OrcaRouter

OrcaRouter is an OpenAI-compatible meta-router that provides a single endpoint for OpenAI, Anthropic, Google, DeepSeek, Grok, Qwen, MiniMax, Kimi, and other upstreams. It also offers an adaptive orcarouter/auto virtual router whose strategy (cheapest, balanced, quality, adaptive, gated_adaptive) is configured per workspace from the routing console.

OrcaRouter follows the OpenAI API format — see the OpenAI provider documentation for shared request semantics.

Setup

1. Get your API key from OrcaRouter.
2. Set the ORCAROUTER_API_KEY environment variable, or specify apiKey in your config.

Popular models

OrcaRouter's full live catalog is at orcarouter.ai/models. A few common IDs:

Basic Configuration

# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
providers:
  - id: orcarouter:openai/gpt-4o-mini
    config:
      temperature: 0.7
      max_tokens: 1000

  - id: orcarouter:anthropic/claude-opus-4.7
    config:
      max_tokens: 2000

  - id: orcarouter:orcarouter/auto
    config:
      max_tokens: 1000

If you route OrcaRouter traffic through a proxy or compatible gateway, set apiBaseUrl in the provider config. Precedence is config.apiBaseUrl → the hardcoded OrcaRouter default (https://api.orcarouter.ai/v1). The generic OpenAI base URL env vars are not consulted for this provider.

The same pattern applies to apiKeyEnvar — set it to read your API key from a custom environment variable name (default ORCAROUTER_API_KEY).

providers:
  - id: orcarouter:openai/gpt-4o-mini
    config:
      apiBaseUrl: https://proxy.example.com/orcarouter/v1
      apiKeyEnvar: MY_PROXY_KEY # optional: read the Bearer token from $MY_PROXY_KEY

Adaptive routing with orcarouter/auto

orcarouter/auto is a virtual router (not a model) — invoke it as orcarouter:orcarouter/auto. OrcaRouter seeds each workspace with an auto router whose strategy and candidate model pool are configured in the routing console. The same /chat/completions endpoint is used; OrcaRouter selects the upstream per request.

You can also pass a models fallback list and a route mode for hard-failover behavior:

providers:
  - id: orcarouter:openai/gpt-4o
    config:
      route: fallback
      models:
        - openai/gpt-4o
        - anthropic/claude-haiku-4.5
        - google/gemini-2.5-flash

When route: fallback and the primary upstream errors out, OrcaRouter walks the models list in order.

:::note OrcaRouter's own docs show fallback configuration as extra_body: { models, route } because they're written for the OpenAI Python SDK, which merges extra_body into the wire request. In promptfoo's YAML, write models and route directly at the provider config level — the provider promotes them to top-level body fields for you. :::

Thinking / Reasoning Models

Reasoning-capable models (Anthropic Claude Opus, OpenAI GPT-5 family, DeepSeek Reasoner, Gemini reasoning previews, etc.) may return a reasoning field alongside content. By default, promptfoo prefixes the reasoning content as Thinking: ...\n\n<actual response>. Hide it with showThinking: false:

providers:
  - id: orcarouter:anthropic/claude-opus-4.7
    config:
      showThinking: false # Hide thinking content from output (default: true)

:::note Several reasoning families reject temperature outright: anthropic/claude-opus-4.x+, OpenAI gpt-5* and o-series, and deepseek/deepseek-reasoner / deepseek-r1. The provider strips temperature from outbound requests for these models — both the default temperature: 0 and any explicit value in your config — so the field never reaches the upstream and you do not need to remember to omit it yourself. For other vendors' reasoning previews not on this list, use omitDefaults: true or set temperature: undefined to suppress the default. :::

Features

• Access to OpenAI, Anthropic, Google, DeepSeek, Grok, Qwen, Kimi, MiniMax, and other upstream providers through one endpoint.
• Adaptive workload-aware routing via orcarouter/auto with strategies tunable from the console (no client redeploy required).
• Explicit fallback chains using models + route: fallback.
• OpenAI-compatible request/response format — works with all standard promptfoo features (assertions, multi-prompt, multimodal where the underlying model supports it).