Sakana Fugu NEW

Sakana Fugu is a multi-agent orchestration model that dynamically coordinates a pool of specialist models through a single OpenAI-compatible API.It learns to assemble agent teams and assign roles (thinker, worker, verifier) to route multi-step workflows for tasks such as coding, reasoning, scientific analysis, and document review.

Two model options, fugu (balanced latency and performance) and fugu ultra (optimized for higher answer quality), can be selected or switched without changing integration.Administrators can control which providers or agents participate to meet data, privacy, and compliance requirements.

Research-driven coordination methods (Trinity and Conductor) enable learned orchestration and natural-language coordination strategies across diverse LLM pools.The system targets developers, data scientists, researchers, and security analysts who need automated multi-step workflows, code generation and review, experiment automation, and complex reasoning.

Technical reports and benchmark comparisons document the model’s behavior and performance across coding, reasoning, and scientific benchmark suites.

Key Features

• OpenAI-compatible single API for dynamically coordinating a pool of specialist models (multi-agent orchestration)
• Learned agent-team assembly and role assignment (thinker, worker, verifier) to route multi-step workflows
• Selectable model options (fugu and fugu ultra) that can be switched without changing integration
• Administrator controls to restrict or select providers/agents for data, privacy, and compliance requirements
• Research-driven coordination methods (Trinity and Conductor) enabling learned orchestration and natural-language coordination across diverse LLM pools

Use Cases

• Automate end-to-end software development workflows using Sakana Fugu, dynamically assembling specialist agents for requirement parsing, code generation, unit and integration testing, automated code review and patch generation, and opening pull requests with learned orchestration strategies and privacy-compliant routing
• Run reproducible scientific analysis pipelines using Sakana Fugu, composing data-prep, modeling, simulation and result-interpretation agents that coordinate multi-step workflows, generate reproducible notebooks and human-readable reports, and route sensitive datasets through privacy-compliant models
• Perform security and compliance audits using Sakana Fugu, orchestrating vulnerability scanning, threat modeling, automated exploit validation, remediation suggestion agents and compliance-report generation while assigning role-based agent routing and maintaining privacy-safe audit trails

Who is it for?

• Software developers
• Data scientists
• Research analysts
• Security analysts
• Project managers