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OpenRouter (Aggregator)

Uses SSE streaming with OpenAI-compatible tool-calling format. Routes requests to any model from any provider through a single API key. OpenRouter is a model aggregator — a single API endpoint that proxies requests to Anthropic, OpenAI, DeepSeek, Qwen, xAI, Meta, Mistral, Google, and dozens more. One key, one billing account, access to everything. Best for: Experimenting with models you haven’t set up directly, unified billing, accessing niche models not yet natively supported by Wolffish.
We recommend configuring providers directly whenever possible. Direct integration gives you lower latency (no proxy hop), accurate cost tracking, provider-specific features (Anthropic’s ephemeral caching, DeepSeek’s FIM), and no middleman markup. OpenRouter adds a routing layer that can introduce latency and occasionally inconsistent behavior across providers.Use OpenRouter when you want to experiment with models you haven’t set up directly, or as a convenient fallback for providers where you don’t want to manage a separate API key.

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Getting an API Key

  1. Go to openrouter.ai
  2. Sign up or log in
  3. Navigate to Keys and create a new key
  4. Paste it into Wolffish → Settings → Models → OpenRouter

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Models

OpenRouter routes to hundreds of models across dozens of providers. The table below is a curated top-20 of the most popular models — the picker exposes many more once your key is connected:
This is a curated shortlist, not the full catalogue. OpenRouter exposes hundreds of models through one key — the picker lists many more than the popular ones shown here. Wolffish doesn’t track per-token cache discounts for routed models, so the Cached column is unavailable across the board.

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Direct Integration vs. OpenRouter

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When to Use OpenRouter

Good fit:
  • Trying models from providers you haven’t configured yet
  • Quick A/B testing across different model families
  • Unified billing when you only want one API bill
  • Accessing niche or newer models not yet natively supported
Use direct integration instead when:
  • The provider is already natively supported (DeepSeek, Anthropic, OpenAI, etc.)
  • You need the lowest possible latency
  • You want provider-specific features (caching, prompt prefixes, etc.)
  • You’re running high-volume production workloads where the proxy hop adds up
If you’re already using DeepSeek, Anthropic, or any other natively supported provider, keep that direct connection. Add OpenRouter only for models you can’t access directly — then select an OpenRouter model as your Brain when you want to use it. There’s no cascade; the model you select is the one that runs.

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Reasoning modes

How this model reasons is set in the model card beside the chat input — hover the model switch to preview the card, click to pin it open. The top chip row, labelled Thinking, is the control: pick a chip and it applies from your next message. Two separate ideas combine here:

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Thinking — whether the model reasons

  • Off — the model answers immediately. Fastest and cheapest; ideal for simple, direct tasks.
  • On (the chip reads Normal) — the model first works through the problem in a dedicated reasoning pass before replying. Slower and uses more tokens, but markedly more accurate on multi-step, logical, or ambiguous tasks.

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Effort — how hard it thinks

Only effort-capable models expose this; it applies once thinking is on.
  • High — standard reasoning depth. The right default for most agentic work.
  • Max — the model reasons longer and deeper for the hardest problems. More tokens and latency in exchange for higher quality on complex work.

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The chip row

The active chip is tinted; the rest sit quiet. Each model shows only the chips it genuinely supports — a model that always reasons has no Off, a model with a single mode shows that one chip inert, and a model that can’t reason at all replaces the row with “Reasoning is not supported by this model.” Wolffish remembers your choice per model. (Before v1.0.236 this was a colour-coded brain button on the composer; it moved into the model card, beside the Single/Workflow row, so every model knob sits in one panel.) On OpenRouter: Reasoning depends on the routed model. Reasoning-capable models show Off / High; non-reasoning models have no control. OpenRouter caps effort at High, and some endpoints (e.g. GPT-5, DeepSeek-R) reason mandatorily — there ‘Off’ falls back to minimal reasoning.

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Using OpenRouter as Your Model

There’s no provider cascade and no priority order. To use an OpenRouter model, select it as your Brain from the model switch beside the chat input (or let the master pick it for an agent in workflow mode). The model you select is the one that runs — OpenRouter is not an automatic fallback behind your other providers.