Billing details for generative AI assets

Learn about how usage for generative AI assets is measured using resource unit (RU), hourly rates, or a flat rate.

Working with generative AI assets with watsonx.ai Runtime requires that you are using watsonx.ai. Overview of IBM watsonx.ai.

Review the details for how resources are measured using:

  • Resource units to measure inferencing atcivities for foundation models provided by watsonx.ai.
  • Hourly rates for custom foundation models you import and deploy with watsonx.ai.
  • Hourly rates for curated foundation models deployed on demand on dedicated hardware.
  • Flat rates by page for document text extraction.

Resource unit metering for foundation models

For the list of supported foundation models and their prices, see Supported foundation models. For the list of supported encoder models and their prices, see Supported encoder models.

A Resource Unit (RU) is equal to 1000 tokens from the input and output of foundation model inferencing. A token is a basic unit of text (typically 4 characters or 0.75 words) used in the input or output for a foundation model prompt or for input to an embeddings model.

Each foundation model provided by IBM watsonx.ai is assigned an inference price for input and output. The price is derived as a multiple of the base price for an RU ($0.0001). For example, a model with a price of $0.0006 has a multiplier of 6 times the base rate.

Important: There are limits by plan on the number of inferencing requests per second that are submitted to a model. If a user exceeds an inferencing request limit, a system notification provides guidance.

A prompt tuned foundation model is assigned the same price as the underlying foundation model. For information about tuned foundation models, see Tuning Studio. Tuning a model in the Tuning Studio consumes capacity unit hours (CUH). For more information, see Billing details for machine learning assets.

Calculating the resource unit rate per model

To calculate charges for foundation model inference, divide the total number of tokens consumed during the month by 1000 and round up to the nearest 1000 to obtain the total number of RUs. Multiply the total number of RUs by the model price to obtain total usage charges. The model price varies by model and can also vary for input or output tokens for a given model.

The basic formula is as follows:

Total tokens used/1000 = Resource Units (RU) consumed
RU consumed x model price = Total usage charge

The base price for an RU is $0.0001. The price for each foundation model is a multiple of the base price.

Billing classes by multiplier

If you are monitoring model usage with the watsonx.ai API, model prices are listed by pricing tier, as follows:

Table 1. API pricing tiers
Model pricing tier Price per RU in USD Multiplier
x base rate
Class 1 $0.0006 6
Class 2 $0.0018 18
Class 3 $0.0050 50
Class C1 $0.0001 1
Class 5 $0.00025 2.5
Class 7 $0.016 160
Class 8 $0.00015 1.5
Class 9 $0.00035 3.5
Class 10 $0.0020 20
Class 11 $0.000005 0.05
Class 12 $0.0002 2
Note:

Certain models, such as Mistral Large, have special pricing that is not assigned by a multiplier. The pricing is listed in Supported models.

Hourly billing rates for custom foundation models

Deploying custom foundation models requires the Standard plan.

Billing rates are according to model hardware configuration and apply for hosting and inferencing the model. Charges begin when the model is successfully deployed and continue until the model is deleted.

Table 2. Custom foundation model billing rates
Configuration size Billing rate per hour in USD
Small $5.22
Medium $10.40
Large $20.85
Important: You can deploy a maximum of four small custom foundation models, two medium models, or one large model per account.

For details on choosing a configuration for a custom foundation model, see Planning to deploy a custom foundation model.

Hourly billing rates for deploy on demand models

Deploy foundation models on demand when you want a hosted solution reserved for the exclusive use of your organization. Only colleagues to whom you grant access to the deployment can inference the foundation model. A dedicated deployment means faster and more responsive interactions, and allows for prompts with larger context window lengths. Billing rates are set per model and apply for hosting and inferencing the model. Charges begin when the model is deployed and continues until the model is deleted.

Note: Deploying foundation models on demand requires the Standard plan. This feature is currently available only for the Dallas data center.

For details on on deploying a foundation model on demand, including pricing, see Supported foundation models available with watsonx.ai.

Rates per page for document text extraction

Use the document text extraction method of the watsonx.ai REST API to convert PDF files that are highly structured and use diagrams and tables to convey information, into an AI model-friendly JSON file format.

Billing is charged at a flat rate per page processed. A page can be a page of text (up to 1800 characters), an image, or a .tiff frame. The billing rate depends on your plan type.

Table 3. Text extraction pricing
Plan type Price per page in USD
Essential $0.038
Standard $0.030

Learn more

Parent topic: watsonx.ai Runtime plans