Sharing a Copilot Chat used to mean screenshots and copy-paste. Now it’s as easy as sending a link. Shared conversations are now available in public preview.
Sharing Copilot Chats makes it easier to:
🕵 Troubleshoot with teammates—like this chat digging into a React onClick issue.
🧠 Showcase learning workflows with a friend. Here’s an example walking through Python interview prep, step by step.
🤗 Drop useful insights into a pull request review or team chat—like this example that clears up an open team debate.
🎬️ Demo cool Copilot tricks on social—like this one where Copilot asks smart follow-up questions before jumping in.
How sharing works
Start a conversation. Once you enter your first prompt, the Share button will appear.
Click Share and copy the generated link. Anyone with the link can view the conversation.
If the chat includes private repository content or other restricted GitHub data, viewers will need the appropriate permissions to see it.
As the conversation continues, recipients will see new messages appear in real time.
You can unshare a conversation at any time to revoke access.
Who can use it
Shared conversations are currently in public preview for individual users (not members of organizations or enterprises). We’re actively working on expanding access to all Copilot users soon.
Introducing AI-powered commit message generation with Copilot—available in the latest GitHub Desktop Beta. With a click of a new button in the commit message box, get your changes to upstream with speed, confidence, and an AI-crafted summary.
Copilot commit message generation is available to Copilot Free and all paid Copilot subscribers. Organizations and enterprises can enable it through the “Copilot in GitHub Desktop” policy.
Try it out today—download the GitHub Desktop v3.4.19-beta3 and see how Copilot can supercharge your commit process. Tell us what you think in the GitHub Desktop open source repo.
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OpenAI’s latest reasoning models, o3 and o4-mini, are now available in GitHub Copilot and GitHub Models bringing next-generation problem-solving, structured reasoning, and coding intelligence directly into your development workflow.
These models represent a major leap forward in capability and efficiency:
o3 is the most capable reasoning model in the o-series, ideal for deep coding workflows and complex technical problem solving.
o4-mini is the most efficient model in the series, combining low latency with high-quality output, full tools support, and multimodal inputs.
Both models are optimized for real-world development and support advanced features like function calling, structured outputs, and long-context handling (up to 200K tokens). Whether you’re building agentic tools, analyzing contracts, writing algorithms, or debugging across multiple layers, these models are designed to help you move faster with more accuracy and insight.
Availability in GitHub Copilot
o4-mini is now rolling out across all GitHub Copilot plans and o3 is available to Enterprise and Pro+ plans. You can access them through the model picker in Visual Studio Code and in GitHub Copilot Chat on github.com. To accelerate your workflow, whether you’re debugging, refactoring, modernizing, testing, or just getting started, select “o3” or “o4-mini” to begin using a new model. Stay tuned for updates on additional availability.
Enabling access
Copilot Enterprise administrators will need to enable access to these models through a new policy in Copilot settings. As an administrator, you can verify availability by checking your individual Copilot settings and confirming that policy is set to enabled for the specific model. Once enabled, you’ll see the model in the Copilot Chat model selector in VS Code and on github.com.
Both o3 and o4-mini will also be available through GitHub Models, enabling developers to experiment, build, and deploy AI-powered features faster than ever. In the GitHub Models playground, you can experiment with sample prompts, refine your ideas, and iterate as you build. You can also try them alongside other models, including those from Cohere, DeepSeek, Meta, and Microsoft.
You now have more choices when chatting with Copilot about images in VS Code, Visual Studio, and on the immersive mode on github.com. Starting today, you can use the vision capability with the Claude Sonnet 3.5, Claude Sonnet 3.7, Gemini 2.0 Flash, Gemini 2.5 Pro, and GPT-4o models.
Some ideas to get you started:
Add screenshots of errors with Copilot to have it interpret the image and suggest solutions for the issue.
Share mockups of new designs, and Vision will help you bring them to life.
Ask questions about architecture diagrams.
Currently, the supported image types are JPEG/JPG, PNG, GIF, and WEBP.
When using Vision on VS Code and Visual Studio, make sure you have the Copilot Editor Preview Features policy enabled to get access. On github.com, get started simply by selecting a Claude or Gemini model from the model picker.
GitHub Copilot Chat is now generally available for Eclipse! If you’re an Eclipse user, you can take advantage of AI-powered assistance with both code completions and in-editor chat assistance today.
Key features of GitHub Copilot Chat for Eclipse
Chat view: Ask Copilot for help with coding tasks directly in the chat view. To learn more about this, see our documentation.
Model Selector for Chat: GitHub Copilot allows you to change the model during a chat. To learn more about this, see our documentation.
Slash commands: Use quick commands, like /explain for code explanations.
Reference code: Scope chats to specific files for more relevant assistance.
ABAP Enablement: GitHub Copilot for Eclipse has introduced enablement for ABAP, allowing users to leverage Copilot’s capabilities while working with ABAP code. GitHub Copilot for Eclipse uses the currently available models described in the documentation, without any specific fine-tuning for ABAP.
Try it out
To access GitHub Copilot Chat for Eclipse, you’ll need a Copilot license.
We’re introducing new controls for automation workflows, enhancing security and flexibility for teams. Additionally, we’ve released updates to Actions runner controller designed to improve performance, customization, and compatibility with evolving deployment strategies. As part of our commitment to maintaining up-to-date infrastructure, we’re retiring older images and encouraging users to transition to newer, more efficient options.
Copilot events not automatically triggering GitHub Actions workflows is in public preview
Copilot authored events will no longer automatically trigger GitHub Actions workflows – administrators will now need to approve these workflows to run.
The approval mechanism is the same as approving runs from forks. This means that a run requiring approval will be given the action_required conclusion before any jobs are started. Users with write access in the UI or actions:write fine-grained access through the API can approve any action_required run. Any triggered workflow runs associated with the same PR in the action_required state will show up in the PR merge box for approval.
If a run is not approved after 30 days, it will be deleted.
We’re beginning the process of closing down the Windows server 2019 hosted runner image, following our N-1 OS support policy. This image will be fully retired by June 30, 2025. We recommend updating workflows use windows-2022 or windows-2025.
To raise awareness of the upcoming removal, we’ll temporarily fail jobs using the windows-2019 label starting in June 2025. The brownouts will occur on the following dates and times:
June 3 13:00 – 21:00 UTC
June 10 13:00-21:00 UTC
June 17 13:00-21:00 UTC
June 24 13:00-21:00 UTC
Actions runner controller release 0.11.0
The latest ARC release (0.11.0) includes two major product enhancements and numerous quality-of-life improvements.
Customers can now set custom annotations and resources, enabling them to use deployment methods like ArgoCD and Helm.
In addition, ARC customers experienced performance issues due to high cardinality metrics, particularly around labels such as runner name, ID, job workflow ref, and others. This significantly impacted resource consumption in Prometheus instances. With this release, customers can now configure metrics, enabling them to choose elements relevant to their reporting strategy.
All included changes in this release can be found in the release notes.
Updates to the network allow list for Azure private networking
GitHub previously reported the network communication requirements for Azure private networks as they relate to the upcoming release of immutable actions. Please use the IPs listed in the NSG template within our documentation, as previous changelog communications contained overlapping CIDR ranges.
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OpenAI’s latest model, GPT-4.1, is now available in GitHub Copilot and GitHub Models, bringing OpenAI’s newest model to your coding workflow. This model outperforms GPT-4o across the board, with major gains in coding, instruction following, and long-context understanding. It has a larger context window and features a refreshed knowledge cutoff of June 2024.
OAI has optimized GPT-4.1 for real-world use based on direct developer feedback about: frontend coding, making fewer extraneous edits, following formats reliably, adhering to response structure and ordering, consistent tool usage, and more. This model is a strong default choice for common development tasks that benefit from speed, responsiveness, and general-purpose reasoning.
Copilot
OpenAI GPT-4.1 is rolling out for all Copilot Plans, including Copilot Free. You can access it through the model picker in Visual Studio Code and on github.com chat. To accelerate your workflow, whether you’re debugging, refactoring, modernizing, testing, or just getting started, select “GPT-4.1 (Preview)” to begin using it.
Enabling access
Copilot Enterprise administrators will need to enable access to GPT-4.1 through a new policy in Copilot settings. As an administrator, you can verify availability by checking your individual Copilot settings and confirming the policy for GPT-4.1 is set to enabled. Once enabled, users will see GPT-4.1 in the Copilot Chat model selector in VS Code and on github.com.
GitHub Models users can now harness the power of GPT-4.1 to enhance their AI applications and projects. In the GitHub Models playground, you can experiment with sample prompts, refine your ideas, and iterate as you build. You can also try it alongside other models including those from Cohere, DeepSeek, Meta, and Microsoft.
GitHub Codespaces has introduced a new Agentic AI feature—you can now open a Codespace running VSCode’s Copilot agent mode, directly from a GitHub issue. With a single click, you can go from issue to implementation!
When you’re in a GitHub issue, the right-hand side of the view now displays a Code with Copilot Agent Mode button in the Development section. Clicking this button initializes a new Codespace, opens the Codespace in a new tab, and enables VSCode’s Copilot agent mode, using the issue body as context. Copilot will then get to work on the issue, thoroughly analyzing the codebase and considering dependencies to suggest appropriate file changes. You can then work with Copilot to fine tune your code and make modifications as required.
VSCode Agent Mode in Codespaces is in public preview, and we’ll be iterating on the experience over the upcoming months. Stay tuned for updates!
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Gemini 2.5 Pro is now available to all GitHub Copilot customers. The latest Gemini model from Google is their most advanced model for complex tasks. It shows strong reasoning and code capabilities. It also leads on common coding, math, and science benchmarks.
Get started today!
Copilot Pro/Pro+ users
You can start using the new Gemini 2.5 Pro model today through the model selectors in Copilot Chat in VS Code and immersive chat on github.com.
Copilot Business or Enterprise users
Copilot Business and Enterprise organization administrators will need to grant access to Gemini 2.5 Pro in Copilot through a new policy in Copilot settings. Once enabled, users will see the model selector in VS Code and chat on github.com. You can confirm the model’s availability by checking individual Copilot settings and confirming the policy for Gemini 2.5 Pro is set to enabled.
Issues, discussions, and pull requests – these are all important pieces of context when building in GitHub. Now, you can reference these within Copilot Chat. Simply paste a link into the chat and Copilot will do the rest!
How it helps you
📂 Multi-repository support: want to compare a pull request from one project with a discussion from another? No problem!
🏷️ Intuitive navigation: maybe you pasted a link, got up to make a coffee, and forgot what you were doing. With chips in the chat context, you don’t need to worry – it will always be clear what you’ve added.
⌨️ Context-building at your fingertips: let Copilot support you and integrate your work by focusing on the specific problems you want to address.
We like to think that GitHub files and Copilot are both great, and they’re even better when they come together. The power of Copilot and the fountain of knowledge in your repositories will collectively help you do amazing things. We know it.
💬 Let us know what you think using the in-product feedback option or pop it into the GitHub Community at any time.
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You can now easily regenerate Copilot responses using a different model. Simply click the retry button underneath Copilot’s response. Copilot will process the same prompt by your chosen model while maintaining all previous conversation context. You can also view previous responses and compare model output.
How it helps you
🧩 Stuck on a complex problem? Switch to a more powerful model for deeper reasoning.
⚡ Need a quick response? Reload with a faster model when speed matters.
💻 Working with code? Switch to a model optimized for programming.
🎨 Fine-tuning creative work? Try different models to explore alternative approaches.
This feature is perfect for when you need a different perspective or more specialized capabilities. Seamlessly blend the strengths of various models into a single conversation. Enjoy more intelligence, more flexibility, and more control – all while staying in the flow.
💬 Let us know what you think using the in-product feedback option or pop it into the GitHub Community at any time.
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Security campaigns with Copilot Autofix are now generally available. As part of GitHub Code Security, you can use security campaigns to prioritize and rapidly reduce your backlog of application security debt. Copilot Autofix generates contextual explanations and fixes for historical code scanning alerts in a security campaign, which help developers and security teams collaborate to fix vulnerabilities with speed and confidence.
With the help of GitHub’s CodeQL and Copilot Autofix, it has never been easier to prevent new vulnerabilities from being added to your code. However, if you don’t address vulnerabilities discovered in already-merged code, security debt can build up and pose a serious risk to deployed applications.
A security campaign on GitHub can contain a large number of code scanning alerts, prioritized by your security team to be fixed within a chosen timeframe. When a campaign is created, Copilot Autofix automatically suggests fixes, and developers who are most familiar with the code are notified. From there, they can review the fixes, open pull requests, and remediate security debt. Security teams can monitor the progress of the campaign and track the number of fixed alerts. Using security campaigns, security and developer teams work together with Copilot Autofix to remove security debt in targeted efforts aimed at maximizing impact by focusing on the alerts that matter.
Starting today, you can also access these new features to plan and manage security campaigns more effectively:
Draft security campaigns: Security managers can now iterate on the scope of campaigns and save them as draft campaigns before making them available to developers. With draft campaigns, security managers can ensure that the highest priority alerts are included before the work goes live.
Automated GitHub issues: Security managers can optionally create GitHub issues in repositories that have alerts included in the campaign. These issues are created and automatically updated as the campaign progresses and can be used by teams to track, manage, and discuss campaign-related work.
Organization-level security campaign statistics: Security managers can now view aggregated statistics showing the progress across all currently-active and past campaigns.
Security campaigns are available for users of GitHub Code Security on GitHub Enterprise Cloud. For more information about security campaigns, see About security campaigns in the GitHub documentation.
If you have any feedback on security campaigns, join the discussion in GitHub Community.
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Code review is one of the most critical parts of software development, but manual code reviews can be time-consuming. Copilot code review helps you offload basic reviews to a Copilot agent that finds bugs, potential performance problems, and even suggests fixes. This means you can start iterating on your code while waiting for a human review, helping you keep your code repositories more maintainable and focused on quality.
In just over a month since we launched the public preview, over 1 million developers have already used Copilot code review, and the response has been incredible.
Check it out in action, in both Visual Studio Code and GitHub:
To request a code review from Copilot, you can set up automatic reviews in a repo through repository rules. Or, you could ask Copilot to review a pull request on demand.
Copilot code review is available to all paid Copilot subscribers. Organizations and enterprises can enable it through the Copilot in github.com policy.
What’s next
We’re continuously improving Copilot code review. Today we’ve added support for C, C++, Kotlin, and Swift in public preview and we’ll add support for HTML and txt early next week.
Today, we’re introducing GitHub Copilot Pro+, a new individual tier for developers who want to take their coding experience to the next level.
Enjoy all the features you love from GitHub Copilot Pro along with exclusive access to the latest models (GPT-4.5 is available today), priority access to previews, and 1500 premium requests per month when they go live on May 5th. This is in addition to the unlimited requests for agent mode, context-driven chat, and code completions that all paid plans have when using our base model.
Anthropic Claude 3.7 Sonnet, Claude 3.5 Sonnet, OpenAI o3-mini, and Google Gemini Flash 2.0 are now generally available in GitHub Copilot. With this change, these models are promoted from preview release terms to generally available release terms. This extends indemnification for IP infringement to code generated using these models in Copilot Chat and agent mode.
Claude 3.7 Sonnet, Anthropic’s most advanced model to date, excels in development tasks that require structured reasoning across large or complex codebases.
Claude 3.5 Sonnet remains a good choice for everyday coding support.
OpenAI o3-mini is a fast, cost-effective reasoning model designed to deliver coding performance while maintaining lower latency and resource usage.
Gemini 2.0 Flash is Google’s model optimized for fast responses and multimodal interactions.
