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Last updated Oct 10, 2024

AI Units

Overview

Tip: To track your AI units consumption at organization and tenant level, check the following pages: To track your AI units consumption for Document UnderstandingTM and AI Center projects, check the Document Understanding and AI Center consumption dashboard page from the Insights user guide.

AI Units is the measure used to license AI products. AI Units are charged based on consumption when the models are bringing value to you.

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

Fore specific details on AI units consumption for Process Mining, check out the License page in the Process Mining guide.

You can also allocate and track AI units consumption at tenant level. See the tenant-level allocation pages for more details:

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

Metering and charging logic

General logic

This page contains specific information regarding AI 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 below:

  • 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
For example, the consumption for UiPath Custom Named Entity Recognition model with input size 5000 characters is as follows:
5000 characters = 3 units Consumption: 3 units x 0.5 (unit cost) = 1.5 AI Units

Input size

ModelInput typeInput sizeComputed input size
Document UnderstandingTM (UiPath and Customer-Managed third party)Document1 pageNumber of pages in the input document
Communications MiningJSON1 messageNumber of messages per mailbox or ticketing system
AI Computer VisionImage1 imageAlways 1
Task MiningDataset1 datasetAlways 1
GenAI ActivitiesStringString size limit is different for each model
Other modelsJSON2000 characters = 1 unitCeil(length(input)/2000)
File5 MB = 1 unitCeil(size/5MB)
Files5 MB = 1 unitCeil(sum(size(input))/5MB)

Model used

ModelWhen we chargeUnit 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 VisionPer prediction0
Models in preview (like UiPath Image Classification) Per prediction0
Task MiningPer successful pipeline5000
Communications MiningPer message uploaded, modified, or predicted1 - for more information on Communications Mining charging logic, check the official documentation.
UiPath Light Text classifierPer prediction0.2
UiPath Multilingual classifierPer prediction0.5
UiPath Custom Named Entity RecognitionPer prediction0.5
Open Source packages

Per prediction

0.1
GenAI ActivitiesPer execution1
Note: Except for Task Mining, running a pipeline or deploying an ML Skill only consumes AI 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.

Use the following table to check the resource cost for ML Skills.

HardwareUnit Cost
0.5 CPU 2 GB RAM (default)1 AI Unit / replica / hour
1 CPU 4 GB RAM2 AI Units / replica / hour
2 CPU 8 GB RAM4 AI Units / replica / hour
4 CPU 16 GB RAM8 AI Units / replica / hour
6 CPU 24 GB RAM12 AI Units / replica / hour
GPU20 AI Units / replica / hour

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

HardwareUnit Cost
CPU6 AI Units / hour
GPU20 AI Units / hour
Note: Any hour started is charged.

Consumption example

Background information

To automate a given process, you need to use the two following UiPath models:

The first step is to train the Multilingual Text Classification model on your dataset. The training takes 6 hours and 30 minutes using GPU.

After deploying both models as HA skills, they are running on CPU for three months. During this time, the Multilingual Text Classification model processed 20,000 texts, all around 3,000 characters, while the Invoices model processed 10,000 invoices containing 2 pages each.

Calculating total consumption

  • AI Units consumed for training Multilingual Text Classification:
    7 (hours) x 20 (AI units per hour for GPU) = 140 AI Units
  • AI Units consumed for hosting Multilingual Text Classification for three months:
    24 (hours in day) x 90 (number of days) x 2 (AI units per hour) = 4320 AI Units
  • AI Units consumed for hosting Invoices for three months:
    24 (hours in day) x 90 (number of days) x 2 (AI units per hour) = 4320 AI Units
  • AI Units consumed for predictions made using Multilingual Text Classification:
    20000 (number of predictions) x 2 (input size) x 0.5 (unit cost) = 20000 AI Units
  • AI Units consumed for predictions made using Invoices:
    10000 (number of predictions) x 2 (input size) x 1 (unit cost) = 20000 AI Units
  • AI Units consumed in total:
    hardware cost + predictions cost = (140 + 4320 + 4320) + (20000 + 20000) = 48780 AI Units

License tracking

AI Units are tracked under AI Units for all scenarios.



If you hover your mouse over the bar from the AI Units section, a pop-up is displayed. You can check this pop-up to see your exact consumption.



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