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Editorial · CASRAI · AI and ML research outputs

GitHub announces December 14 Copilot model deprecations

GitHub plans six Copilot model deprecations for December 14, with an annual-plan exception and model-specific access conditions.

Published 15 Nov 2026· 2 minute read

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GitHub announced on November 13, 2026 that six GitHub Copilot models are scheduled for deprecation on December 14. The change covers Copilot Chat, inline edits, ask and agent modes, and code completions.

Which Copilot models are scheduled for deprecation?

GitHub’s December deprecation notice identifies these replacements:

Model scheduled for deprecation GitHub’s suggested alternative
Claude Fable 5 Claude Fable 5.2
Claude Haiku 4.5 Claude Haiku 5.5
Gemini 3.8 Flash Gemini 4 Hydrogen
Gemini 4 Argon Gemini 4 Carbon
Grok 4.6 Grok 4.7
Kimi K3 To be announced

The Haiku 4.5 deprecation excludes individual Copilot subscribers on annual plans. GitHub asks users to update workflows and integrations before the deadline; users need not remove deprecated models themselves.

Replacement availability depends on model policies

GitHub announced general availability of Gemini 4 Hydrogen on November 13 and Gemini 4 Carbon on November 10. Both release notices describe gradual rollouts and administrator controls for Business and Enterprise customers. A release announcement therefore does not establish that every institutional user already sees the replacement.

GitHub’s supported-model documentation distinguishes default availability from explicit model policies. Its default policy applies to eligible generally available models that administrators have not configured. Exceptions include models outside GitHub’s data-retention agreement.

That qualification matters for Fable 5.2. Its November 9 release notice says the model policy is off by default. Anthropic retains prompts and outputs for safety classifiers by default. Eligible enterprises can obtain a temporary zero-data-retention exemption through the end of 2026, but approval still requires a separate administrator enablement step. For institutions assessing zero data retention for research AI tools, the replacement’s name alone does not establish the applicable configuration.

What the announcement means for university research

For research software teams, the implication is a dated change to the available coding assistant. Recording the selected model and the transition alongside code revisions would help distinguish a software change from a change in how code was generated. Testing replacement-generated changes remains relevant to computational reproducibility; the retirement notice supplies no evidence that a replacement preserves a particular project’s results.

For research offices and university IT teams, the institutional decision concerns both access and data handling. The distinction belongs in an AI governance framework: a suggested replacement, an enabled model policy and approval for a particular research use are separate decisions. The December deadline makes that distinction operational for teams using the affected models.

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