GitHub incident

Elevated rate of errors for OpenAI models provided by Copilot

Resolved after 49 minutes, affecting Copilot AI Model Providers, on September 17, 2026.

resolved Sep 17, 2026, 09:49 PM UTC

Between 20:26 and 21:17 UTC on September 17, 2026, GitHub Copilot experienced degradation affecting several GPT models, including GPT-5.6 Luna, GPT-5.6 Terra, GPT-5.6 Sol, GPT-5.3-Codex, and GPT-6 Astra. Users encountered elevated error rates when using these models. The degradation was caused by an issue with an upstream model provider. GitHub engineers detected the issue through automated monitoring and coordinated with the provider. Our automated model-warning system activated in-product warnings for affected models during the incident. Service returned to normal after the provider implemented a mitigation.

Started
Sep 17, 2026, 08:59 PM UTC
Resolved
Sep 17, 2026, 09:49 PM UTC
Duration
49m
Detected by Pingoru
Sep 17, 2026, 08:59 PM UTC

Affected components

Copilot AI Model Providers

Update timeline

  1. investigating Sep 17, 2026, 08:59 PM UTC

    We are investigating reports of degraded performance for Copilot AI Model Providers

  2. monitoring Sep 17, 2026, 09:39 PM UTC

    We are experiencing degraded availability for GPT-5.6 Luna, GPT-5.6 Terra, GPT-5.6 Sol, GPT-6 Astra, GPT-5.3-Codex in Copilot products and IDE surfaces. This is due to an issue with an upstream model provider. The provider is working to mitigate the problem and we are monitoring recovery. We recommend choosing another model or selecting 'Auto' to continue using Copilot.

  3. resolved Sep 17, 2026, 09:49 PM UTC

    Between 20:26 and 21:17 UTC on September 17, 2026, GitHub Copilot experienced degradation affecting several GPT models, including GPT-5.6 Luna, GPT-5.6 Terra, GPT-5.6 Sol, GPT-5.3-Codex, and GPT-6 Astra. Users encountered elevated error rates when using these models. The degradation was caused by an issue with an upstream model provider. GitHub engineers detected the issue through automated monitoring and coordinated with the provider. Our automated model-warning system activated in-product warnings for affected models during the incident. Service returned to normal after the provider implemented a mitigation.

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