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Sakana AI's Fugu-Cyber demonstrates that specialized orchestration models can achieve state-of-the-art performance in both vulnerability verification and threat intelligence mapping, narrowing the gap with general frontier capabilities like GPT-5.5-Cyber while offering a distinct security-tuned endpoint within its existing architecture. The release highlights a strategic shift toward domain-specific agents for critical infrastructure tasks rather than relying solely on broad-purpose model scaling to solve complex cybersecurity reasoning problems.
Sakana AI Releases Fugu-Cyber: An Orchestration Model Reporting 86.9% on CyberGym and 72.1% on CTI-REALM
Sakana AI has released Fugu-Cyber, a security-tuned endpoint on its Fugu orchestration model. It reports 86.9% on CyberGym and 72.1% on CTI-REALM, edging past GPT-5.5-Cyber and Claude Mythos Preview. Access is gated behind manual approval, a defensive-use policy, and the Token Plan. Here is what the numbers actually mean. The post Sakana AI Releases Fugu-Cyber: An Orchestration Model Reporting 86.9% on CyberGym and 72.1% on CTI-REALM appeared first on MarkTechPost.
Sakana AI has released Fugu-Cyber (model ID is fugu-cyber-v1.0), a cybersecurity-specialized addition to its Fugu orchestration family. It is not just a new frontier model. It is a third endpoint on the Fugu orchestrator, tuned for security reasoning. Sakana launched that orchestrator a month earlier. Sakana reports a success rate of 86.9% on CyberGym and 72.1% on CTI-REALM. It describes those results as comparable to cyber-focused frontier models such as GPT-5.5-Cyber…
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