GitHub Copilot

HydraFusion has an updated model pool, improved orchestration workflows, and introduces HydraFusion Max. Both HydraFusion and HydraFusion Max are available across VS Code, the GitHub Copilot app, and GitHub Copilot CLI and remain in research preview. HydraFusion orchestrates multiple models to produce a single response, bringing together their strengths so you don’t have to choose an individual model for each task. What’s new in HydraFusion Latest frontier models: HydraFusion and HydraFusion Max draw from a pool that now includes Claude Opus 5.5, GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna. The models used for each task vary based on the orchestration workflow. Reasoning effort tailored to each step: Previously, HydraFusion only used each model’s default reasoning effort. With this update, it explicitly tailors effort to each stage, using medium effort for initial drafts and high effort for review. This keeps drafting efficient while dedicating deeper reasoning to checking and improving the work. Optimized Cascade and Critique workflows: Cascade: Previously used an initial model to solve the task, with escalation to a stronger model when needed. It can now include a judging step that inspects the initial work and requests a repair only when needed. Critique: Previously relied heavily on text summaries. It now relies more on tools to inspect the actual workspace directly. Critique now also uses parallel critic models to inspect work. Introducing HydraFusion Max HydraFusion Max is built on the same architecture and uses the same workflow techniques as HydraFusion, but is tuned for frontier capability on more demanding tasks. It applies higher reasoning efforts where depth and thoroughness matter most, while still using orchestration to consider token efficiency. Option Description Typical use case HydraFusion Balanced approach with moderate token savings. Agentic tasks that require a balance of speed, cost, and performance. HydraFusion Max Frontier capability for more demanding tasks, with token efficiency considered through orchestration. Tasks requiring the deepest possible reasoning and most thorough analysis. Both options are supported across all three clients, so you can access the latest HydraFusion experience whether you work in VS Code, the GitHub Copilot app, or the terminal. HydraFusion and HydraFusion Max are available on Copilot Pro, Pro+, Business, and Enterprise plans with experimental or preview features enabled, subject to your organization’s model policies. Learn more in the HydraFusion documentation. Share your feedback in the HydraFusion discussion.

Gemini 4 Argon, Google’s newest frontier model, is now generally available in GitHub Copilot. It is designed for complex coding, agentic, and reasoning tasks. In early testing, Gemini 4 Argon solved more tasks than previous Gemini models on every coding benchmark, with its largest gains in Copilot CLI. It also thoroughly checks its work, testing edge cases before it finishes. This model is billed at provider list pricing under usage-based billing. See Models and pricing for GitHub Copilot for details. Availability in GitHub Copilot Gemini 4 Argon is available to Copilot Pro+, Max, Business, and Enterprise users. You can select the model in the model picker in: Visual Studio Code Visual Studio Copilot CLI GitHub Copilot coding agent GitHub Copilot app JetBrains IDEs Xcode Eclipse Rollout will be gradual. Check back soon if you don’t see it yet. Enabling access Copilot Enterprise and Copilot Business plan administrators can manage access to Gemini 4 Argon through the model policy in Copilot settings. Under default model enablement, new models are automatically enabled unless an administrator has turned off the global default or explicitly disables this model. Learn more To explore all models available in GitHub Copilot, see our documentation on models and get started with Copilot. Share your feedback Join the GitHub Community to share your feedback.

Enterprise administrators can now require supported GitHub Copilot clients to retrieve current server-managed settings at startup instead of relying on a cached policy. We are also adding minimum client version requirements to governance-focused managed settings keys over time, starting with the sandbox key. Force refresh settings on client startup Set forceRemoteSettingsRefresh to true through server-managed, MDM-managed, or file-based settings when a policy change must take effect before Copilot starts. The setting is supported in Copilot CLI, VS Code, and the GitHub Copilot app. MDM-managed and file-based delivery can require freshness before the client signs in for the first time. A server-managed value begins requiring refreshes on subsequent startups after the client has received it once. While the setting is active, a cached response cannot satisfy the freshness requirement. If the client cannot confirm current policy, it fails closed rather than running with a stale or unconfirmed policy. Without this setting, clients continue to use the normal managed-settings cache for faster startup and resilience during transient service failures. Minimum required client version We’ve also added enforcement of a required minimum client version to the sandbox key in support of the generally available local sandbox capability. When this key is included in managed settings, users who pin to older versions of Copilot clients will now be forced to update in order to resume using Copilot. To learn more, see Deploying enterprise managed settings. Join the discussion within GitHub Community.

Enterprise administrators can now use telemetry in managed settings to attribute GitHub Copilot activity to a user without collecting their prompts, responses, or tool content. The telemetry.capture.identity setting adds three attributes to OpenTelemetry (OTel) data: user.name: The authenticated Copilot account name, currently the GitHub login. process.user.name: The local operating-system account. host.name: The local machine name. Identity capture is off by default and remains separate from the existing pseudonymous user identifier. Fine-grained capture controls are available in Copilot CLI, the GitHub Copilot app, and VS Code sessions using Agent Host. Administrators can also independently control five additional capture classes: prompts: User, system, and developer prompts and supported input context. responses: Assistant responses and supported reasoning content. toolArguments: Raw tool arguments, commands, tool schemas, and identifiers for tools, MCP servers, plugins, and hooks. toolOutput: Tool results and execution-error details. policyDetail: Raw policy details such as sandbox filesystem paths. Every capture class is off by default. Explicit managed values take precedence over local settings, SDK configuration, and environment variables. The existing captureContent setting remains available as a legacy shorthand for the five content classes, but it never enables identity. Prompt, tool, and policy capture can include source code, file contents, commands, tool results, and workspace or user-profile paths. Enable only the classes required for your audit use case and send them to an approved collection endpoint. To learn more, see the enterprise managed settings reference and monitor agent usage with OpenTelemetry. Join the discussion within GitHub Community.

This update brings more control over default models and MCP server in GitHub Copilot for JetBrains. It also makes diagnostics easier to address, improves chat navigation and account controls, and strengthens reliability across agent sessions, customizations, and worktrees. What’s new Enterprise-managed default models Enterprise administrators can now use managed settings to choose any available Copilot agent model as the default for new conversations. This gives organizations more control over the starting model while still preserving an explicit model picker choice. Faster fixes from diagnostics Diagnostic intention menus now include a Fix action that opens inline chat and asks Copilot to repair the issue. The action uses agent mode when it is available and ask mode otherwise, helping you move from a reported problem to a proposed fix with fewer steps. More control over MCP server startup A new MCP setting lets you disable automatic server startup for Copilot and Claude, giving you more control over when configured tools become active. User experience enhancements This release makes everyday chat, account, and navigation workflows clearer: Account controls: Signed-in Copilot accounts now have clearer labels, a simpler status display, better navigation for long lists, and a Switch Account action. Chat discovery and sign-in: A one-time reminder helps new users find Chat, while the sign-in page has a responsive layout, clearer headings, improved provider choices, a direct Copilot plans link, and cancellable progress during browser authorization. Conversation navigation: Chat messages are grouped by turn, with controls for moving quickly between turns. Message actions: User messages now include actions to copy or edit their content. Agent guidance: The Copilot agent placeholder now highlights questions, edits, context, and commands. Migration flow: After you accept a migration command, Go Back opens a Copilot home session even when you continue the local conversation. Quality improvements This release improves reliability during language server startup, model and provider switching, MCP configuration, customization refreshes, file changes, and worktree workflows. It also resolves interaction and display issues in model management, tool-call details, working sets, and JetBrains IDE settings. Deprecation GitHub Copilot has ended support for JetBrains IDE 2025.1. You now need JetBrains IDE 2025.2 or later to use the plugin. Try it out We encourage you to try out the latest version of the GitHub Copilot plugin and share your feedback. Your input is invaluable in helping us refine and improve the product. Share your feedback Your feedback drives improvements. We’d love to hear about your experience in the following channels: In-product feedback: Use the feedback options within your IDE. Feedback repository: Share your thoughts in the GitHub Copilot for JetBrains IDEs issues.

This week’s updates make Copilot easier to use across accounts and environments, with more control over what agents can access and how you manage their work. GitHub Copilot Claude Haiku 5.5 is available to Copilot Pro, Pro+, Max, Business, and Enterprise users. Limit agents’ access to files, networks, and credentials with local sandboxing, now generally available in Copilot CLI, the Copilot app, and VS Code sessions using Agent Host. This is included with Copilot at no extra cost. Learn more about local sandboxing. GitHub Copilot app The Copilot app now lets you use separate GitHub accounts for your Copilot license and your repositories. For example, use an enterprise-provided Copilot license while accessing repositories through another account. Download the Copilot app. GitHub Copilot CLI GitHub Copilot CLI makes it easier to choose a local model without leaving your existing workflow. Use /model to discover supported models from a running local Ollama instance, alongside your configured models and cloud models provided by GitHub Copilot. Discover local models in GitHub Copilot CLI. GitHub Copilot in VS Code (1.141 release) View agent sessions side by side in the Agents window. Arrange them in a grid to compare results or follow multiple tasks. Free up disk space with “Open worktree cleanup” in chat. See how much space inactive session worktrees use and choose which to remove. Explore everything that’s new in the full VS Code release notes.

This release adds new billing and license controls for Copilot code review admins: Billing: Organization owners can bill Copilot code reviews from members with a Copilot license to the organization’s cost center instead of using up those members’ Copilot quotas. Review request controls: Organization owners and repository admins can control whether people with external licenses can request a review. 💳 Choose how members with a Copilot license are billed By default, Copilot code review bills requests associated with members who have a Copilot license to that member’s own Copilot entitlement. Organization owners can now choose to bill the organization that owns the repository instead in order to avoid consuming or exhausting member quotas. The Choose how members with a Copilot license are billed setting has two options: Member (default): Bills the member’s own Copilot entitlement. If the member’s quota is exhausted, the code review fails. Organization: Bills the organization that owns the repository. This requires AI Credits paid usage to be enabled for the organization, and you can optionally set a budget. You can find the setting in your organization settings, under Copilot -> Policies. 🔒 Control who can request a review By default, anyone with a paid Copilot license can use it to request a review from Copilot in the repositories they have access to. Organization owners and repository admins can now, if desired, turn on the Only allow Copilot code review to be triggered by authorized users setting to require that review requests come from people with a Copilot license provided by your organization or enterprise. When it’s on, people can’t use a Copilot license from outside your organization or enterprise (e.g., a personal license) to request a review. If you turn it on at the organization level, repository admins can’t turn it off. For details on how the setting applies to personal repositories, automatic reviews, and API requests, see Reviews requested with an external Copilot license.

Claude Haiku 5.5, Anthropic’s newest lightweight model, is now generally available in GitHub Copilot. It is designed for fast, high-volume work like subagents, quick edits, and terminal tasks. In early testing, Haiku 5.5 matched Claude Sonnet 5 on many coding tasks while using significantly fewer tokens and steps. This model is billed at provider list pricing under usage-based billing. See Models and pricing for GitHub Copilot for details. Availability in GitHub Copilot Claude Haiku 5.5 is available to Copilot Pro, Pro+, Max, Business, and Enterprise users. You can select the model in the model picker in: Visual Studio Code Visual Studio Copilot CLI GitHub Copilot cloud agent GitHub Copilot app github.com GitHub Mobile on iOS and Android JetBrains IDEs Xcode Eclipse Rollout will be gradual. Check back soon if you don’t see it yet. Enabling access Copilot Enterprise and Copilot Business plan administrators can manage access to Claude Haiku 5.5 through the model policy in Copilot settings. Under default model enablement, new models are automatically enabled unless an administrator has turned off the global default or explicitly disables this model. Learn more To explore all models available in GitHub Copilot, see our documentation on models and get started with Copilot. Share your feedback Join the GitHub Community to share your feedback.

Secret protection should keep pace with the way you build software, whether you write code yourself or work with an AI agent. With our new purpose-built model, we’re bringing context-aware detection into more developer workflows to help you catch secrets before they’re exposed. What’s new Today, we’re sharing plans for AI secret detection across secret scanning alerts, push protection, and GitHub Copilot security reviews. These features leverage GitHub’s fine-tuned model for secret detection. It reads surrounding code to identify likely credentials, including passwords without a recognizable token format, without generating code or prose. Model availability: Customers with AI-detected Password alerts have automatically been upgraded to the new model. AI-detected secrets in push protection is available in private preview. AI-based secret scanning with the GitHub Copilot /security-review command for the Copilot CLI and Copilot app available soon in private preview. Billing notice and availability AI-detected secret alerts will remain included in GHSP and GHAS at no additional charge. The new opt-in checks for push protection and the security review command will consume GitHub AI Credits. We’re sharing their planned billing model ahead of broader availability so you can review access and spending before enabling them. This notice applies to the following features: AI-detected secrets in push protection for GitHub Secret Protection (GHSP) and GitHub Advanced Security (GHAS) AI-based secret scanning with the GitHub Copilot /security-review command AI Credit usage for these opt-in checks will be introduced in the coming weeks. AI-detected alerts remain included with Secret Protection Starting today, existing AI-detected secret alert scans will automatically switch to the new model at no additional charge for GHSP and GHAS customers. These scans remain included in GHSP and GHAS, separate from the new credit-consuming checks. AI-detected alerts are coming to GitHub Enterprise Server The model will also bring AI-detected alerts to GHES 3.23 in public preview. This feature is included with an enterprise’s existing purchase of GHSP and GHAS. AI secret detection in push protection AI push protection checks for unstructured credentials at push time, giving you a chance to remove a secret before it enters repository history. The feature will be available to customers on GitHub Enterprise Cloud or GitHub Teams with a purchase of GHSP or GHAS. An administrator must enable it, subject to your organization’s or enterprise’s policies. The planned AI Credit usage will be billed to the organization that owns the repository. A check can consume credits even if it doesn’t block a push. Outside of user-namespace repositories for enterprise-managed users (EMUs), where usage is attributed to the pusher and apply to the user’s allocated credits, AI Credit usage will be attributed to the organization and will not apply to any specific user’s allocated credits. Usage will be listed under AI Credit consumption for the Secret Protection AI Credits SKU in your AI usage insights. Billing begins once your organization opts into the public preview and enables the feature. AI secret checks in GitHub Copilot /security-review In a supported Copilot CLI or Copilot App session, use /security-review before committing, pushing, or requesting pull request review. It reviews active changes for security vulnerabilities and returns prioritized findings with remediation suggestions. Developers and coding agents can use the built-in security-review specialist, address confirmed findings with the appropriate authorization, and run the review again after fixes. The review is read-only—existing Copilot policies and billing apply. Coming soon, GitHub is adding checks from the secret classifier alongside the existing LLM-based review. You don’t need a GHSP or GHAS license to use these checks. The new checks will consume AI Credits in addition to the review’s existing usage. The billing account for your active Copilot plan will receive this usage, reported under GHSP in your AI usage insights. Billing begins once you opt into the public preview and enable the feature. The new checks will be off by default. Running /security-review won’t enable them. You must opt in where your plan and policies allow. Agents shouldn’t enable credit-consuming features or change policies or budgets without explicit authorization. See the Copilot CLI security-review agent documentation and security-review instructions for Copilot App sessions. Plans and platforms GitHub hosting plans, GHSP licenses, and Copilot subscriptions are separate. GitHub Enterprise (GHE) includes GitHub Enterprise Cloud (GHEC) and GitHub Enterprise Server (GHES). Copilot Enterprise is a separate Copilot subscription. Plan or platform Eligibility for these updates GitHub Team and GHEC on github.com AI push protection requires paid GHSP or GHAS coverage. Public, private, and internal repositories can qualify. GHEC with data residency on ghe.com Copilot Business and Enterprise are supported plans on this platform with the Copilot security review command. AI push protection is planned with paid GHSP/GHAS coverage. GHES The new model is planned for AI-detected alerts in GHES 3.23, at no additional charge with GHSP/GHAS. AI push protection isn’t part of this Server release. The Copilot security review command isn’t part of this Server release. Individual Copilot plans: Pro, Pro+, Max, Free, and Student Eligible for security review checks with the new model, subject to access controls and credit consumption. No GHSP or GHAS license is required. Copilot Business and Copilot Enterprise Eligible for security review checks with the new model on supported platforms, subject to invitation and administrator policies. These subscriptions don’t replace the GHSP license required for AI push protection. Manage access and spending Organization and enterprise administrators will be able to disable the new capabilities by policy and set budgets for their AI Credit usage. Opting in won’t override those controls. Applicable included credits and any additional paid usage follow your account’s billing policies and limits. To set a dedicated budget, open Billing and licensing and select Budgets and alerts. Choose SKU-level budget, Advanced Security as the product, and Secret Protection AI Credits as the SKU. An all AI Credits budget can cover multiple credit-consuming SKUs. Budget alerts alone don’t stop usage. Configure Stop usage when budget limit is reached where available if you want a spending cap. If you’re already using AI push protection in private preview, continued use after this billing change takes effect will consume AI Credits. Disable it beforehand if you don’t want that usage. AI-detected alert scanning remains included at no additional charge. Before enabling or continuing the new checks, review the eligibility, AI Credit pricing, and billing details above, along with your budget settings and documentation for usage-based billing.

Local sandboxing for GitHub Copilot is now generally available in GitHub Copilot CLI, the GitHub Copilot app, and VS Code sessions using Agent Host. Local sandboxes give developers a secure execution boundary for agentic workflows on their own machines. Tools and commands initiated by Copilot run with restricted access to the filesystem, network, credentials, and other system capabilities, based on policies defined by the developer or their organization. Local sandboxing is powered by Microsoft eXecution Container (MXC), which translates a common sandbox policy into native operating-system controls across Windows, macOS, and Linux. With local sandboxing, developers and organizations can: Limit the files and directories that agent-run commands can read or modify. Control access to the internet, local networks, Git credentials, and GitHub CLI credentials. Apply sandboxing to local tools and services, including local MCP and language servers where supported. Use enterprise-managed settings to require sandboxing and enforce policies that developers cannot weaken. Adopt more autonomous agent workflows while maintaining clear boundaries around what Copilot can access. Model execution and tool isolation are separate concerns. Sandbox policies apply to tool execution regardless of which model Copilot uses. Local sandboxing is included with GitHub Copilot at no additional cost. To get started, see About cloud and local sandboxes for GitHub Copilot.

GitHub Copilot CLI makes it easier to choose a local model without leaving your existing workflow. Starting in CLI version 1.0.94-0, use /model to discover supported models from a running local Ollama instance, alongside your configured models and cloud models provided by GitHub Copilot. Discovery doesn’t automatically add models. Choose a discovered model, review its provider and endpoint, then confirm Add and use for this session or Add without switching. You can use the model in your current session without restarting the CLI. Ollama and the model must already be installed—this flow doesn’t install a runtime or download models. Models must support tool calling and streaming. Provider connection failures appear in the picker with an explanation, helping you identify what needs attention. This CLI update builds on the same idea as the GitHub Copilot app’s provider experience: choose the model that fits your work. In the app, add a supported provider in Settings > Model providers. Choosing a local model doesn’t turn on offline mode or disable GitHub telemetry. In the CLI, offline mode remains an explicit choice through COPILOT_OFFLINE=true. A remote provider can still receive prompts and code context over the network, even in offline mode. Follow the CLI provider and offline-mode documentation for configuration and limits. We’re also announcing intelligent routing with local models. Read the announcement on the Microsoft Command Line blog and stay tuned for availability. Learn more about setting up your own model provider in the GitHub Copilot app.

If your Copilot usage metrics have shown agent activity or agent lines of code falling while Copilot usage kept growing, we’ve found the cause, and a fix is rolling out to each IDE. Several IDEs recently moved Copilot agent sessions to the Copilot SDK. Those sessions didn’t identify which IDE they came from, so usage metrics couldn’t attribute them correctly. Most of that activity was left out of reports, and some was counted as Copilot CLI activity. Only IDE versions that use the Copilot SDK for agent mode are affected. Developers on earlier versions are still counted. The fix is available now in Visual Studio Code. Other IDEs will receive it in upcoming releases, which we expect to finish rolling out by November 2026. Once developers update, their agent activity is counted again in the Copilot usage metrics dashboard and API. Update your IDE Agent activity is counted again once developers are on these versions. If your developers are on an affected version, update as soon as the fixed version is available, because their activity can’t be recovered later. If you manage IDE versions centrally and rely on agent metrics, you can plan your rollout to move developers directly to these versions. IDE Version Availability Visual Studio Code 1.139.0 and later Available now Visual Studio 18.12 Not yet released, expected in October 2026 JetBrains IDEs Next plugin release Not yet released, expected by late October 2026 Eclipse Next plugin release Not yet released, expected by November 2026 Xcode Next plugin release Not yet released, expected by November 2026 We’ll add each version to the supported IDEs in the docs as it ships. What to expect in your reports Billing isn’t affected. This issue only changed how agent activity was attributed in usage metrics, not what you were charged. The gap persists for any developer on an affected IDE version until they update. Until then, their agent interactions and agent lines of code (e.g., loc_added_sum and loc_deleted_sum for agent_edit) stay undercounted. This applies to enterprise, organization, and user reports, for both 1-day and 28-day reports. We can’t backfill missing data. Activity from affected IDE versions doesn’t identify which IDE it came from, so it can’t be attributed after the fact. Expect a gradual recovery as developers move to these versions rather than a single jump. Copilot CLI metrics may be inflated, because some activity from other SDK-based clients was counted as Copilot CLI activity. This will clear up as developers update those clients, but earlier Copilot CLI metrics can’t be corrected, because that activity can’t be separated from real Copilot CLI use. Copilot CLI users don’t need to update. Why client-side metrics can differ from other Copilot data Most detailed usage metrics (e.g., feature, language, model, and lines of code breakdowns) come from telemetry that each IDE sends. GitHub also records server-side data when Copilot handles a request. That data reliably shows who was active, but it can’t see what happens in the editor. When your reports and other Copilot data disagree, the gap is usually on the client side: Telemetry is turned off in the IDE, so no detailed activity is sent. A network proxy or firewall blocks the Copilot telemetry endpoint. The IDE or Copilot extension is out of date and doesn’t send the events that metrics rely on. The client changed how it sends telemetry, as with the Copilot SDK change above. The client doesn’t send Copilot telemetry, such as an unsupported or third-party editor. We’re steadily reducing how much your reports depend on client telemetry. Usage metrics now use server-side data to count active users that client telemetry misses and to identify the IDE for those users, and we’re continuing to expand where server-side data can fill in. Some detail, such as lines of code and accepted suggestions, can only come from the editor, so client-side gaps won’t disappear entirely. The most reliable way to keep your metrics complete is to manage your developers’ environments: Keep IDEs and Copilot extensions current. Use your device management tooling to enforce minimum versions where you can. Keep IDE telemetry enabled and allow the Copilot telemetry endpoint through proxies and firewalls. Spot outdated clients in your reports. In per-user reports, totals_by_ide includes last_known_ide_version and last_known_plugin_version for each user. To learn how usage metrics combine client-side and server-side telemetry, see Which usage is included? in the Copilot usage metrics documentation.

You can now request a GitHub Copilot code review through the REST and GraphQL APIs and set the review effort level for each request. Balanced is also now the default review effort level. These changes are generally available to Copilot Pro, Pro+, Max, Business, and Enterprise plans. 🔌 Request Copilot code review with the API You can now request a review from Copilot using the supported REST and GraphQL APIs. When you make a request, you can optionally set the review effort level for that review. This lets you bring Copilot code review into your own scripts, workflows, and internal tools, so reviews can start from the systems your team already uses. ⚖️ Balanced is now the default review effort level As announced on August 28, 2026, the Default review effort level now uses Balanced for new and existing repositories and organizations using Copilot code review. If you explicitly selected Lite in your settings, that selection was respected. This change took effect September 28, 2026. ⚙️ Configure your review effort level If you prefer Lite or want to try out the options available to you, you can change the review effort level from Default to Lite at the level you manage: Enterprise: In your enterprise settings, go to AI controls → Agents → Copilot code review. Organization: In your organization settings, go to Copilot → Code review. Repository: In your repository settings, go to Copilot → Code review. Personal: Click your profile picture, then go to Copilot settings → Copilot → Code review. Each level can override the one above it. For step-by-step instructions, see Configuring code review by GitHub Copilot.

As of today, October 2, 2026, we have deprecated the following models across all GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions). Model Deprecation date Suggested alternative Gemini 3.5 Flash 2026-10-02 Gemini 3.8 Flash Gemini 3.6 Flash 2026-10-02 Gemini 3.8 Flash Kimi K2.7 Code 2026-10-02 Kimi K3 Claude Opus 4.7 2026-10-02 Claude Opus 5.5 Please update your workflows and integrations to use supported models. Copilot Enterprise administrators may need to enable access to alternative models through their model policies in Copilot settings. As an administrator, you can verify availability by checking your individual Copilot settings and confirming that the policy is 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. No action is required to remove the deprecated models. GitHub Enterprise customers with questions or concerns are encouraged to reach out to their account manager for further assistance. Share your feedback To learn more about the models available in Copilot, see our documentation on models and get started with Copilot today. Join the GitHub Community to share your feedback.