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[Image: Chetan Jha\/MITSMR Middle East] <\/p>\n
Riding the current AI momentum, Japanese AI startup Sakana AI has unveiled Fugu, a multi-agent orchestration platform, which claims to surpass Anthropic\u2019s Claude Fable 5 on select coding and reasoning benchmarks.<\/p>\n For the uninitiated, instead of relying on a single large language model, orchestration models coordinate multiple AI agents, databases, and APIs to function seamlessly.\u00a0<\/p>\n \u200bThe company has launched two versions of the platform. The standard Fugu model is for everyday tasks like coding and chat, while Fugu Ultra is built for harder, more complex work.<\/p>\n \u201cToday, this orchestration is no longer just a technical optimization; it has become a geopolitical and operational imperative. Recent disruptions in the AI landscape have demonstrated the severe risk of single-vendor dependency. For an organization or a nation, relying on a single company\u2019s APIs for critical infrastructure, finance, or governance is a material vulnerability. This risk is no longer a hypothetical possibility, but a reality,\u201d\u00a0 the official release read<\/a>.<\/p>\n \u200bAccording to benchmark results shared by the firm, Fugu\u2019s value is most evident in long, messy, real-world workflows. The Fugu Ultra and the standard Fugu model achieved scores of 93.2 and 92.9 on LiveCodeBench, respectively. Anthropic\u2019s Claude Fable 5 recorded 89.8 while OpenAI\u2019s GPT 5.5 recorded the lowest figure of 85.3.<\/p>\n \u200bOther key benchmarks included GPQA-D, CharXiv Reasoning, SWEBench Pro, SciCode, Terminal Bench 2.1, and CTI-REALM.<\/p>\n \u200bNotably, the Humanity\u2019s Last Exam (text), an ultra-challenging academic AI benchmark consisting of 2,500 highly specific questions across more than 100 subject domains, had all participating models score between 44.3 and 53.3.<\/p>\n Fugu and Fugu Ultra both scored the highest of 95.5 on GPQA-Diamond, a benchmark of\u00a0 graduate-level multiple-choice questions used to test the limits of scientific reasoning.<\/p>\n \u201cOne of the clearest signals came from automated data science research: early users running Sakana Fugu in an almost fully automated research mode saw it drive meaningful progress with little to no human intervention,\u201d the release said.<\/p>\n Early users reported that Fugu Ultra outperformed GPT-5.5 in code review, citing its ability to catch bugs that other models missed and to deliver more comprehensive answers. Regarding security tasks, one user noted that Fugu completed a full end-to-end assessment without prompting\u2014staying within scope and avoiding destructive actions throughout.<\/p>\n Going forward, it will expand the pool of expert agents, including open models and Sakana AI\u2019s own models, to strengthen coordination for long-running and agentic tasks.<\/p>\n
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\n Japan’s Sakana AI Unveils Fugu, Claims Edge Over Claude Fable 5 in Coding
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