AI Cost and Token Consumption

Measure AI consumption across pull requests, developers, teams, models, and vendors using token usage data collected from supported AI providers.

LinearB presents AI consumption as an estimated cost in USD. This value is calculated from the models and tokens consumed during AI-assisted development.

This release supports the following AI providers:

• Claude (all API integrations and OpenTelemetry)
• Cursor
• GitHub Copilot

Overview

LinearB collects token usage from supported AI providers and correlates that data with engineering activity.

Consumption is presented as an estimated dollar value calculated from the AI models and tokens consumed. It provides a consistent way to compare AI usage across users, teams, repositories, pull requests, and providers, regardless of each provider's billing model.

Use Consumption (Estimated Cost) to understand how AI resources are used across your engineering organization and how that usage relates to delivered work.

Supported providers

• Claude API — Consumption, token usage, AI models, skills, and tool calls.
• Claude OpenTelemetry (OTEL) — Consumption, token usage, AI models, skills, and tool calls.
• Cursor — Consumption, token usage, and AI models.
• GitHub Copilot — Consumption (Estimated Cost), token usage, AI models, usage volume, interactions, and suggested and accepted lines, based on the data available through the GitHub Copilot Metrics API.

Available reports

Two predefined reports are available in the Custom Metric Builder.

Daily AI Cost

Daily AI Cost displays AI consumption as an estimated cost over time.

Use this report to identify changes in AI usage, monitor adoption trends, and compare consumption across time periods.

AI Cost per Pull Request

AI Cost per Pull Request displays AI consumption associated with individual pull requests as an estimated cost.

Each row can include:

• Pull request ID
• Pull request title
• Pull request URL
• Total tokens
• Consumption (Estimated Cost)

Use this report to identify AI-intensive implementation work and understand AI consumption by delivered feature.

Build custom AI cost reports

AI consumption and token usage data is available in the Custom Metric Builder.

You can create custom reports such as:

• Consumption by engineer
• Consumption by team
• Consumption by repository
• Consumption by release
• Consumption by AI model
• Consumption by AI vendor
• Daily AI adoption
• Consumption by project

Leadership use cases

AI consumption data helps engineering leaders answer questions such as:

• Which teams consume the most AI resources?
• Which AI models are used most frequently?
• Which pull requests required the most AI assistance?
• How much AI consumption supports each delivered feature?
• How does AI usage vary across teams, repositories, and projects?
• Which AI vendors are used most across the organization?

Data collection

LinearB aggregates AI usage into daily per-user records and correlates that data with engineering activity.

AI usage can be correlated with:

• Pull requests
• Repositories
• Commits
• AI interactions
• Developers
• Teams

This allows AI consumption to be analyzed alongside existing engineering metrics and custom reports.

Limitations

• GitHub Copilot Consumption (Estimated Cost) is available from June 1, 2026. Earlier GitHub Copilot consumption data is not available.
• Historical AI data is currently backfilled for up to 90 days, subject to each provider's data availability.
• Available metrics depend on the capabilities of each AI provider.
• Skills, tool-call, and model analytics may not be available for all providers.
• Consumption (Estimated Cost) is calculated from token and model usage. It does not represent provider billing or invoice totals.