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Sakana AI's new Fugu Max and Ultra v2 models represent a significant evolution in multi-agent orchestration by dynamically routing tasks to cost-effective or high-capability specialized models via a unified API. This approach optimizes the Pareto frontier between performance and expense, allowing developers to avoid over-provisioning expensive foundation models for simple queries while maintaining robustness on complex workflows. The release underscores a shifting industry focus toward efficient agentic systems that leverage diverse model pools rather than relying solely on monolithic architectures.

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Sakana AI Launches Fugu Max and Fugu Ultra v2 for Cheaper, Stronger Multi-Agent Orchestration

MarkTechPostSeptember 11, 20264 min read

Sakana AI has released Fugu Max and Fugu Ultra v2, 2 models built on the same learned orchestration architecture. Fugu Max routes tasks to lean open and specialized models, including NVIDIA Nemotron, at $2/$6 per 1M tokens. Fugu Ultra v2 targets peak capability, scoring 48.3 on Chartography and 74.3 on DeepSWE. The post Sakana AI Launches Fugu Max and Fugu Ultra v2 for Cheaper, Stronger Multi-Agent Orchestration appeared first on MarkTechPost.

Sakana AI has released Fugu Max and Fugu Ultra v2, 2 new models in its Sakana Fugu family. Fugu is not a single foundation model. It is a learned orchestrator that routes work across a pool of other models behind 1 API. The new release tunes that architecture for 2 missions. Fugu Max targets the best output per dollar. Fugu Ultra v2 targets…

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