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GitHub Copilot introduces three levels of auto model selection for cost and quality

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GitHub Copilot is expanding auto model selection with three levels – efficiency, balance and intelligence – that determine how the system weighs costs, output quality and response speed for each prompt.

GitHub has added three levels to auto model selection in Copilot: efficiency, balance and intelligence. Users choose a level based on how they want the system to balance costs, output quality and response time for individual prompts, and Copilot optimizes model selection accordingly.

All three levels work with the same set of available models; auto evaluates each prompt individually and selects the most suitable model. According to GitHub, a simple task, such as adding a docstring to an existing function, may therefore use a small, efficient model even when the intelligence level is selected.

The feature is gradually rolling out in Visual Studio Code, Copilot CLI and the GitHub Copilot app. Billing is based on the model that auto actually selects, regardless of the chosen level, and paid users continue to receive a 10% discount on usage billed through auto. According to GitHub, this is the first step toward greater customization of model selection and better visibility into the trade-offs users make when choosing.

What changed

Why it matters

Developers and teams using GitHub Copilot gain direct control over whether to prioritize lower costs, faster responses or higher output quality for a specific task, without having to manually select a particular model. For companies paying for Copilot licenses, this provides a tool for managing the costs of AI assistance in development, because billing is based on the model actually used, not the chosen level, and paid users retain their discount on usage through auto.

Two audiences, two different impacts

What this means

01

For individuals

A developer can choose the efficiency, balance or intelligence level for a specific task, influencing the balance between response speed, costs and the quality of the response from Copilot without manually switching between individual models.

What to do Try out and set the auto model selection level based on task type – efficiency for simple edits, intelligence for more demanding tasks.
More practical updates →
02

For a business

Companies paying for GitHub Copilot can use the level selection (efficiency, balance, intelligence) to manage the costs of using the AI assistant across teams; billing is based on the specific model selected, and paid users continue to receive a 10% discount on usage billed through auto.

Development
What to decide Consider recommendations for development teams on which level (efficiency/balance/intelligence) to use based on task type, and monitor the impact on costs billed through auto.
More business impacts →
auto model selection cost optimization GitHub Copilot LLM selection model selection

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Event sources

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GitHub Copilot Changelog primary source · first detected Configure cost and quality in Copilot auto model selection