Add Opencode Model

Add OpenCode Zen Model

Fetches model details from both OpenCode and OpenRouter APIs to provide structured information for the agent to add the model to source/models/opencode-zen-provider.ts.

Usage

# Get details for a specific OpenCode model
{baseDir}/add-model.js google/gemini-3-flash-preview

How It Works

1. Confirms model exists in OpenCode API (https://opencode.ai/zen/v1/models)
2. Searches OpenRouter API (https://openrouter.ai/api/v1/models) for matching model to get:
   • Context window length
   • Max output tokens
   • Pricing information
   • Supported features (reasoning/tool calling)
3. Determines client type based on model provider:
   • openai → uses @ai-sdk/openai (Responses API)
   • google → uses @ai-sdk/google (custom base URL)
   • anthropic → uses @ai-sdk/anthropic
   • openai-compatible → uses createOpenAICompatible
4. Outputs JSON with all details needed to add the model

JSON Output Format

The script outputs a JSON object wrapped in markers:

--- MODEL_DETAILS_JSON_START ---
{...}
--- MODEL_DETAILS_JSON_END ---

JSON Structure

{
  "modelKey": "gemini-3-flash-preview",
  "opencodeId": "google/gemini-3-flash-preview",
  "openrouterId": "google/gemini-3-flash-preview",
  "providerFile": "./source/models/opencode-zen-provider.ts",
  "registryId": "opencode:gemini-3-flash-preview",
  "clientType": "google",
  "registryEntry": {
    "id": "opencode:gemini-3-flash-preview",
    "provider": "OpenCode",
    "contextWindow": 1048576,
    "maxOutputTokens": 65535,
    "defaultTemperature": 0.5,
    "promptFormat": "markdown",
    "supportsReasoning": true,
    "supportsToolCalling": true,
    "costPerInputToken": 0.0000005,
    "costPerOutputToken": 0.000003
  },
  "clientConfig": {
    "key": "gemini-3-flash-preview",
    "opencodeId": "google/gemini-3-flash-preview",
    "clientType": "google",
    "openrouterId": "google/gemini-3-flash-preview"
  },
  "modelInfo": {
    "opencodeId": "google/gemini-3-flash-preview",
    "opencodeName": "Gemini 3 Flash Preview",
    "openrouterId": "google/gemini-3-flash-preview",
    "openrouterName": "Google: Gemini 3 Flash Preview",
    "contextLength": 1048576,
    "maxCompletionTokens": 65535,
    "pricing": {...},
    "supportedParameters": [...]
  }
}

Client Type Reference

How to Add Model to Provider File

Step 1: Add client if needed

In source/models/opencode-zen-provider.ts, check if you need to add a new client based on clientType:

// For OpenAI models (Responses API)
import { createOpenAI } from "@ai-sdk/openai";
const openaiClient = createOpenAI({
  apiKey: process.env["OPENCODE_ZEN_API_TOKEN"] ?? "",
  baseURL: "https://opencode.ai/zen/v1",
});

// For Google models
import { createGoogle } from "@ai-sdk/google";
const googleClient = createGoogle({
  apiKey: process.env["OPENCODE_ZEN_API_TOKEN"] ?? "",
  baseURL: "https://opencode.ai/zen/v1/models/<model-id>",
});

Step 2: Add to opencodeZenModels object

Find the opencodeZenModels const object and add the new model entry in alphabetical order by key, using the appropriate client:

const opencodeZenModels = {
  "glm-4-7": completionsClient("glm-4.7-free"),
  "minimax-m2-1": messagesClient("minimax-m2.1-free"),
  // For OpenAI-compatible models:
  "new-model": completionsClient("provider/new-model"),
  // For Anthropic models:
  "claude-model": messagesClient("anthropic/claude-model"),
  // For Google models:
  "gemini-flash": googleClient("google/gemini-3-flash-preview"),
} as const;

Step 3: Add to opencodeZenModelRegistry object

Find the opencodeZenModelRegistry object and add the registry entry in alphabetical order by registryId:

export const opencodeZenModelRegistry: {
  [K in ModelName]: ModelMetadata<ModelName>;
} = {
  "opencode:glm-4-7": {
    id: "opencode:glm-4-7",
    provider: "opencode",
    // ... existing entry ...
  },
  // ... existing entries ...
  "opencode:new-model": {
    id: "opencode:new-model",
    provider: "opencode",
    contextWindow: 1048576,
    maxOutputTokens: 65535,
    defaultTemperature: 0.5,
    promptFormat: "markdown",
    supportsReasoning: true,
    supportsToolCalling: true,
    costPerInputToken: 0.0000005,
    costPerOutputToken: 0.000003,
  },
  // ...
};

Step 4: Validate changes

Run the project's validation commands:

npm run typecheck
npm run lint
npm run format

Field Mapping Reference

Matching Strategy

The script uses multiple strategies to find a matching OpenRouter model:

1. Direct key match: Match by model key (e.g., glm-4.7 matches glm-4.7)
2. Provider + name match: Match by provider prefix and model name (e.g., google/gemini-3-flash matches google/gemini-3-flash-preview)
3. Partial name match: Match by partial model name (fallback)

If no match is found, defaults are used for pricing and capability fields.

Default Value Inferences

Error Handling

• Validates model ID exists in OpenCode API
• Shows first 10 available OpenCode models if ID not found
• Warns if no matching OpenRouter model found
• Provides clear error messages with suggestions

Examples

# Add Google Gemini Flash
{baseDir}/add-model.js google/gemini-3-flash-preview

# Add OpenAI GPT model
{baseDir}/add-model.js openai/gpt-4o

# Add Anthropic Claude model
{baseDir}/add-model.js anthropic/claude-3-5-sonnet

# Add other provider model
{baseDir}/add-model.js deepseek/deepseek-v3