Sakana AI's Fugu Ultra Beats Frontier Models by Coordinating Them

Sakana AI just made Fugu Ultra available on OpenRouter, extending access to what may be the most interesting architectural bet in AI right now: a relatively small model whose entire job is to coordinate other, larger models. The result, according to benchmarks, is frontier-level performance , without ever training a frontier model.

One API, a whole team behind it

Sakana Fugu is a new product that delivers a full multi-agent orchestration system as a single foundation model. Fugu dynamically orchestrates the world's best models to tackle complex, multi-step tasks, accessible through a single model API. From your code's perspective, you're talking to one endpoint. Behind the scenes, a coordinated team of specialist models is doing the actual work.

Instead of training a new frontier model from scratch, Sakana trained a 7-billion-parameter orchestrator whose job is to decide which external model should handle each part of a problem. It can call a pool of third-party systems, delegate sub-tasks, check outputs, and synthesize one answer through an OpenAI-compatible endpoint.

Sakana Fugu is itself a language model trained to call various LLMs in an agent pool, including instances of itself recursively. That recursive self-calling is key: the orchestrator can spawn sub-orchestrators for deeply nested tasks, not just hand off to a flat list of specialists.

Two tiers, one integration

Sakana Fugu comes in two models , Fugu and Fugu Ultra , both available through one OpenAI-compatible API. Pick the model that fits your workload, or switch between them without changing your integration.

• Fugu: Balances strong performance with low latency, making it a great default for everyday work. It fits naturally into tools like Codex for coding and code review, as well as chatbots and other interactive services. For teams with data, privacy, or compliance requirements, Fugu also lets you opt specific agents out of its pool.