VS Code 로컬 AI 지원 추가...하지만 유료 플랜 필수

AI language models in VS Code Visual Studio Code offers different built-in language models that are optimized for different tasks. You can also bring your own language model API key to use models from other providers. For background on how language models work and their key characteristics, see Language models concepts . This article describes how to change the language model for chat or inline suggestions and how to use your own API key. Choose the right model for your task By default, chat uses a base model to provide fast, capable responses for a wide range of tasks, such as coding, summarization, knowledge-based questions, reasoning, and more. However, you are not limited to using only this model. You can choose from a selection of language models , each with its own particular strengths. As a general guideline, use a fast model for quick edits and simple questions, and a reasoning model for complex refactoring, architectural decisions, or multi-step tasks. For a detailed comparison, see Choosing the right AI model for your task in the GitHub Copilot documentation. Depending on the agent you are using, the list of available models might be different. For example, in agent mode, the list of models is limited to those that have good support for tool calling. Note If you are a Copilot Business or Enterprise user, your administrator needs to enable certain models for your organization by opting in to Editor Preview Features in the Copilot policy settings on GitHub.com. Change the model for chat conversations Use the language model picker in the chat input field to change the model that is used for chat conversations and code editing. Tip Install the AI Toolkit extension to add more language models to enhance GitHub Copilot capabilities. For more information, see Change the chat model . You can further extend the list of available models by using your own language model API key . If you have a paid Copilot plan, the model picker shows the premium request multiplier for premium models. Learn more about premium requests in the GitHub Copilot documentation. Configure thinking effort Some models support configurable thinking effort. Thinking effort controls how much reasoning the model applies to each request. Use a higher effort level for complex tasks like architectural decisions or multi-step debugging, and a lower level for straightforward code generation or simple questions. For background on how thinking and reasoning work, see Thinking and reasoning . VS Code sets recommended default effort levels based on evaluations and online performance data, and has adaptive reasoning enabled. Adaptive reasoning lets the model dynamically determine when and how much to think based on the complexity of each request. For most use cases, the defaults work well and you don't need to change them. You can configure the thinking effort directly from the model picker: Open the model picker in the chat input field and select a reasoning model. Select the > arrow that appears next to the model name to open the Thinking Effort submenu. Note Non-reasoning models, such as GPT-4.1 and GPT-4o, do not show the thinking effort submenu. Select an effort level. The model picker label updates to show the selected effort level, for example "Claude Sonnet 4.6 · High". The effort level persists across conversations for the same model. Note The github.copilot.chat.anthropic.thinking.effort Open in VS Code Open in VS Code Insiders and github.copilot.chat.responsesApiReasoningEffort Open in VS Code Open in VS Code Insiders settings are deprecated. You should configure thinking effort directly via the language model picker. Auto model selection Note Auto model selection is available as of VS Code release 1.104. With auto model selection, VS Code automatically selects a model to ensure that you get the optimal performance and reduce rate limits due to excessive usage of particular language models. It detects degraded model performance and uses the best model at that point in time. We continue to improve this feature to pick the most suitable model for your needs. To use auto model selection, select Auto from the model picker in chat. Currently, auto chooses between Claude Sonnet 4, GPT-5, GPT-5 mini and other models. If your organization has opted out of certain models , auto will not select those models. If none of these models are available or you run out of premium requests, auto will fall back to a model at 0x multiplier. Important Starting April 20, 2026 , new sign-ups for Copilot Pro, Copilot Pro+, and student plans are temporarily paused. Additionally, we are tightening weekly usage limits. If you hit a weekly limit and you have premium requests remaining, you can continue using Copilot with auto model selection. See GitHub Copilot usage limits . Multiplier discounts When using auto model selection, VS Code uses a variable model multiplier , based on the selected model. If you are a paid user, auto will apply a request discount. At any time, you can see which model and model multiplier are used by hovering over the chat response. Manage language models You can use the language models editor to view all available models, choose which models are shown in the model picker, and add more models by adding from built-in providers or from extension-provided model providers. To open the Language Models editor, open the model picker in the Chat view and select Manage Models or run the Chat: Manage Language Models command from the Command Palette. The Language Models editor opens by default in a modal overlay on top of the editor area. The editor lists all models available to you, showing key information such as the model capabilities, context size, billing details, and visibility status. By default, models are grouped by provider, but you can also group them by visibility. You can search and filter models by using the following options: Text search with the search box Provider: @provider:"OpenAI" Capability: @capability:tools , @capability:vision , @capability:agent Visibility: @visible:true/false Customize the model picker You can customize which models are shown in the model picker by changing the visibility status of models in the Language Models editor. You can show or hide models from any provider. Hover over a model in the list and select the eye icon to show or hide the model in the model picker. Bring your own language model key Note If you are a Copilot Business or Enterprise user, your administrator can disable the Bring Your Own Language Model Key policy in the Copilot policy settings on GitHub.com. GitHub Copilot in VS Code comes with a variety of built-in language models that are optimized for different tasks. If you want to use a model that is not available as a built-in model, you can bring your own language model API key (BYOK) to use models from other providers. Using your own language model API key in VS Code has several benefits: Model choice : access hundreds of models from different providers, beyond the built-in models. Experimentation : experiment with new models or features that are not yet available in the built-in models. Local compute : use your own compute for one of the models already supported in GitHub Copilot or to run models not yet available. Greater control : by using your own key, you can bypass the standard rate limits and restrictions imposed on the built-in models. VS Code provides different options to add more models: Use one of the built-in model providers Install a language model provider extension from the Visual Studio Marketplace, for example, AI Toolkit for VS Code with Foundry Local Considerations when using bring your own model key Only applies to the chat experience and doesn't affect inline suggestions or other AI-powered features in VS Code. Capabilities are model-dependent and might differ from the built-in models, for example, support for tool calling, vision, or thinking. The Copilot service API is still used for some tasks, such as se