OpenRouter released Fusion, a new API that allows developers to combine multiple LLMs in a single API call. The standout: Fusion's default "DRACO" mode (a specific fusion strategy) beats Fable 5 on a range of benchmarks, at 40% of the cost.
The "multi-model fusion" idea: instead of choosing a single LLM, Fusion routes the request to multiple LLMs and combines their outputs. The combination strategy can be "voting" (majority vote), "blending" (weighted average of logits), or "cascading" (use the cheapest model first, escalate to a stronger one if needed). DRACO is a learned combination strategy, trained via RL.
The "one line of API" highlight: the developer writes a single API call, and Fusion handles the rest. The result is a "team of LLMs" that can outperform any single LLM, with a unified billing model. The API is compatible with OpenAI's API format, so existing applications can adopt Fusion with minimal code changes.
The benchmark: on the OpenRouter Fusion benchmark (a mix of MMLU, HumanEval, GSM8k, and a custom reasoning set), DRACO beats Fable 5 by 3.2 points, at 40% of the cost (because DRACO uses cheaper models for the easy parts and only escalates to expensive models for hard parts).
The bigger takeaway: "model fusion" is becoming a real product category. Just as "model routing" emerged in 2024 (route each request to the best LLM), "model fusion" is emerging in 2026 (combine multiple LLMs into a single output). For the industry, this signals that "the best LLM" is no longer a single model — it's a team of models, and Fusion is the first "team-as-a-service" product.