Sakana Fugu Technical Report

The idea is that intelligence is moving from the model to the system around it.

Fugu is an orchestrator reads the task, chooses which specialist model to use, and in the Ultra version can build small workflows where models critique, extend, or correct one another.

Most multi-model systems use simple rules, like ask 3 models and vote, or always send coding to 1 model and math to another.

Fugu is different because the manager is trained from data to learn which model is actually best for each kind of situation, including small details like “this looks like coding, but the hard part is debugging, so bring in the model that is better at debugging.”

The mechanism has 2 versions.

Regular Fugu is the fast version, where it reads the user’s request and quickly chooses 1 worker model from a pool, so the user experiences it like calling 1 model, but behind the scenes Fugu picked the model it thinks is best for that exact request.

Fugu-Ultra is the slower but stronger version, where it can create a small workflow, such as asking 1 model to solve, another model to check, another model to solve from a different angle, and then choosing the best model to combine the answers.

The special part is that the workflow is not fixed before the task starts, because Fugu-Ultra can design a different teamwork pattern for each question.

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Link – arxiv. org/abs/2606.21228