Pricing

AI Platform offers scalable, flexible pricing options to fit your project and budget.

AI Platform charges you for training your models and getting predictions. There is no charge for using AI Platform Vizier, AI Platform Notebooks, AI Platform Deep Learning Containers, AI Platform Deep Learning VM Image, or AI Platform Pipelines. However, you do pay for any Google Cloud resources you use with these products.

Prices for the AI Platform Data Labeling Service are computed based on the type of labeling task, the number of human labelers, and the number of annotation units generated.

Training

The tables below provide the price per hour of various training configurations, as well as the number of training units used by each configuration. Training units measure the resource usage of your job; the price per hour of a machine configuration is the number of training units it uses multiplied by the region's cost of training.

You can choose a predefined scale tier or a custom configuration of selected machine types. If you choose a custom configuration, sum the costs of the virtual machines you use.

Accelerator-enabled legacy machine types include the cost of the accelerators in their pricing. If you use Compute Engine machine types and attach accelerators, the cost of the accelerators is separate. To calculate this cost, multiply the prices in the table of accelerators below by how many of each type of accelerator you use.

The following tables summarize the pricing in each region where custom training is available. For additional details and example billing calculations, see the Pricing page for AI Platform Training.

Americas

The cost of a training job in all available Americas regions is $0.49 per hour, per training unit.

Predefined scale tiers - price per hour (training units)
`BASIC`	$0.1900 (0.3878)
`STANDARD_1`	$1.9880 (4.0571)
`PREMIUM_1`	$16.5536 (33.7829)
`BASIC_GPU`	$0.8300 (1.6939)
`BASIC_TPU`	$4.6900 (9.5714)
`CUSTOM`	If you select CUSTOM as your scale tier, you have control over the number and type of virtual machines used for your training job. See the table of machine types.

Machine types - price per hour (training units)
`n1-standard-4`	$0.1900 (0.3878)
`n1-standard-8`	$0.3800 (0.7755)
`n1-standard-16`	$0.7600 (1.5510)
`n1-standard-32`	$1.5200 (3.1020)
`n1-standard-64`	$3.0400 (6.2041)
`n1-standard-96`	$4.5600 (9.3061)
`n1-highmem-2`	$0.1184 (0.2416)
`n1-highmem-4`	$0.2368 (0.4833)
`n1-highmem-8`	$0.4736 (0.9665)
`n1-highmem-16`	$0.9472 (1.9331)
`n1-highmem-32`	$1.8944 (3.8661)
`n1-highmem-64`	$3.7888 (7.7322)
`n1-highmem-96`	$5.6832 (11.5984)
`n1-highcpu-16`	$0.5672 (1.1576)
`n1-highcpu-32`	$1.1344 (2.3151)
`n1-highcpu-64`	$2.2688 (4.6302)
`n1-highcpu-96`	$3.4020 (6.9429)
`cloud_tpu`⁶	$4.5000 (9.1840) or N/A if accelerators are attached explicitly⁶
`standard`	$0.1900 (0.3878)
`large_model`	$0.4736 (0.9665)
`complex_model_s`	$0.2836 (0.5788)
`complex_model_m`	$0.5672 (1.1576)
`complex_model_l`	$1.1344 (2.3151)
`standard_gpu`	$0.8300 (1.6939)
`complex_model_m_gpu`	$2.5600 (5.2245)
`complex_model_l_gpu`	$3.3200 (6.7755)
`standard_p100`	$1.8400 (3.7551)
`complex_model_m_p100`	$6.6000 (13.4694)
`standard_v100`	$2.8600 (5.8367)
`large_model_v100`	$2.9536 (6.0278)
`complex_model_m_v100`	$10.6800 (21.7959)
`complex_model_l_v100`	$21.3600 (43.5918)

Accelerators - price per hour (training units)
`NVIDIA_TESLA_K80`	$0.4500 (0.9184)
`NVIDIA_TESLA_P4`	$0.6000 (1.2245)
`NVIDIA_TESLA_P100`	$1.4600 (2.9796)
`NVIDIA_TESLA_T4`	$0.3500 (0.7143)
`NVIDIA_TESLA_V100`	$2.4800 (5.0612)
Eight `TPU_V2` cores⁶	$4.5000 (9.1840)
Eight `TPU_V3` cores⁶ (Beta)	$8.0000 (16.3264)

Europe

The cost of a training job in all available Europe regions is $0.54 per hour, per training unit.

Predefined scale tiers - price per hour (training units)
`BASIC`	$0.2200 (0.4074)
`STANDARD_1`	$2.3020 (4.2630)
`PREMIUM_1`	$19.1640 (35.4889)
`BASIC_GPU`	$0.9300 (1.7222)
`BASIC_TPU`	$5.4400 (10.0741)
`CUSTOM`	If you select CUSTOM as your scale tier, you have control over the number and type of virtual machines used for your training job. See the table of machine types.

Machine types - price per hour (training units)
`n1-standard-4`	$0.2200 (0.4074)
`n1-standard-8`	$0.4400 (0.8148)
`n1-standard-16`	$0.8800 (1.6296)
`n1-standard-32`	$1.7600 (3.2593)
`n1-standard-64`	$3.5200 (6.5185)
`n1-standard-96`	$5.2800 (9.7778)
`n1-highmem-2`	$0.1370 (0.2537)
`n1-highmem-4`	$0.2740 (0.5074)
`n1-highmem-8`	$0.5480 (1.0148)
`n1-highmem-16`	$1.0960 (2.0296)
`n1-highmem-32`	$2.1920 (4.0593)
`n1-highmem-64`	$4.3840 (8.1185)
`n1-highmem-96`	$6.5760 (12.1778)
`n1-highcpu-16`	$0.6568 (1.2163)
`n1-highcpu-32`	$1.3136 (2.4326)
`n1-highcpu-64`	$2.6272 (4.8652)
`n1-highcpu-96`	$3.9408 (7.2978)
`cloud_tpu`⁶	$5.2200 (9.6667) or N/A if accelerators are attached explicitly⁶
`standard`	$0.2200 (0.4074)
`large_model`	$0.5480 (1.0148)
`complex_model_s`	$0.3284 (0.6081)
`complex_model_m`	$0.6568 (1.2163)
`complex_model_l`	$1.3136 (2.4326)
`standard_gpu`	$0.9300 (1.7222)
`complex_model_m_gpu`	$2.8400 (5.2593)
`complex_model_l_gpu`	$3.7200 (6.8889)
`standard_p100`	$2.0400 (3.7778)
`complex_model_m_p100`	$7.2800 (13.4815)
`standard_v100`	$2.9684 (5.4970)
`large_model_v100`	$3.0708 (5.6867)
`complex_model_m_v100`	$11.0368 (20.4385)
`complex_model_l_v100`	$22.0736 (40.8770)

Accelerators - price per hour (training units)
`NVIDIA_TESLA_K80`	$0.4900 (0.9074)
`NVIDIA_TESLA_P4`	$0.6500 (1.2037)
`NVIDIA_TESLA_P100`	$1.6000 (2.9630)
`NVIDIA_TESLA_T4`	$0.3800 (0.7037)
`NVIDIA_TESLA_V100`	$2.5500 (4.7222)
Eight `TPU_V2` cores⁶	$5.2200 (9.6664)
Eight `TPU_V3` cores⁶ (Beta)	$8.8000 (16.2960)

Asia Pacific

The cost of a training job in all available Asia Pacific regions is $0.54 per hour, per training unit.

Predefined scale tiers - price per hour (training units)
`BASIC`	$0.2200 (0.4074)
`STANDARD_1`	$2.3020 (4.2630)
`PREMIUM_1`	$19.1640 (35.4889)
`BASIC_GPU`	$0.9300 (1.7222)
`BASIC_TPU`	(Not available)
`CUSTOM`	If you select CUSTOM as your scale tier, you have control over the number and type of virtual machines used for your training job. See the table of machine types.

Machine types - price per hour (training units)
`n1-standard-4`	$0.2200 (0.4074)
`n1-standard-8`	$0.4400 (0.8148)
`n1-standard-16`	$0.8800 (1.6296)
`n1-standard-32`	$1.7600 (3.2593)
`n1-standard-64`	$3.5200 (6.5185)
`n1-standard-96`	$5.2800 (9.7778)
`n1-highmem-2`	$0.1370 (0.2537)
`n1-highmem-4`	$0.2740 (0.5074)
`n1-highmem-8`	$0.5480 (1.0148)
`n1-highmem-16`	$1.0960 (2.0296)
`n1-highmem-32`	$2.1920 (4.0593)
`n1-highmem-64`	$4.3840 (8.1185)
`n1-highmem-96`	$6.5760 (12.1778)
`n1-highcpu-16`	$0.6568 (1.2163)
`n1-highcpu-32`	$1.3136 (2.4326)
`n1-highcpu-64`	$2.6272 (4.8652)
`n1-highcpu-96`	$3.9408 (7.2978)
`cloud_tpu`⁶	(Not available)
`standard`	$0.2200 (0.4074)
`large_model`	$0.5480 (1.0148)
`complex_model_s`	$0.3284 (0.6081)
`complex_model_m`	$0.6568 (1.2163)
`complex_model_l`	$1.3136 (2.4326)
`standard_gpu`	$0.9300 (1.7222)
`complex_model_m_gpu`	$2.8400 (5.2593)
`complex_model_l_gpu`	$3.7200 (6.8889)
`standard_p100`	$2.0400 (3.7778)
`complex_model_m_p100`	$7.2800 (13.4815)
`standard_v100`	$2.9684 (5.4970)
`large_model_v100`	$3.0708 (5.6867)
`complex_model_m_v100`	$11.0368 (20.4385)
`complex_model_l_v100`	$22.0736 (40.8770)

Accelerators - price per hour (training units)
`NVIDIA_TESLA_K80`	$0.4900 (0.9074)
`NVIDIA_TESLA_P4`	$0.6500 (1.2037)
`NVIDIA_TESLA_P100`	$1.6000 (2.9630)
`NVIDIA_TESLA_T4`	$0.3900 (0.7222)
`NVIDIA_TESLA_V100`	$2.5500 (4.7222)
Eight `TPU_V2` cores⁶	(Not available)
Eight `TPU_V3` cores⁶ (Beta)	(Not available)

Notes:

All use is subject to the AI Platform quota policy.

You are required to store your data and program files in Google Cloud Storage buckets during the AI Platform lifecycle. See more about Cloud Storage usage.

The cloud_tpu machine type currently provides a TPU v2 device with 8 cores by default, even if you don't explicitly attach any accelerators to your configuration. In this case, you pay the price listed for cloud_tpu in the machine types table.

If you do explicitly attach TPU v2 or TPU v3 accelerators to a cloud_tpu machine type in your configuration, you do not pay for the cloud_tpu machine type itself. Instead, you pay for the TPU_V2 or TPU_V3 accelerator attachments.

You are charged for training your models:

In one-minute increments.
At a price per hour as shown in the above table, where the price per hour is calculated from a base price and a number of training units, determined by the processing configuration you choose when you start your training job.
With a minimum of 10 minutes per training job.
From the moment when resources are provisioned for a job until the job finishes.

Prediction

This table provides the prices of batch prediction and online prediction per node hour. A node hour represents the time a virtual machine spends running your prediction job or waiting in a ready state to handle prediction requests.

The following tables summarize the pricing in each region where custom training is available. For additional details and example billing calculations, see the Pricing page for AI Platform Prediction.

Americas

Prediction

Batch prediction $0.0791205 per node hour

Online prediction

Machine types - price per node hour

mls1-c1-m2 (default)

$0.045147

mls1-c4-m2 (Beta)

$0.151962

n1-standard-2

Approximations:

`us-east4`	$0.107
`northamerica-northeast1`	$0.1046
Other Americas regions	$0.095

n1-standard-4

Approximations:

`us-east4`	$0.214
`northamerica-northeast1`	$0.2092
Other Americas regions	$0.1901

n1-standard-8

Approximations:

`us-east4`	$0.428
`northamerica-northeast1`	$0.4183
Other Americas regions	$0.3802

n1-standard-16

Approximations:

`us-east4`	$0.8559
`northamerica-northeast1`	$0.8367
Other Americas regions	$0.7603

n1-standard-32

Approximations:

`us-east4`	$1.7119
`northamerica-northeast1`	$1.6733
Other Americas regions	$1.5207

n1-highmem-2

Approximations:

`us-east4`	$0.1332
`northamerica-northeast1`	$0.1302
Other Americas regions	$0.1184

n1-highmem-4

Approximations:

`us-east4`	$0.2665
`northamerica-northeast1`	$0.2605
Other Americas regions	$0.2367

n1-highmem-8

Approximations:

`us-east4`	$0.5329
`northamerica-northeast1`	$0.5209
Other Americas regions	$0.4735

n1-highmem-16

Approximations:

`us-east4`	$1.0659
`northamerica-northeast1`	$1.0419
Other Americas regions	$0.947

n1-highmem-32

Approximations:

`us-east4`	$2.1317
`northamerica-northeast1`	$2.0838
Other Americas regions	$1.894

n1-highcpu-2

Approximations:

`us-east4`	$0.0798
`northamerica-northeast1`	$0.078
Other Americas regions	$0.0709

n1-highcpu-4

Approximations:

`us-east4`	$0.1596
`northamerica-northeast1`	$0.156
Other Americas regions	$0.1417

n1-highcpu-8

Approximations:

`us-east4`	$0.3192
`northamerica-northeast1`	$0.312
Other Americas regions	$0.2834

n1-highcpu-16

Approximations:

`us-east4`	$0.6384
`northamerica-northeast1`	$0.624
Other Americas regions	$0.5669

n1-highcpu-32

Approximations:

`us-east4`	$1.2768
`northamerica-northeast1`	$1.248
Other Americas regions	$1.1338

Europe

Prediction

Batch prediction $0.086118 per node hour

Online prediction

Machine types - price per node hour

mls1-c1-m2 (default)

$0.044095

mls1-c4-m2 (Beta)

$0.148414

n1-standard-2

Approximations:

`europe-west2`	$0.1224
`europe-west3`	$0.1224
Other Europe regions	$0.11

n1-standard-4

Approximations:

`europe-west2`	$0.2448
`europe-west3`	$0.2448
Other Europe regions	$0.2201

n1-standard-8

Approximations:

`europe-west2`	$0.4896
`europe-west3`	$0.4896
Other Europe regions	$0.4401

n1-standard-16

Approximations:

`europe-west2`	$0.9792
`europe-west3`	$0.9792
Other Europe regions	$0.8802

n1-standard-32

Approximations:

`europe-west2`	$1.9583
`europe-west3`	$1.9583
Other Europe regions	$1.7605

n1-highmem-2

Approximations:

`europe-west2`	$0.1524
`europe-west3`	$0.1524
Other Europe regions	$0.137

n1-highmem-4

Approximations:

`europe-west2`	$0.3048
`europe-west3`	$0.3048
Other Europe regions	$0.274

n1-highmem-8

Approximations:

`europe-west2`	$0.6097
`europe-west3`	$0.6097
Other Europe regions	$0.548

n1-highmem-16

Approximations:

`europe-west2`	$1.2193
`europe-west3`	$1.2193
Other Europe regions	$1.0959

n1-highmem-32

Approximations:

`europe-west2`	$2.4386
`europe-west3`	$2.4386
Other Europe regions	$2.1918

n1-highcpu-2

Approximations:

`europe-west2`	$0.0913
`europe-west3`	$0.0913
Other Europe regions	$0.0821

n1-highcpu-4

Approximations:

`europe-west2`	$0.1826
`europe-west3`	$0.1826
Other Europe regions	$0.1642

n1-highcpu-8

Approximations:

`europe-west2`	$0.3651
`europe-west3`	$0.3651
Other Europe regions	$0.3284

n1-highcpu-16

Approximations:

`europe-west2`	$0.7303
`europe-west3`	$0.7303
Other Europe regions	$0.6567

n1-highcpu-32

Approximations:

`europe-west2`	$1.4606
`europe-west3`	$1.4606
Other Europe regions	$1.3134

Asia Pacific

Prediction

Batch prediction $0.086118 per node hour

Online prediction

Machine types - price per node hour

mls1-c1-m2 (default)

$0.051456

mls1-c4-m2 (Beta)

$0.17331

n1-standard-2

Approximations:

`asia-east1`	$0.11
`asia-northeast1`	$0.1219
`asia-southeast1`	$0.1172
`australia-southeast1`	$0.1348

n1-standard-4

Approximations:

`asia-east1`	$0.2201
`asia-northeast1`	$0.2438
`asia-southeast1`	$0.2344
`australia-southeast1`	$0.2696

n1-standard-8

Approximations:

`asia-east1`	$0.4401
`asia-northeast1`	$0.4875
`asia-southeast1`	$0.4688
`australia-southeast1`	$0.5392

n1-standard-16

Approximations:

`asia-east1`	$0.8802
`asia-northeast1`	$0.975
`asia-southeast1`	$0.9375
`australia-southeast1`	$1.0784

n1-standard-32

Approximations:

`asia-east1`	$1.7605
`asia-northeast1`	$1.9501
`asia-southeast1`	$1.8751
`australia-southeast1`	$2.1567

n1-highmem-2

Approximations:

`asia-east1`	$0.137
`asia-northeast1`	$0.1517
`asia-southeast1`	$0.1459
`australia-southeast1`	$0.1679

n1-highmem-4

Approximations:

`asia-east1`	$0.274
`asia-northeast1`	$0.3034
`asia-southeast1`	$0.2919
`australia-southeast1`	$0.3357

n1-highmem-8

Approximations:

`asia-east1`	$0.548
`asia-northeast1`	$0.6067
`asia-southeast1`	$0.5837
`australia-southeast1`	$0.6714

n1-highmem-16

Approximations:

`asia-east1`	$1.0959
`asia-northeast1`	$1.2135
`asia-southeast1`	$1.1675
`australia-southeast1`	$1.3428

n1-highmem-32

Approximations:

`asia-east1`	$2.1918
`asia-northeast1`	$2.4269
`asia-southeast1`	$2.335
`australia-southeast1`	$2.6857

n1-highcpu-2

Approximations:

`asia-east1`	$0.0821
`asia-northeast1`	$0.091
`asia-southeast1`	$0.0874
`australia-southeast1`	$0.1005

n1-highcpu-4

Approximations:

`asia-east1`	$0.1642
`asia-northeast1`	$0.182
`asia-southeast1`	$0.1748
`australia-southeast1`	$0.2011

n1-highcpu-8

Approximations:

`asia-east1`	$0.3284
`asia-northeast1`	$0.364
`asia-southeast1`	$0.3496
`australia-southeast1`	$0.4021

n1-highcpu-16

Approximations:

`asia-east1`	$0.6567
`asia-northeast1`	$0.7279
`asia-southeast1`	$0.6992
`australia-southeast1`	$0.8043

n1-highcpu-32

Approximations:

`asia-east1`	$1.3134
`asia-northeast1`	$1.4558
`asia-southeast1`	$1.3985
`australia-southeast1`	$1.6085

Compute Engine (N1) machine types for online prediction are only available in the us-central1, europe-west4, and asia-east1 regions, and their pricing is charged as two separate SKUs on your Google Cloud bill:

vCPU cost, measured in vCPU hours
RAM cost, measured in GB hours

The prices for Compute Engine (N1) machine types in the previous table approximate the total hourly cost for each prediction node of a model version using that machine type. For example, since an n1-highcpu-32 machine type includes 32 vCPUs and 28.8 GB of RAM, the hourly pricing per node is equal to 32 vCPU hours + 28.8 GB hours.

The prices in the previous table are provided to help you estimate online prediction costs. The following table shows the vCPU and RAM pricing for Compute Engine (N1) machine types, which more precisely reflect the SKUs that you will be charged for:

Americas

Compute Engine (N1) machine type SKUs

vCPU

N. Virginia (`us-east4`)	$0.035605 per vCPU hour
Montreal (`northamerica-northeast1`)	$0.034802 per vCPU hour
Other Americas regions	$0.031613 per vCPU hour

RAM

N. Virginia (`us-east4`)	$0.004771 per GB hour
Montreal (`northamerica-northeast1`)	$0.004664 per GB hour
Other Americas regions	$0.004242 per GB hour

Europe

Compute Engine (N1) machine type SKUs

vCPU

London (`europe-west2`)	$0.04073 per vCPU hour
Frankfurt (`europe-west3`)	$0.04073 per vCPU hour
Other Europe regions	$0.036632 per vCPU hour

RAM

London (`europe-west2`)	$0.005458 per GB hour
Frankfurt (`europe-west3`)	$0.005458 per GB hour
Other Europe regions	$0.004902 per GB hour

Asia Pacific

Compute Engine (N1) machine type SKUs

vCPU

Taiwan (`asia-east1`)	$0.036632 per vCPU hour
Tokyo (`asia-northeast1`)	$0.040618 per vCPU hour
Singapore (`asia-southeast1`)	$0.038999 per vCPU hour
Sydney (`australia-southeast1`)	$0.044856 per vCPU hour

RAM

Taiwan (`asia-east1`)	$0.004902 per GB hour
Tokyo (`asia-northeast1`)	$0.005419 per GB hour
Singapore (`asia-southeast1`)	$0.005226 per GB hour
Sydney (`australia-southeast1`)	$0.006011 per GB hour

You can optionally use GPU accelerators for online prediction with Compute Engine (N1) machine types. GPUs incur an additional charge, separate from those described in the previous table. The following table describes the pricing for each type of GPU:

Americas

Accelerators - price per hour

NVIDIA_TESLA_K80 $0.4500

NVIDIA_TESLA_P4

Iowa (`us-central1`)	$0.6000
N. Virginia (`us-east4`)	$0.6000
Montréal (`northamerica-northeast1`)	$0.6500

NVIDIA_TESLA_P100 $1.4600

NVIDIA_TESLA_T4 $0.3500

NVIDIA_TESLA_V100 $2.4800

Europe

Accelerators - price per hour

NVIDIA_TESLA_K80 $0.4900

NVIDIA_TESLA_P4 $0.6500

NVIDIA_TESLA_P100 $1.6000

NVIDIA_TESLA_T4

London (`europe-west2`)	$0.4100
Netherlands (`europe-west4`)	$0.3800

NVIDIA_TESLA_V100 $2.5500

Asia Pacific

Accelerators - price per hour

NVIDIA_TESLA_K80 $0.4900

NVIDIA_TESLA_P4

Singapore (`asia-southeast1`)	$0.6500
Sydney (`australia-southeast1`)	$0.6500

NVIDIA_TESLA_P100 $1.6000

NVIDIA_TESLA_T4

Tokyo (`asia-northeast1`)	$0.3700
Singapore (`asia-southeast1`)	$0.3700

NVIDIA_TESLA_V100 Not available

Note that the pricing is per GPU, so if you use multiple GPUs per prediction node (or if your version scales to use multiple nodes), then costs scale accordingly.

AI Platform Prediction serves predictions from your model by running a number of virtual machines ("nodes"). By default, AI Platform automatically scales the number of nodes running at any time. For online prediction, the number of nodes scales to meet demand. Each node can respond to multiple prediction requests. For batch prediction, the number of nodes scales to reduce the total time it takes to run a job. You can customize how prediction nodes scale.

You are charged for the time that each node runs for your model, including:

When the node is processing a batch prediction job.
When the node is processing an online prediction request.
When the node is in a ready state for serving online predictions.

The cost of one node running for one hour is a node hour. The table of prediction prices describes the price of a node hour, which varies across regions and between online prediction and batch prediction.

You can consume node hours in fractional increments. For example, one node running for 30 minutes costs 0.5 node hours.

Vizier, Notebooks, Deep Learning Containers, Deep Learning VM Image, and Pipelines

There is no charge for using AI Platform Vizier, AI Platform Notebooks, AI Platform Deep Learning Containers, AI Platform Deep Learning VM Image, or AI Platform Pipelines. However, you do pay for any Google Cloud resources you use with these products.

For example, when you use AI Platform Notebooks, you pay for the Google Cloud resources you use with your notebook instances, such as Compute Engine:

Compute Engine resources: You incur costs from the time that you create an Notebooks instance until you delete the instance. The default machine type is n1-standard-4, but you can choose a different machine type. You are also charged for a 100 GB Standard Persistent Disk, which is used as a boot disk (see Storage resources). The boot disk is deleted when the VM instance is deleted.
Data Analysis Services: You incur BigQuery costs when you issue SQL queries within a Notebook (see BigQuery Pricing).
Customer-managed encryption keys: You incur costs when you use customer-managed encryption keys. Each time your Notebooks instance uses a Cloud Key Management Service key, that operation is billed at the rate of Cloud KMS key operations (see Cloud KMS pricing).

Data labeling

AI Platform enables you to request human labeling for a collection of data that you plan to use to train a custom machine learning model. Prices for the service are computed based on:

The number of human labelers for each data item. This is specified by the HumanAnnotationConfig replica_count field in the API and the labelers per data item field when creating a new data labeling request in the UI.
The number of annotation units generated. The price for the unit of each labeling task is described in the table below.
- For an image classification task, units are determined the number of images and the number of human labelers. For example, an image with 3 human labelers counts for 1 * 3 = 3 units. The price for single-label and multi-label classification are the same.
- For an image bounding box task, units are determined by the number of bounding boxes identified in the images and the number of human labelers. For example, if an image with 2 bounding boxes and 3 human labelers counts for 2 * 3 = 6 units. Images without bounding boxes will not be charged.
- For an image segmentation/rotated box/polyline/polygon task, units are determined in the same way as a image bounding box task.
- For a video classification task, units are determined by the video length (every 5 seconds is a price unit) and the number of human labelers. For example, a 25 seconds video with 3 human labelers counts for 25 / 5 * 3 = 15 units. The price for single-label and multi-label classification are the same.
- For a video object detection task, unit are determined by the number of objects identified in the video and the number of human labelers. For example, for a video with 2 objects and 3 human labelers, it counts for 2 * 3 = 6 units. Video without objects will not be charged.
- For a video object tracking task, units are determined by the video length (every 30 seconds is a price unit), the number of human labelers, and the number of objects identified. For a 120 seconds video with 3 human labelers and 2 objects identified, it counts for 120 / 4 * 2 * 3 = 18 units.
- For a video event task, units are determined in the same way as a video object tracking task.
- For a text classification task, units are determined by text length (every 50 words is a price unit) and the number of human labelers. For example, one piece of text with 100 words and 3 human labelers counts for 100 / 50 * 3 = 6 units. The price for single-label and multi-label classification is the same.
- For a text sentiment task, units are determined in the same way as a text classification task.
- For a text entity extraction task, units are determined by text length (every 50 words is a price unit), the number of entities identified, and the number of human labelers. For example, a piece of text with 100 words, 2 entities identified, and 3 human labelers counts for 100 / 50 * 2 * 3 = 12 units. Text without entities will not be charged.
For image/video/text classification and text sentiment tasks, human labelers may lose track of classes if the label set size is too large. As a result, we send at most 20 classes to the human labelers at a time. For example, if the label set size of a labeling task is 40, each data item will be sent for human review 40 / 20 = 2 times, and we will charge 2 times of the price (calculated above) accordingly.

The table below provides the price per 1,000 units per human labeler, based on the unit listed for each objective. Tier 1 pricing applies to the first 50,000 units per month in each Google Cloud project; Tier 2 pricing applies to the next 950,000 units per month in the project, up to 1,000,000 units. Contact us for pricing above 1,000,000 units per month.

Data type	Objective	Unit	Tier 1	Tier 2
Image	Classification	Image	$35	$25
	Bounding box	Bounding box	$63	$49
	Segmentation	Segment	$870	$850
	Rotated box	Bounding box	$86	$60
	Polygon/polyline	Polygon/Polyline	$257	$180
Video	Classification	5sec video	$86	$60
	Object detection	Bounding box	$86	$60
	Object tracking	Object in 30sec video	$686	$480
	Event	Event in 30sec video	$214	$150
Text	Classification	50 words	$129	$90
	Sentiment	50 words	$200	$140
	Entity extraction	Entity	$86	$60

Required use of Cloud Storage

In addition to the costs described in this document, you are required to store data and program files in Cloud Storage buckets during the AI Platform lifecycle. This storage is subject to the Cloud Storage pricing policy.

Required use of Cloud Storage includes:

Staging your training application package for custom-trained models.
Storing your training input data.
Storing the output of your training jobs. AI Platform does not require long-term storage of these items. You can remove the files as soon as the operation is complete.
Staging your model files when you are ready to deploy a model version.
Storing your input data for batch prediction.
Storing the output of your batch prediction jobs. AI Platform does not require long-term storage of these items. You can remove the files as soon as the operation is complete.

Free operations for managing your resources

The resource management operations provided by AI Platform are available free of charge. The AI Platform quota policy does limit some of these operations.

Resource	Free operations
models	create, get, list, delete
versions	create, get, list, delete, setDefault
jobs	get, list, cancel
operations	get, list, cancel, delete

Google Cloud Platform costs

Since you store images to be analyzed in Google Cloud Storage, and may use other Google Cloud Platform resources in tandem with the AI Platform, such as Google AI Platform, containers and database instances, then you will also be billed for the use of those services. See the Google Cloud Platform Pricing Calculator to determine other costs based on current rates.

To view your current billing status in the Cloud Console, including usage and your current bill, see the Billing page. For more details about managing your account, see the Cloud Billing Documentation or Billing and Payments Support.