OpenRouter

OpenRouter puts one API key and one OpenAI-compatible endpoint in front of models from Anthropic, OpenAI, Google, Meta, DeepSeek, Qwen, Mistral, xAI and others. You switch models by changing the model id, with no new credential, and OpenRouter handles billing in one place.

Many models on OpenRouter are served by several upstream providers (Llama 3.3 70B, for example, by Groq, DeepInfra, Together and others). OpenRouter chooses one per request, and you can steer that choice for latency or data-handling requirements, as described in Provider routing.

Get credentials

1. Sign in at https://openrouter.ai.
2. Open Settings → API Keys (direct link: https://openrouter.ai/settings/keys).
3. Click Create Key, name it, and copy the sk-or-v1-... string.
4. Add credits under Settings → Credits. Requests fail with 402 when the balance runs out.

Configure in jambonz

In the portal: Account → LLM Services → + Add LLM Service → OpenRouter.

Click Test to verify. The test checks the key against OpenRouter’s authenticated key endpoint, so a wrong or revoked key fails here, not on the first call.

Use in an agent verb

Model ids are <org>/<model>:

session.agent({
  llm: {
    vendor: 'openrouter',
    model: 'anthropic/claude-haiku-5.5',
    llmOptions: {
      systemPrompt: 'You are a helpful voice assistant.',
    },
  },
  stt: { vendor: 'deepgram', language: 'en-US' },
  tts: { vendor: 'cartesia', voice: 'sonic-english' },
  turnDetection: 'krisp',
  bargeIn: { enable: true },
  actionHook: '/agent-complete',
}).send();

Available models

The portal’s model dropdown lists OpenRouter’s live catalog of text models. Any model id from openrouter.ai/models works. Common picks for voice agents:

Provider routing

By default OpenRouter routes each request mainly by price, skipping providers that have had a recent outage. For voice, latency usually matters more than price.

Quickest option: a model suffix. Append :nitro to any model id to route by throughput, or :floor to route by price:

llm: { vendor: 'openrouter', model: 'meta-llama/llama-3.3-70b-instruct:nitro' }

Full control: llmOptions.vendorParams. Anything in vendorParams is added to the request sent to OpenRouter, so you can use OpenRouter’s provider routing and model fallbacks directly:

llm: {
  vendor: 'openrouter',
  model: 'meta-llama/llama-3.3-70b-instruct',
  llmOptions: {
    systemPrompt: 'You are a helpful voice assistant.',
    vendorParams: {
      provider: {
        sort: 'latency',          // fastest host first
        data_collection: 'deny',  // skip hosts that store or train on prompts
        require_parameters: true, // only hosts that support every parameter sent, such as tools
      },
      models: ['openai/gpt-4.1-mini', 'google/gemini-3.5-flash'], // fallbacks if the primary model fails
    },
  },
}

Useful provider fields:

Reasoning

Some models think before answering by default, which adds latency to every turn. OpenRouter’s reasoning parameter controls this across vendors:

llmOptions: {
  vendorParams: { reasoning: { effort: 'minimal' } },  // or 'none' for OpenAI GPT-5 models
}

In our tests google/gemini-3.5-flash spent 381 tokens thinking by default, took ~2.5 s to its first token, and ran out of a 400-token budget before finishing its answer. With effort: "minimal" it used no thinking tokens and reached its first token in ~1.0 s. openai/gpt-5.4-mini with effort: "none" reached its first token in ~0.7 s versus ~2.2 s at "high".

Prompt caching

For anthropic/... models, jambonz turns on OpenRouter’s automatic prompt caching, so long system prompts are cached after the first turn. OpenAI-family and Gemini models cache automatically on the provider side. Cached tokens are reported in the agent’s per-turn LLM usage.

Quirks & errors