Platform Units

Overview

For more general information on Platform Units consumption for our AI products, check the Metering and charging logic and License tracking sections.

For specific details on Platform Units consumption for Process Mining, check out the License page in the Process Mining guide.

You can also allocate and track Platform Units consumption at tenant level. Check the Allocating licenses to tenants page from the Automation Suite guide for more details.

Note:

By default, each tenant is allocated 0 Platform Units, and all Platform Units are consumed from the account pool. If there are no Platform Units allocated to the tenant, Platform Units are consumed from the organization account pool. In case all Platform units are consumed from the tenant pool, then the admin needs to allocate more on that specific tenant.

General logic

This section contains specific information regarding Platform Units depending on the used activity, covering the cost for every AI product.

To calculate the overall consumption cost, the following formula is used:

prediction cost + hardware cost = consumption cost

For more information, check the following sections:

• Prediction cost
• Hardware cost

Prediction cost

To calculate the prediction cost, the following formula is used:

input size x unit cost of the model = prediction cost

Input size

Model	Input type	Input size	Computed input size
Document Understanding TM (UiPath and Customer-Managed third party)	Document	1 page	Number of pages in the input document
Communications Mining	JSON	1 message	Number of messages per mailbox or ticketing system
AI Computer Vision	Image	1 image	Always 1
Task Mining	Dataset	1 dataset	Always 1
GenAI Activities	String	String size limit is different for each model
Other models	JSON	2000 characters = 1 unit	Ceil(length(input)/2000)
	File	5 MB = 1 unit	Ceil(size/5MB)
	Files	5 MB = 1 unit	Ceil(sum(size(input))/5MB)

Model used

Model	When we charge	Platform Unit cost
Document UnderstandingTM (UiPath and Customer-Managed third party)	Per prediction	For a list of all Document Understanding models, check the Metering & Charging Logic page from the Document Understanding guide.
AI Computer Vision	Per prediction	0
Models in preview (like UiPath Image Classification)	Per prediction	0
Task Mining	Per successful pipeline	1000
UiPath Light Text classifier	Per prediction	0.04
UiPath Multilingual classifier	Per prediction	0.1
UiPath Custom Named Entity Recognition	Per prediction	0.1
Open Source packages	Per prediction	0.02
GenAI Activities	Per execution	0.2 - without Context grounding 0.4 - with Context grounding

Note:

Except for Task Mining, running a pipeline or deploying an ML Skill only consumes Platform Units related to hardware consumption.

Hardware cost

The hardware cost at the time of deploying ML Skills is calculated as follows:

replicas x resource cost

The default replica count depends on the account type:

• Enterprise account: 2
• Other account types: 1

Note:

Availability is increased by increasing the number of replicas. High Availability (HA) is not guaranteed if user reduces the number of replicas to 1.

Hardware	Platform Units Cost
0.5 CPU 2 GB RAM (default)	0.2 Platform Unit / replica / hour
1 CPU 4 GB RAM	0.4 Platform Units / replica / hour
2 CPU 8 GB RAM	0.8 Platform Units / replica / hour
4 CPU 16 GB RAM	1.6 Platform Units / replica / hour
6 CPU 24 GB RAM	2.4 Platform Units / replica / hour
GPU	4 Platform Units / replica / hour

For hardware cost related to Pipelines, check the following table.

Hardware	Platform Units Cost
CPU	1.2 Platform Units / hour
GPU	4 Platform Units / hour

Note:

Any hour started is charged.