Sakana AI’s Fugu orchestrates multiple LLMs to match Anthropic’s Fable and Mythos benchmarks
Japanese AI startup Sakana AI is launching Fugu, a system that coordinates multiple AI models on the fly to compete with leaders like Anthropic’s Fable 5. The approach also aims to cut dependence on any single AI provider.
Results were “fine” but fell short of Fable in practice. He demonstrates with his 3D simulation benchmark “Harbor Town”. X user @LLMJunky blew through his entire five-hour quota on the $20 plan with a single prompt. A ThreeJS coding task came back “notably worse than GPT 5.5” and needed seven or eight fix rounds before the game even ran. “Early impressions…not great,” he wrote. On Hacker News, developers gripe that the $200-a-month plan gets you less than three hours a week. The API is reportedly slow, and output quality isn’t close to Fable. Code reviews were a bright spot, though, roughly matching Opus 4.8 or GPT 5.5. Hamel Husain on X agrees it’s solid for code reviews but weaker on frontend work, calling it “a bit jagged in its abilities.” A head-to-head by X user Mark Santos on a Crossy Road clone shows Fugu Ultra finishing in 22 minutes at $7.32, way faster and cheaper than Opus 4.8 at 79 minutes and $37.85. But Santos liked the output less. Sakana AI’s sovereignty claim also drew pushback. The system still depends on whatever models sit in its pool, and Sakana uses proprietary models like Claude Opus for its benchmarks. Smart engineering can squeeze more out of AI models, but that’s nothing new. This so-called “harness engineering” plays a big role in agentic AI. Tokyo-based AI startup Sakana AI is launching Fugu, a system that dynamically coordinates multiple AI models to compete with leading systems like Anthropic’s Fable 5.
