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Sakana Fugu is a frontier-level multi-agent orchestration model that dynamically coordinates a pool of specialized LLMs through a single OpenAI-compatible API. Instead of hand-crafting workflows, Fugu learns how to assemble, route, and synchronize expert agents to deliver stronger results on complex, multi-step tasks.
Built on research from the TRINITY and Conductor ICLR 2026 papers, Fugu uses evolved coordination strategies and reinforcement learning to unlock collective intelligence across coding, reasoning, math, and knowledge-intensive workloads. One request automatically leverages multiple agents with roles such as Thinker, Worker, and Verifier to improve reliability and depth of answers.
With Fugu, engineering and data teams can streamline integration while maintaining strict governance. You can control which underlying models participate, opt out of specific providers to satisfy privacy or compliance requirements, and optimize cost-performance without managing multiple APIs. Fugu and Fugu Ultra variants give you flexible performance tiers for quality-critical workflows.
Use Sakana Fugu to embed multi-agent intelligence directly into product features, internal tools, and automated pipelines. From robust code generation and refactoring to advanced analytical reasoning, Fugu provides a single, research-driven interface to orchestrated LLM ecosystems that outperform individual models on challenging benchmarks.
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