“Too dangerous to release” or just too expensive?

“Too dangerous to release” vs marketing narrative

• Many commenters see the “too dangerous to release” framing as a recycled marketing move (compared to GPT‑2/3 era messaging).
• Some argue it conveniently hides either modest capability gains or uneconomical serving costs while preserving a mystique.
• Others think Anthropic leadership likely does believe in substantial cyber risk, even if the messaging is overdramatized.

Cost, compute, and business incentives

• Strong view that Anthropic is compute‑constrained and Mythos is expensive to run; safety is seen as a useful excuse to limit access.
• Pricing details (Mythos vs Opus, preview pricing, free credits) lead some to doubt it’s vastly superior; others note larger models naturally cost more.
• Several see the timing and framing as IPO / enterprise‑sales driven hype and a way to lock in large contracts.
• There is suspicion about protecting IP and slowing competitors’ ability to distill or train on Mythos outputs.

How capable is Mythos really?

• On cyber vulns, views diverge sharply:
  • One camp says Mythos is only incrementally better than other frontier models; evidence cited includes limited new findings on well‑audited projects (e.g., curl) and similar performance from other LLMs given enough compute.
  • Another camp reports “revolutionary” results on very large proprietary codebases, with thousands of real bugs and design flaws uncovered, far beyond prior tools.
• Some emphasize that even small gains in security‑bug discovery could materially change offensive capabilities.
• There’s debate whether Mythos is just “a bigger model on the scaling curve” versus a meaningful qualitative shift; unclear from public data.

Safety, risk, and governance

• Concerns span offensive cyber use, possible bio‑risk, and the long‑tail of increasingly capable systems.
• Others counter that bioweapon barriers are dominated by regulation, logistics, and deterrence, not LLM access.
• Worries are raised that “safety” rhetoric could be weaponized against open‑weight models and used to entrench proprietary moats.
• A commenter from Anthropic states the bottleneck is safeguards for offensive cyber risks, not compute, and that Mythos‑class models are intended for broader deployment once controls exist; skeptics question what concrete safeguards mean.

Meta: quality of the article and ecosystem

• Many criticize the linked article as verbose, derivative, and likely LLM‑generated “slop,” though some found its cost‑focus illuminating.
• The thread also touches on HN “hug of death,” fragile WordPress hosting, and general fatigue with AI‑driven content and marketing.