To use a local coding model in VS Code, install a model runtime such as Ollama, download a compatible model, and add Ollama’s official VS Code extension as a language-model provider. Then select the model in VS Code’s chat picker. The setup enables local chat without a Copilot plan, but it does not replace every Copilot feature: inline suggestions and semantic search still rely on GitHub Copilot services.
Use Ollama’s official extension for VS Code chat
VS Code’s built-in Ollama provider is deprecated. Microsoft recommends installing the official Ollama extension from the Visual Studio Marketplace instead. These steps describe the current provider-based route for using an Ollama model in VS Code chat.
- Install Ollama and download a model. Follow Ollama’s installation instructions, then download a model supported by the runtime. You can use the command pattern
ollama pull <model-name>, replacing the placeholder with the model’s actual name. The model must be available locally before you can use it. - Open the language-model management screen. In VS Code’s Chat view, open the language model picker and select Manage Language Models. Alternatively, open the Command Palette and run Chat: Manage Language Models.
- Install the Ollama provider extension. Choose Install Model Providers, or open Extensions and search for
@tag:language-models. Install the extension published by Ollama, then follow its setup flow. - Select the model and test it. Choose your local model from the chat model picker and try a small coding request. If the model or provider does not appear, check the troubleshooting section below.
Microsoft’s VS Code language-model documentation describes provider setup and BYOK use. The recommendation to use Ollama’s extension rather than the deprecated built-in provider appears in the VS Code 1.127 release notes.
When to use Foundry Toolkit instead
Foundry Toolkit for VS Code is an alternative for exploring, testing, and managing models. It supports local sources including Ollama, Foundry Local, and ONNX, as well as hosted sources. It is not required just to make an Ollama model available in VS Code chat; use the Ollama provider extension above for that simpler goal.
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- Install Ollama and download the model you want to try. Foundry Toolkit’s Ollama integration works with models already downloaded in Ollama.
- In Foundry Toolkit, choose Add Ollama Model, acknowledge the third-party provider notice, and select an installed model. The toolkit also supports configuring a custom Ollama endpoint.
- Use the toolkit’s model catalog or playground workflow to experiment. Microsoft’s documentation notes that attachments are not supported for Ollama in this integration.
See Microsoft’s Foundry Toolkit model documentation for its supported setup flow.
What a local model does—and does not—replace
VS Code’s bring-your-own-model (BYOK) support lets you use a configured local model for chat without a GitHub account or Copilot plan. Once the local model and provider are set up, chat can work offline. The scope is important: using a local model for chat does not make every AI feature local.
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- Chat: Available through the configured local provider, subject to the model and provider’s capabilities.
- Utility tasks: VS Code documents
chat.utilityModelandchat.utilitySmallModelsettings for directing supported tasks, such as generating a title or commit message, to a local model. - Inline suggestions and semantic search: BYOK models do not provide these features. They continue to depend on GitHub Copilot services; embedding-based features are not supplied by BYOK.
- Agent workflows and richer inputs: Tool calling, vision, and other capabilities vary by model and provider. Verify that both support what your workflow needs before relying on them. Availability can also differ by harness.
Microsoft explains these distinctions in its documentation on AI language models in VS Code and model capabilities and BYOK.
Choose the route that matches your work
| Need | Ollama extension | Foundry Toolkit |
|---|---|---|
| Use a local model in VS Code chat | Direct provider route: install the official extension and choose a model in the chat picker. | Can be used for model experimentation, but is not required for chat-provider setup. |
| Browse or experiment with models | Focused on connecting Ollama to VS Code’s language-model workflow. | Provides model discovery and playground workflows, including local and hosted sources. |
| Use a model already downloaded in Ollama | Install and set up the provider, then select the model. | Choose Add Ollama Model and select a model installed in Ollama. |
| Use a custom Ollama endpoint | Not established in the cited VS Code provider instructions. | Supported by the toolkit’s Ollama workflow. |
| Use attachments with Ollama | Not stated in the cited provider documentation. | Attachments are not supported in the Ollama integration, according to Microsoft’s toolkit documentation. |
| Get inline suggestions or semantic search from the local model | Not provided through BYOK; these depend on Copilot services. | Not provided through BYOK; these depend on Copilot services. |
Troubleshoot common setup problems
Ollama is missing from the provider list
Confirm that the installed extension is the official Ollama-published VS Code extension and complete its setup flow. Do not rely on VS Code’s deprecated built-in Ollama provider.
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Foundry Toolkit shows no Ollama models
The toolkit lists models already downloaded in Ollama. Pull the model into Ollama first, then return to Add Ollama Model.
Chat works, but VS Code features still need an online service
That is expected for features such as inline suggestions and semantic search, which BYOK does not supply. Local chat can work offline after setup; Copilot-service-dependent capabilities remain separate.
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An agent workflow cannot use a tool or input
Check the capabilities of the particular model and provider, including tool calling or vision if relevant. Support varies, so the fact that a model appears in the picker does not establish that it can perform every agent task.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to check before choosing a model
There is no universal memory, disk, or GPU minimum established by the cited setup documentation. Requirements and compatibility depend on the model and runtime, so check the selected model’s own requirements rather than assuming one local configuration fits all.
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- Does the model provide the coding quality and context capacity your tasks require?
- Does the provider expose tool calling or other capabilities needed for your intended chat or agent workflow?
- Are you setting up chat, utility tasks, or agent tools? They do not all use a local model in the same way.
- Is offline chat sufficient, or do you need Copilot-service features such as inline suggestions?
- If using Foundry Toolkit, does its workflow support the inputs you need? Its documented Ollama integration does not support attachments.
Microsoft’s model guidance describes capabilities as dependent on the model and workflow; compare the requirements for your specific choice.
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