Sakana AI's Fugu is a trained orchestrator that learns to manage other models, moving coordination from code into weights

Sakana AI's Fugu is a trained multi-model orchestrator. It decides which models to call, how to assign roles, and how to verify results—no hand-coded rules. Two ICLR 2026 papers back it: TRINITY trains a sub-20K-parameter coordinator via evolutionary strategy, Conductor trains a 7B orchestrator via RL. Fugu Ultra scores 93.2 on LiveCodeBench, beating Fable 5's 89.8, but trails on SWE-Bench Pro and HLE. Sakana deliberately hides which models are called per request and their raw outputs, calling routing info proprietary. All data is self-reported with no independent third-party replication and no head-to-head against OpenRouter Fusion. The direction holds, but transparency is still missing.

Why it matters: Sakana AI turned multi-model orchestration from hand-coded rules into a trained capability, backed by two ICLR 2026 papers with concrete mechanisms. Score held back because the post doesn't disclose LiveCodeBench numbers or pricing, and the product just launched without commun...