Watson Studio, Watson Knowledge Catalog, and Watson Machine Learning offering plans

The plan you choose for Watson Studio, Watson Knowledge Catalog, or Watson Machine Learning affects the features and capabilities that you can use. See the plan pages in IBM Cloud for pricing information.

Watson Studio plans

Watson Studio has Lite, Standard, and Enterprise plans. You can provision multiple Watson Studio Standard and Enterprise instances in an IBM Cloud account. However, you can provision only one Watson Studio Lite instance per IBM Cloud account.

All Watson Studio plans contain these features without additional services:

All Watson Studio plans contain these features that require additional IBM Cloud services:

Some Watson Studio plans include these features:

The Lite plan allows only one user Watson Studio. That means that other collaborators in your projects must have their own Watson Studio Lite plans.

The Standard and Enterprise plans include a set number of authorized users, which are project collaborators who have the Admin or Editor role, plus an unlimited number of collaborators who have the Viewer role. You can pay to have more collaborators with the Admin or Editor roles. You adjust the number of authorized users on the Authorized Users page. See Manage authorized users.

A set amount of processing usage is included in each plan. Processing usage is measured in capacity unit hours (CUH). With the Standard and Enterprise plans, you can pay for more processing usage. For details on computing resource allocation and consumption, see Runtime usage.

Feature Lite Standard Enterprise
Crowd annotation integration  
Custom encryption keys    
Connectors base set more connectors all connectors
Collaborators 1 1 + viewers + pay for more 5 + viewers + pay for more
Processing usage 50 CUH 50 CUH + pay for more 5000 CUH + pay for more

Learn how to upgrade your plan.

Notebooks

Name Capacity type Capacity units per hour
Default Python 3.5 Free 1 vCPU and 4 GB RAM 0
Default Python 3.6 XS 2 vCPU and 8 GB RAM 1
Default R 3.4 XS 2 vCPU and 8 GB RAM 1
Default R 3.4 S 4 vCPU and 16 GB RAM 2
Default Spark Python 3.6 XS 2 Executors each: 1 vCPU and 4 GB RAM; Driver: 1 vCPU and 4 GB RAM 1.5
Default Spark R 3.4 2 Executors each: 1 vCPU and 4 GB RAM; Driver: 1 vCPU and 4 GB RAM 1.5
Default Spark Scala 2.11 2 Executors each: 1 vCPU and 4 GB RAM; Driver: 1 vCPU and 4 GB RAM 1.5

Spark MLlib modeler flows

Name Capacity type Capacity units per hour
Default Spark Python 3.6 XS 2 Executors each: 1 vCPU and 4 GB RAM; Driver: 1 vCPU and 4 GB RAM 1.5
Default Spark R 3.4 2 Executors each: 1 vCPU and 4 GB RAM; Driver: 1 vCPU and 4 GB RAM 1.5
Default Spark Scala 2.11 2 Executors each: 1 vCPU and 4 GB RAM; Driver: 1 vCPU and 4 GB RAM 1.5

Data Refinery and Data Refinery flows

Name Capacity type Capacity units per hour
Default Data Refinery XS runtime 3 vCPU and 12 GB RAM 1.5
Default Spark R 3.4 2 Executors each: 1 vCPU and 4 GB RAM; Driver: 1 vCPU and 4 GB RAM 1.5

Watson Knowledge Catalog plans

Watson Knowledge Catalog has these plans:

  • Lite: Use this free plan to try the catalog and policy features before you buy the Standard or Professional plan.
  • Standard: Use this plan while you set up your first catalog and policies.
  • Professional: Use this plan when you’re ready to deploy catalogs and policy enforcement throughout your enterprise.

You can provision only one Watson Knowledge Catalog instance per IBM Cloud account.

All Watson Knowledge Catalog plans have these features for catalogs:

All Watson Knowledge Catalog plans have these features for projects:

Some Watson Knowledge Catalog plans include these features:

A set amount of processing usage is included in each plan. Processing usage is measured in capacity unit hours (CUH). With the Standard and Enterprise plans, you can pay for more processing usage.

Feature Lite Standard Professional
Number of catalogs 1 1 unlimited
Number of assets 50 500 unlimited
Business glossary terms 5 50 unlimited
Data policy rules 1 5 unlimited
Information Governance Catalog integration  
Lineage  
Connectors base set more connectors all connectors
Custom encryption keys    
Collaborators 50 users 50 users + pay for more 500 users + pay for more
Processing usage 50 CUH 500 CUH + pay for more 5000 CUH + pay for more

Learn how to upgrade your plan.

Watson Machine Learning plans and compute usage

You use Watson Machine Learning resources, measured in capacity unit hours, when you train AutoAI models, run deep learning experiments, and request predictions from deployed models. This topic describes the various plans you can choose, and what services are included, and provides a list of default computing environments to help you select a plan that matches your needs.

Watson Machine Learning plans

Watson Machine Learning plans govern how you are billed for models you train and deploy with Watson Machine Learning. Choose a plan based on your needs:

  • Lite is a free plan with limited capacity. Choose this plan if you are evaluating Watson Machine Learning and want to try out the capabilities. Note that HIPAA support is not available with the Standard plan
  • Standard is a pay-as-you-go plan that gives you the flexibility to build, deploy, and manage models to match your needs. Note that Decision Optimization and HIPAA support are not available with the Standard plan
  • Professional is a high-capacity, flat-rate enterprise plan designed to support all of an organization’s machine learning needs.

This table provides details for plan allowances and restrictions.

Feature Lite Standard Professional
Max published models 200 1000 1000
Deployed models 5 1000 1000
Predictions 5000 per month Billed per prediction 2 million then billed per 1,000
Capacity Unit Hours 50 per month Billed per CUH 1,000 then billed for additional CUH
HIPAA readiness     Available if provisioned on IBM Cloud - Dallas region
Decision Optimization  
AutoAI Experiments
Batch scoring
Deep learning training Max 8 k80 GPU in parallel Unlimited Unlimited

For details on computing resource allocation and consumption, see Watson Machine Learning plans and compute usage.