Qwen Code

Qwen Code can call TokenHub models through the OpenAI compatible interface. Keep the official installation flow, then replace only the API key, Base URL, and model ID.

The TokenHub endpoint used by this guide is https://us-api.tokenhub.com/v1/chat/completions.

When to use it

Start in a small repository or test project. First ask the tool to read files, explain code, or produce a plan; only then enable edits, terminal commands, or agent automation.

Install or open the tool

Follow the official Qwen Code documentation to install or open the tool. If menus or command names differ, prefer the current official documentation.

For CLI tools, confirm the executable works before adding TokenHub credentials:

qwen --version

Prepare TokenHub credentials

Create a TokenHub API key and choose a model from the TokenHub model list that fits this tool.

export TOKENHUB_API_KEY="sk-..."

Keep the key in your local shell, IDE secret storage, or the secure API key field of the tool. Do not commit it to the repository.

Configure TokenHub persistently

Use the tool configuration file or settings page first. This avoids the common problem where a terminal sees the environment variable but the IDE, plugin, or new window does not.

Provider values

Field	Value
Provider	OpenAI Compatible or Custom
Base URL	`https://us-api.tokenhub.com/v1`
API Key	The value of `TOKENHUB_API_KEY`
Model	`qwen3-coder-plus` or another TokenHub model ID

Settings file locations

Field	Value
User config	`~/.qwen/settings.json`
Project config	`.qwen/settings.json`
Provider fields	`modelProviders.openai`, `security.auth.selectedType`, `model.name`

{
  "modelProviders": {
    "openai": {
      "protocol": "openai",
      "models": [
        {
          "id": "qwen3-coder-plus",
          "name": "TokenHub / qwen3-coder-plus",
          "baseUrl": "__API_BASE_URL__/v1",
          "envKey": "TOKENHUB_API_KEY"
        }
      ]
    }
  },
  "security": {
    "auth": {
      "selectedType": "openai"
    }
  },
  "model": {
    "name": "qwen3-coder-plus"
  }
}

If your installed version writes a slightly different schema, use its interactive setup first, then keep the same TokenHub values: Base URL, API key, and model ID.

If the tool separates chat, edit, apply, and fast models, use the same TokenHub model for the first test. Split models later by cost, latency, and reasoning strength.

Temporary environment variables for debugging

Use temporary variables only to confirm the key, network, and model name. After validation, move the same values into the persistent configuration above.

export TOKENHUB_API_KEY="sk-..."
export OPENAI_API_KEY="$TOKENHUB_API_KEY"
export OPENAI_BASE_URL="__API_BASE_URL__/v1"
export OPENAI_MODEL="qwen3-coder-plus"

Verify the connection

Test with a read-only prompt first, confirming that the model can read context without changing files. Then test edits, Apply, or agent tasks.

Read the project README and summarize it in three sentences. Do not modify any files.

After a successful prompt, check TokenHub request logs for model name, endpoint, token usage, and billing group.

Troubleshooting

Symptom	Fix
401 or authentication failure	Confirm `TOKENHUB_API_KEY` is valid and saved in the same terminal, IDE, or client profile.
404 or model not found	Use a model ID that exists in your TokenHub workspace and matches the selected protocol.
Wrong endpoint	Keep the Base URL exactly as shown. OpenAI-compatible tools usually need `/v1`; Claude-compatible tools usually do not.
Request timeout	Check network access to `https://us-api.tokenhub.com`, proxy settings, and workspace allowlists.
Tool uses another model	Recheck every chat, edit, apply, fast, and autocomplete model slot.

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