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[AI]

ANTHROPIC ADMITS OPUS 4.7 LAGS MYTHOS IN CAPABILITIES

AI DESKTHU, APR 16, 2026

Anthropic has acknowledged that its Opus 4.7 model is less capable than the upcoming Claude Mythos Preview, particularly in cybersecurity applications. The admission comes as the White House prepares government agencies to adopt Mythos.

Anthropic disclosed that Opus 4.7 represents a step backward compared to Mythos Preview across general capabilities and cyber skills, according to reporting from CNBC's Ashley Capoot. The statement underscores the significance of Mythos, which has drawn attention from early testers who describe it as a "potent" tool for cybersecurity work. Those with access to the model report sharp improvements over Anthropic's prior offerings. Meanwhile, the White House is moving quickly to integrate Mythos into government operations. A memo from the Office of Management and Budget (OMB) has notified Cabinet departments that protections are being established to allow federal agencies to begin using Mythos, according to Bloomberg. The setup suggests the administration views Mythos as sufficiently secure and valuable for sensitive government work. The OMB's proactive framework indicates coordination between Anthropic and federal leadership on deployment safeguards. Anthropic's candor about Opus 4.7's limitations is notable. Rather than positioning it as an incremental improvement, the company has been direct about where the newer model falls short. This transparency may signal confidence in Mythos's capabilities or reflect internal assessments about which product deserves institutional backing. The timing aligns with broader government interest in AI adoption. Federal agencies have been cautious about AI deployment but are under pressure to modernize. Mythos's cybersecurity strengths appear to have convinced the White House that structured access is warranted. Anthropologic's Mythos remains in preview status, meaning wider adoption will likely follow initial government testing. The OMB protections framework will be critical in determining how quickly federal agencies can operationalize the model for real work.

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