GitHub removes manual model selection from Copilot Free and Student plans, leaving Auto as the sole option

Users on GitHub Copilot’s Free and Student plans can no longer choose models manually. GitHub now limits them to “Auto.”
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GitHub removes model selection from Copilot Free and Student
GitHub announced on June 24, 2026, that it would make Copilot auto model selection the default and sole model selection method for GitHub Copilot Free, the free tier of GitHub Copilot, and GitHub Copilot Student, the free plan for students.
Free and Student users can now use GitHub Copilot’s [Auto] option instead of choosing a model such as GPT, Claude, or Gemini.
Auto chooses the model that best fits the task. Users cannot choose models themselves, and their plan limits which models they can use.
Free or Student users who want to choose models manually will need to consider paid plans that support model selection, each provider’s API, or a separate service such as Claude Code or Codex.

Which models does Auto use?
At the time of writing, GitHub lists GPT-5 mini, GPT-5.3-Codex, GPT-5.4, GPT-5.4 mini, Claude Haiku 4.5, Claude Sonnet 4.6, MAI-Code-1-Flash, Raptor mini, and other models as available through Auto model selection. The models each user can access vary by plan, organization policy, client, and other factors.
In Copilot Chat, you can check which model Auto used by hovering over the response. In Copilot CLI and Copilot cloud agent, GitHub shows the model in the response.
The Student plan had already restricted some model choices, and GitHub has continued revising plans since April
GitHub Copilot Student had already blocked users from choosing some models manually before this change.
In March 2026, GitHub announced that students would lose the ability to choose some premium models, including Claude Opus, Claude Sonnet, and GPT-5.4, as part of a restructuring of its free plan for students.

In April, GitHub then removed GPT-5.3-Codex from the Student plan’s model picker and made it available through Auto alone.
In late April, GitHub said agentic workflows had started consuming more compute resources, paused new sign-ups for Copilot Pro, Pro+, and Student, and announced tighter usage limits and changes to available models.

On June 18, GitHub announced that it would resume new sign-ups for Copilot Student, Pro, Pro+, and Max in phases.
This latest change, which removes manual model selection, appears to form part of the plan revisions GitHub has continued since April.
My analysis
GitHub launched Copilot in 2021 as a service that completed code and generated simple code from instructions such as comments.
In 2023, GitHub added chat. Developers can now use agent mode inside VS Code and external tools such as OpenCode, where AI agents act on human prompts and handle everything from reading and writing code to verification.
Developers often call this style vibe coding or agentic coding. It consumes large amounts of compute because AI agents can operate for long periods, and some developers run multiple agents in parallel.
Given that context, GitHub may be trying to improve Copilot’s profitability.
GitHub had already reduced the models available in the Student plan. It also tightened limits when it moved to credit-based billing: Copilot Pro includes 1,000 AI credits per month, while the Student plan includes 200 AI credits.
Users on GitHub Copilot Free or GitHub Copilot Student can no longer choose a specific model for their work. Developers who want to specify a model will need to move to a higher GitHub Copilot plan or use Claude Code, Codex, each provider’s API, or another option.
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Next articles
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- GitHub temporarily suspends new free trials for Copilot Pro as it steps up measures against increasing abuse
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I've been using JavaScript more than my native language since birth. I am nowhere and everywhere on the internet.
I build web apps and browser extensions in TypeScript as a web frontend programmer. I released Shadowban Scanner, a tool that detects shadowbans on X, and Restore Link Card, a tool that brings back link cards. Media outlets in Japan and abroad covered both tools. For iGEM 2023, I built the Wiki for Team Japan-United and helped the team win the Grand Prize. On my blog, I cover news about X and social media, test and troubleshoot bugs, and share frontend development insights.








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