GitHub Copilot can use a variety of AI models. This article explains how these models are hosted and served.
OpenAI models
Used for:
- GPT-4.1
- GPT-5-Codex (supported in Visual Studio Code v1.104.1 or higher)
- GPT-5 mini
- GPT-5
- GPT-5.1
- GPT-5.1-Codex
- GPT-5.1-Codex-Mini
These models are hosted by OpenAI and GitHub's Azure infrastructure.
OpenAI makes the following data commitment: We [OpenAI] do not train models on customer business data. Data processing follows OpenAI's enterprise privacy comments.
GitHub maintains a zero data retention agreement with OpenAI.
All input requests and output responses processed by GitHub Copilot's models continue to pass through GitHub Copilot's, content filtering systems. These filters include checks for public code matches (when applied) as well as mechanisms to detect and block harmful or offensive content.
OpenAI models fine-tuned by Microsoft
Used for:
- Raptor mini
Raptor mini is deployed on GitHub managed Azure OpenAI tenant.
Anthropic models
Used for:
- Claude Haiku 4.5
- Claude Sonnet 4.5
- Claude Opus 4.1
- Claude Sonnet 4
These models are hosted by Amazon Web Services, Anthropic PBC, and Google Cloud Platform. GitHub has provider agreements in place to ensure data is not used for training. Additional details for each provider are included below:
- Amazon Bedrock: Amazon makes the following data commitments: Amazon Bedrock doesn't store or log your prompts and completions. Amazon Bedrock doesn't use your prompts and completions to train any AWS models and doesn't distribute them to third parties.
- Anthropic PBC: GitHub maintains a zero data retention agreement with Anthropic.
- Google Cloud: Google commits to not training on GitHub data as part of their service terms. GitHub is additionally not subject to prompt logging for abuse monitoring.
To provide better service quality and reduce latency, GitHub uses prompt caching. You can read more about prompt caching on Anthropic PBC, Amazon Bedrock, and Google Cloud.
When using Claude, input prompts and output completions continue to run through GitHub Copilot's content filters for public code matching, when applied, along with those for harmful or offensive content.
Google models
Used for:
- Gemini 2.5 Pro
- Gemini 3 Pro
GitHub Copilot uses Gemini 3 Pro and Gemini 2.5 Pro hosted on Google Cloud Platform (GCP). When using Gemini models, prompts and metadata are sent to GCP, which makes the following data commitment: Gemini doesn't use your prompts, or its responses, as data to train its models.
To provide better service quality and reduce latency, GitHub uses prompt caching.
When using Gemini models, input prompts and output completions continue to run through GitHub Copilot's content filters for public code matching, when applied, along with those for harmful or offensive content.
xAI models
Complimentary access to Grok Code Fast 1 is continuing past the previously announced end time. A new end date has not been set. We may update or conclude this promotion at any time. Regular pricing applies after the extension ends.
Complimentary access to Grok Code Fast 1 is continuing past the previously announced end time. A new end date has not been set. We may update or conclude this promotion at any time. Regular pricing applies after the extension ends.
These models are hosted on xAI. xAI operates Grok Code Fast 1 in GitHub Copilot under a zero data retention API policy. This means xAI commits that user content (both inputs sent to the model and outputs generated by the model):
Will not be:
- Logged for any purpose, including human review
- Saved to disk or retained in any form, including as metadata
- Accessible by xAI personnel
- Used for model training
Will only:
- Exist temporarily in RAM for the minimum time required to process and respond to each request
- Be immediately deleted from memory once the response is delivered
When using xAI, input prompts and output completions continue to run through GitHub Copilot's content filters for public code matching, when applied, along with those for harmful or offensive content.
For more information, see xAI's enterprise terms of service on the xAI website.