IDEs & editors

VS Code — built-in Chat

Add RouterPlex models to VS Code's built-in Chat via a custom endpoint.

VS Code's built-in Chat view can bring your own models through a *custom endpoint*. Add RouterPlex once and every model below shows up in the Chat model picker. The steps are the same on macOS, Windows, and Linux.

This is for VS Code's native Chat. For the Cline, Roo Code, and Continue extensions, see VS Code — Cline, Roo, Continue.

Add RouterPlex as a custom endpoint #

1. Open the Chat view, click the model dropdown, and choose "Manage Models…".

The Chat model picker, with "Manage Models…" at the bottom.
The Chat model picker, with "Manage Models…" at the bottom.

2. Click "Add Models", then choose "Custom Endpoint".

Add Models then Custom Endpoint in the Language Models panel.
Add Models then Custom Endpoint in the Language Models panel.

3. Name the group "RouterPlex" and press Enter.

Naming the model group RouterPlex.
Naming the model group RouterPlex.

4. Paste your RouterPlex API key and press Enter.

Pasting your RouterPlex API key.
Pasting your RouterPlex API key.

5. Choose "Chat Completions" as the API type.

Selecting the Chat Completions API type.
Selecting the Chat Completions API type.

6. VS Code opens chatLanguageModels.json — add one entry per model, then save.

Editing chatLanguageModels.json: id is the model ID, url is the RouterPlex API, and the token limits depend on the model.
Editing chatLanguageModels.json: id is the model ID, url is the RouterPlex API, and the token limits depend on the model.

That file lives at:

  • macOS: ~/Library/Application Support/Code/User/chatLanguageModels.json
  • Windows: %APPDATA%\Code\User\chatLanguageModels.json
  • Linux: ~/.config/Code/User/chatLanguageModels.json

7. Added the provider by editing the JSON directly? If you created the RouterPlex group by hand instead of the wizard above, VS Code doesn't have your key yet. Right-click the group in the Language Models list, choose Update API Key, and paste your RouterPlex key.

Right-click the model group and choose "Update API Key" to set your key.
Right-click the model group and choose "Update API Key" to set your key.

Example configuration #

Every model points url at RouterPlex (https://api.routerplex.com/v1). Add as many entries to models as you like:

json
[
{
"name": "RouterPlex",
"vendor": "customendpoint",
"apiKey": "${input:chat.lm.secret.-8cc97ea}",
"apiType": "chat-completions",
"models": [
{
"id": "claude-opus-4-8",
"name": "Claude Opus 4.8",
"url": "https://api.routerplex.com/v1",
"toolCalling": true,
"vision": true,
"maxInputTokens": 1000000,
"maxOutputTokens": 64000
},
{
"id": "qwen3.7-plus",
"name": "Qwen3.7 Plus",
"url": "https://api.routerplex.com/v1",
"toolCalling": true,
"vision": true,
"maxInputTokens": 1000000,
"maxOutputTokens": 128000
}
]
}
]

Leave apiKey as the ${input:…} placeholder VS Code generated in step 4 — it references the key you pasted, so you never store the raw key in the file.

Want all 28 models at once? Copy the complete chatLanguageModels.json, paste it into the file, and delete any you don't want.

Models #

Every entry uses "url": "https://api.routerplex.com/v1". Copy the id, maxInputTokens, and maxOutputTokens for each model you want:

Model IDMax input tokensMax output tokens
claude-opus-4-8100000064000
claude-opus-4-7100000064000
claude-opus-4-6100000064000
claude-sonnet-4-6100000064000
claude-haiku-4-525600064000
gpt-5.525600064000
gpt-5.41000000128000
gemini-3.1-pro1000000128000
gemini-3.5-flash1000000128000
deepseek-v4-pro1000000128000
deepseek-v4-flash1000000128000
kimi-k2.725600064000
kimi-k2.625600064000
qwen3.7-max1000000128000
qwen3.7-plus1000000128000
qwen3.6-plus1000000128000
glm-5.21000000128000
glm-5.125600064000
MiniMax-M31000000128000
MiniMax-M3-highspeed1000000128000
MiniMax-M2.719600064000
MiniMax-M2.7-highspeed19600064000
doubao-seed-2.0-pro12800032000
doubao-seed-2.0-code20000064000
mimo-v2.5-pro1000000128000
mimo-v2.51000000128000
mimo-v2-omni25600064000
step-3.7-flash25600064000

The Copy all button sets "vision" on the models that accept image input and "toolCalling": true on all of them — adjust either per model if you like. Give this key its own budget so editor usage is capped and shows up separately in your logs.