Pricing

Google Cloud Machine Learning offers scalable, flexible pricing options to help fit your project and budget. Cloud ML charges for training models and getting predictions, but managing your machine learning resources in the cloud is free of charge.

The following table summarizes Cloud ML pricing. All use is also subject to the Cloud ML quota policy.

Action US Cost Europe/Asia Cost Notes
Model training $0.49 per hour, per ML training unit $0.54 per hour, per ML training unit See Training pricing.
Batch prediction $0.10 per thousand predictions, plus $0.40 per hour $0.11 per thousand predictions, plus $0.44 per hour See Prediction pricing.

Free operations

The resource management operations provided by Cloud ML are available free of charge. The Cloud ML 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 create, get, list, cancel, delete

Training pricing

Pricing for training your models in the cloud is defined in terms of ML training units, which are an abstract measurement of the processing power involved. 1 ML training unit represents a standard machine configuration used by the training service. The number of ML training units you will be charged per hour of processing is determined by the processing configuration you choose when you start your training job.

You are charged for training in one-minute increments, based on the hourly rate. Costs are computed per training job, and there is a minimum charge of ten minutes per job.

Region Training Cost
US

$0.49 per hour, per ML training unit.

Processing is charged per minute separately for each training job, with a minimum charge of ten minutes.

Europe and Asia

$0.54 per hour, per ML training unit.

Processing is charged per minute separately for each training job, with a minimum charge of ten minutes.

ML training units by scale tier

You can control the type of processing cluster to use when training your job. The simplest way is to choose from one of the predefined configurations called scale tiers. Each scale tier has a cost in ML training units:

Scale Tier ML training units
BASIC 1
STANDARD_1 10
PREMIUM_1 75
CUSTOM Varies by configuration, see the machine type table.

Machine types for custom cluster configurations

If you select CUSTOM as your scale tier, you have control over the number and type of virtual machines to use as the master, your workers and your parameter servers. Each machine in a custom configuration has its own cost in ML training units per hour:

Machine type Cost per instance
standard 1 ML training unit
large_model 3 ML training units
complex_model_s 2 ML training units
complex_model_m 3 ML training units
complex_model_l 6 ML training units

Training cost examples

Finding your training cost requires some calculation:

(ML training units * cost per unit / 60) * job duration in minutes

As illustrated in the following examples:

  • A data scientist in the US region runs a training job and selects the STANDARD_1 scale tier. Her job takes 15 minutes:

    (10 ML training units * $0.49 per hour / 60) * 15 minutes
    

    For a total of $1.23 for the job.

  • A computer science professor in the US region runs a training job using the CUSTOM scale tier. She has a very large model, so she wants to take advantage of the large model VMs for her parameter servers. She configures her processing cluster like this:

    • A complex_model_s machine for her master (2 ML training units).
    • 5 parameter servers on large_model VMs (5 @ 3 = 15 ML training units).
    • 8 workers on complex_model_s VMs (8 @ 2 = 16 ML training units).

    Her job runs for 2 hours and 26 minutes:

    (33 ML training units * $0.49 per hour / 60) * 146 minutes
    

    For a total of $39.35 for the job.

Prediction pricing

Prediction pricing applies to requests made to trained model versions hosted by Cloud ML. You are charged a flat rate per prediction served each month. You are also charged for the time used on each node in the processing cluster that performs the predictions. For batch prediction, Cloud ML will use a number of nodes that you specify when you create the job.

Batch prediction pricing

You are charged for batch predictions served by your models according to the following table:

Region Standard rate High volume rate Notes
US

$0.10 per 1000 predictions

Plus $0.40 per node hour

$0.05 per 1000 predictions

Plus $0.40 per node hour

Predictions are accumulated per month and the cost is rounded to the nearest penny.

Processing is charged per minute separately for each training job, with a minimum charge of ten minutes.

High volume pricing applies to requests after the 100 millionth in a calendar month.

Europe and Asia

$0.11 per 1000 predictions

Plus $0.44 per node hour

$0.05 per 1000 predictions

Plus $0.44 per node hour

Online prediction pricing

The online prediction service is an alpha feature even though the rest of Cloud ML is in beta. While online prediction remains in alpha you can use it free of charge.

Prediction cost examples

Finding your prediction cost for a month requires some calculation:

(Number of predictions / 1000) * cost per 1K + (hours of processing * cost per hour)

As illustrated in the following example:

  • A real-estate company in the US runs a weekly prediction of housing values in areas they serve. In one month they run predictions for four weeks in batches of 3920, 4277, 3849, and 3961. Predictions take an average of 0.72 node seconds of processing to infer.

    The cost per prediction is cumulative:

    3920 + 4277 + 3849 + 3961 = 16007
    

    They are charged for 16007: (16007 / 1000) * $0.10 = $1.60

    The cost for processing is per job (this example uses the average, but real costs use exact values for each job):

    3920 * 0.72 = 47.04 minutes
    4277 * 0.72 = 51.324 minutes
    3849 * 0.72 = 46.188 minutes
    3961 * 0.72 = 47.532 minutes
    

    Each job is greater than ten minutes, and so is charged per minute of processing:

    (48 * $0.40) / 60 = $0.32
    (52 * $0.40) / 60 = $0.35
    (47 * $0.40) / 60 = $0.31
    (48 * $0.40) / 60 = $0.32
    

    For a total hourly charge of $1.30 and a total charge for the month of $2.90.

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