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This article details OpenRouter Fusion, a compound inference system that orchestrates parallel responses from multiple models to synthesize a final output through a structured debate and judgment process. By trading speed and token efficiency for improved accuracy in complex reasoning tasks, this technology represents a significant advancement in multi-agent collaboration within the AI infrastructure landscape.
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OpenRouter Fusion: How It Works and When to Use It

OpenRouter9 min read

Fusion is our compound model. It turns one prompt into a short debate among several models: a panel answers in parallel, a judge maps agreement and disagreement, and the calling model writes the final answer. You trade some speed and tokens for quality. This is what it does, what it costs, and when to use it.

Fusion is our compound model. It takes one prompt and turns it into a short debate among several models. We send your prompt to a panel of expert models at once, and a judge compares every response so the calling model can write a single final answer. With Fusion, you trade some speed and tokens for quality. This page covers what Fusion does, what it costs, when it beats a single model, and when it doesn’t. What Fusion does. It gives a model access to a multi-model deliberation tool. A panel answers in parallel, a judge maps agreement and disagreement, and the calling model writes the final response. What it costs. An invoked Fusion call adds panel and judge completions. The default three-model panel costs roughly four to five times as much as one completion on the same prompt and often takes two to three times longer. When to use it. Use Fusion as a selective escalation path for complex research, expert critique, and decisions where an…

Excerpt shown under the publisher's RSS terms · 167 words · full text and figures are on the publisher's site

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