What this error means

Unknown tokenizer: undefined — Copilot Agent Mode fails for custom OpenAI-compatible models is a GitHub Copilot failure pattern reported for developers trying to fix github copilot agent mode failing with 'unknown tokenizer: undefined' for custom openai-compatible models. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue #314419 (37 comments) on microsoft/vscode reports Copilot Agent Mode failing with 'Unknown tokenizer: undefined' for custom OpenAI-compatible models via customoai provider. Normal chat completions succeed — issue is specific to Agent Mode. Affects VS Code Insiders 1.120.0 + Copilot 0.48.x.

Common causes

  • GitHub Copilot Agent Mode fails with 'Unknown tokenizer: undefined' when using custom OpenAI-compatible models (configured via chatLanguageModels.json), while normal chat completions work fine. Affects VS Code Insiders 1.120.0 users running custom LLM providers through local proxies.
  • GitHub issue #314419 (37 comments) on microsoft/vscode reports Copilot Agent Mode failing with 'Unknown tokenizer: undefined' for custom OpenAI-compatible models via customoai provider. Normal chat completions succeed — issue is specific to Agent Mode. Affects VS Code Insiders 1.120.0 + Copilot 0.48.x.

Quick fixes

  1. Confirm the exact error signature matches Unknown tokenizer: undefined — Copilot Agent Mode fails for custom OpenAI-compatible models.
  2. Check the GitHub Copilot account, local tool state, and provider configuration involved in the failing workflow.
  3. Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

  • Verify the command, editor, extension, or API client that produced the error.
  • Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
  • Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. Keep the working fix documented for the team or deployment environment.

How to prevent it

  • Keep provider/tool configuration documented.
  • Record non-secret diagnostics such as tool version, provider name, model name, and command path.
  • Add a lightweight check before CI or production workflows depend on the tool.