) | ||||
1.98 | US (Virginia) | ||||
ecs.gn6i-c24g1.12xlarge | gn6i, GPU-accelerated compute-optimized instance family (NVIDIA T4 × 2) | 48 | 186 | 5.46 | India (Mumbai) |
5.94 | Singapore (Singapore) | ||||
5.52 | Indonesia (Jakarta) | ||||
5.88 |
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5.22 | China (Hong Kong) | ||||
5.28 | China (Zhangjiakou) | ||||
5.7 | Germany (Frankfurt) | ||||
5.04 | US (Virginia) | ||||
ecs.gn6i-c24g1.6xlarge | gn6i, GPU-accelerated compute-optimized instance family (NVIDIA T4 × 1) | 24 | 93 | 2.7 | India (Mumbai) |
2.76 | Indonesia (Jakarta) | ||||
2.94 |
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2.64 |
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2.88 | Germany (Frankfurt) | ||||
2.52 | US (Virginia) | ||||
ecs.gn6i-c4g1.xlarge | gn6i, GPU-accelerated compute-optimized instance family (NVIDIA T4 × 1) | 4 | 15 | 1.5 |
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1.44 | Indonesia (Jakarta) | ||||
1.98 |
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1.32 |
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1.8 | China (Zhangjiakou) | ||||
1.38 | Germany (Frankfurt) | ||||
ecs.gn6i-c8g1.2xlarge | gn6i, GPU-accelerated compute-optimized instance family (NVIDIA T4 × 1) | 8 | 31 | 1.74 | India (Mumbai) |
1.8 | Singapore (Singapore) | ||||
1.68 |
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2.4 |
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1.56 |
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2.16 | China (Zhangjiakou) | ||||
ecs.gn6v-c8g1.2xlarge | gn6v, GPU-accelerated compute-optimized instance family (NVIDIA V100 × 1) | 8 | 32 | 5.22 | Singapore (Singapore) |
4.5 |
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3.36 | China (Zhangjiakou) | ||||
3.12 | US (Virginia) | ||||
ecs.r6.2xlarge | r6, memory-optimized instance family | 8 | 64 | 0.6 |
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0.72 |
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0.48 |
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0.78 | China (Hong Kong) | ||||
0.3 | China (Zhangjiakou) | ||||
ecs.r6.4xlarge | r6, memory-optimized instance family | 16 | 128 | 1.2 | India (Mumbai) |
1.38 |
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0.9 |
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1.56 | China (Hong Kong) | ||||
0.6 | China (Zhangjiakou) | ||||
1.14 |
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ecs.r6.6xlarge | r6, memory-optimized instance family | 24 | 192 | 1.8 | India (Mumbai) |
1.38 |
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2.1 |
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2.34 | China (Hong Kong) | ||||
0.96 | China (Zhangjiakou) | ||||
1.74 |
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ecs.r6.8xlarge | r6, memory-optimized instance family | 32 | 256 | 2.4 | India (Mumbai) |
2.76 |
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1.8 |
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3.06 | China (Hong Kong) | ||||
1.26 | China (Zhangjiakou) | ||||
2.34 |
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ecs.g7.2xlarge | g7, general-purpose instance family | 8 | 32 | 0.54 |
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0.42 |
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ecs.g7.4xlarge | g7, general-purpose instance family | 16 | 64 | 1.02 |
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0.78 |
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1.14 | China (Hong Kong) | ||||
ecs.g7.6xlarge | g7, general-purpose instance family | 24 | 96 | 1.56 |
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1.2 |
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1.68 | China (Hong Kong) | ||||
ecs.g7.8xlarge | g7, general-purpose instance family | 32 | 128 | 2.04 |
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1.56 |
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2.28 | China (Hong Kong) | ||||
ecs.c7.2xlarge | c7, compute-optimized instance family | 8 | 16 | 0.42 |
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0.3 |
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0.48 | China (Hong Kong) | ||||
ecs.c7.4xlarge | c7, compute-optimized instance family | 16 | 32 | 0.84 |
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0.6 |
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0.9 | China (Hong Kong) | ||||
ecs.c7.6xlarge | c7, compute-optimized instance family | 24 | 48 | 1.26 |
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0.9 |
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1.38 | China (Hong Kong) | ||||
ecs.c7.8xlarge | c7, compute-optimized instance family | 32 | 64 | 1.68 |
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1.2 |
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1.86 | China (Hong Kong) | ||||
ecs.r7.2xlarge | r7, memory-optimized instance family | 8 | 64 | 0.66 | Singapore (Singapore) |
0.54 |
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0.72 | China (Hong Kong) | ||||
ecs.r7.4xlarge | r7, memory-optimized instance family | 16 | 128 | 1.32 | Singapore (Singapore) |
1.02 |
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1.44 | China (Hong Kong) | ||||
ecs.r7.6xlarge | r7, memory-optimized instance family | 24 | 192 | 1.98 | Singapore (Singapore) |
1.56 |
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2.16 | China (Hong Kong) | ||||
ecs.r7.8xlarge | r7, memory-optimized instance family | 32 | 256 | 2.58 | Singapore (Singapore) |
2.04 |
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2.88 | China (Hong Kong) | ||||
ecs.gn7-c12g1.3xlarge | gn7, GPU-accelerated compute-optimized instance family (NVIDIA A100 × 1) | 12 | 95 | 5.4 |
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ecs.g7.16xlarge | g7, general-purpose instance family | 64 | 256 | 4.08 |
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3.12 |
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4.5 | China (Hong Kong) | ||||
ecs.c7.16xlarge | c7, compute-optimized instance family | 64 | 128 | 3.36 |
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2.46 |
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3.66 | China (Hong Kong) | ||||
ecs.r7.16xlarge | r7, memory-optimized instance family | 64 | 512 | 5.22 | Singapore (Singapore) |
4.08 |
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5.7 | China (Hong Kong) | ||||
ecs.gn7i-c8g1.2xlarge | gn7i, GPU-accelerated compute-optimized instance family (NVIDIA A10 × 1) | 8 | 30 | 3.06 | Singapore (Singapore) |
2.16 |
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ecs.gn7i-c16g1.4xlarge | gn7i, GPU-accelerated compute-optimized instance family (NVIDIA A10 × 1) | 16 | 60 | 3.24 | Singapore (Singapore) |
2.28 |
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ecs.gn7i-c32g1.8xlarge | gn7i, GPU-accelerated compute-optimized instance family (NVIDIA A10 × 1) | 32 | 188 | 3.6 | Singapore (Singapore) |
2.52 |
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ecs.gn6e-c12g1.3xlarge | gn6e, GPU-accelerated compute-optimized instance family (NVIDIA V100 × 1) | 12 | 92 | 4.68 | Singapore (Singapore) |
3.36 |
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ecs.g6.xlarge | g6, general-purpose instance family | 4 | 16 | 0.24 |
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0.3 |
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0.18 |
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0.12 | China (Zhangjiakou) | ||||
ecs.c6.xlarge | c6, compute-optimized instance family | 4 | 8 | 0.18 |
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0.12 |
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0.24 | China (Hong Kong) | ||||
ecs.r6.xlarge | r6, memory-optimized instance family | 4 | 32 | 0.3 |
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0.36 |
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0.24 |
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0.18 | China (Zhangjiakou) | ||||
ecs.g6.large | g6, general-purpose instance family | 2 | 8 | 0.12 |
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0.06 |
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ecs.c6.large | c6, compute-optimized instance family | 2 | 4 | 0.12 |
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0.06 |
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ecs.r6.large | r6, memory-optimized instance family | 2 | 16 | 0.12 |
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0.18 |
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0.06 | China (Zhangjiakou) |
Billing examples for shared resource groups
- Scenario:
You used shared resource groups with the specified instance type in the China (Hangzhou) region to deploy a model service.
- The model service occupied 2 vCPUs and 8 GB of memory, and started to run at 09:00:00 (UTC+8) on June 3, 2019.
- You scaled in the model service and reduced the occupied resources to 1 vCPU and 4 GB of memory at 10:00:00 (UTC+8) on June 3, 2019.
- Then, you scaled out the model service and increased the occupied resources to 4 vCPUs and 16 GB of memory at 11:00:00 (UTC+8) on June 3, 2019.
- At 12:00:00 (UTC+8) on June 3, 2019, the model service stopped running.
- The bill amount is calculated based on the following formula:
Bill amount: 2 × 0.03 + 8 × 0.004 + 1 × 0.03 + 4 × 0.004 + 4 × 0.03 + 16 × 0.004 = USD 0.322
Billing rules for dedicated resource groups
Item | Subscription | Pay-as-you-go |
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Billing formula |
Note Subscription duration is measured in minutes.
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Note Subscription duration is measured in minutes.
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Unit price | For more information about the prices, see Prices of dedicated resource groups. | |
Subscription or usage duration | After you purchase a dedicated resource group, the resource group is free of charge
on the current day, and the subscription takes effect from the next day. For example,
you purchased a dedicated resource group on July 31, 2019, and the subscription duration
is one month. Then, the resource group expired at 00:00:00 (UTC+8) on August 31, 2019.
Note Valid subscription durations: one month, two months, three months, and six months.
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Scaling | N/A |
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Notes | Some resources may be unavailable in one or more regions for a short period of time. During the time period, you cannot purchase relevant resource groups in these regions. |
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Prices of dedicated resource groups
For more information about the pricing of the subscription dedicated resource groups, go to the Dedicated Node for EAS (Subscription) buy page.
For more information about the pricing of pay-as-you-go dedicated resource groups, go to the Dedicated Node for EAS (Pay-As-You-Go) buy page.
Billing examples for dedicated resource groups
- Subscription
- Scenario:
You subscribe to two subscription NVIDIA T4 GPUs in the China (Hangzhou) region for three months, and the specifications of each GPU are 4 vCPUs and 15 GB of memory. The unit price of the subscribed GPUs is USD 570 per month.
- The bill amount is calculated based on the following formula:
Bill amount: 2 × 570 × 3 = USD 3,420
- Scenario:
- Pay-as-you-go
- Scenario:
You purchase two pay-as-you-go Elastic Compute Service (ECS) instances whose instance type is ecs.g6.6xlarge in the China (Hangzhou) region, and use the instances for 45 minutes. The specifications of each ECS instance are 24 vCPUs and 96 GB of memory. The unit price of the ECS instance of the ecs.g6.6xlarge type is USD 2.94 per hour.
- The bill amount is calculated based on the following formula:
Bill amount: 2 × (2.94/60) × 45 = USD 4.41
- Scenario: