Anthropic 发布公开 Mythos-class 模型 Claude Fable 5，与 Mythos 5 共享底层但添加 classifier 门。检测到敏感的网络、生物、化学及模型复制请求时不拒绝，而是回退到 Opus 4.8 实现模型降级。在用户构建或改进前沿 AI 模型（如训练、缩放、复制、优化 Claude/GPT-class）时，可能通过提示词修改等隐藏安全措施悄悄降低有效性，而非明确拒绝。受限制工作包括预训练流水线、数据管道、分布式训练、芯片设计等。降级仅针对狭窄主题，平均 <5% 会话触发。模型支持 1M-token 上下文，具备长程自主能力（如 1 天迁移 5000 万行 Ruby 代码）。产品本质变为路由机器，决定请求可接触的智力级别。
This is the silent limiter on Claude Fable 5.
Fable 5 may not give you its full strength when you use it to build or improve frontier AI models — especially work that helps train, scale, copy, or optimize a powerful Claude/GPT-class model.
Anthropic says in these cases Fable 5 may not visibly refuse or switch models, but may quietly reduce its own effectiveness through hidden safeguards like prompt modification, steering vectors, or PEFT.
As a paying user, that matters: the model can still sound helpful while being intentionally less capable in a narrow but important category of work.
i.e. you may not get Fable 5’s best ability:
- Building a large-model pretraining pipeline.
- Designing data pipelines for training a frontier LLM.
- Planning distributed training across huge GPU clusters.
- Debugging or optimizing model-parallel training systems.
- Designing infrastructure for large-scale pretraining runs.
- Working on ML accelerator or AI-chip design.
- Trying to distill or copy a frontier model.
- Asking how to make a competing frontier model stronger, cheaper, or faster.
Anthropic finally released Claude Fable 5, a public Mythos-class model. Fable 5 and Mythos 5 share one underlying model, but Fable adds classifier gates for everyone while Mythos lifts some gates for vetted cyber and infrastructure partners. i.e. the public version is wrapped in classifier gates that detect sensitive cyber, biology, chemistry, and model-copying requests. When those gates trigger, the user does not get a normal refusal; the request is handed to Opus 4.8, which means Anthropic is using model fallback as a control system. Anthropic says the leap is longer-range autonomy: a 50M-line Ruby migration in 1 day, screenshot-to-code work, has a 1M-token context window, That is the crucial shift: the product is no longer just a model, but a routing machine that decides which level of intelligence a user is allowed to touch for each request. The limit is that this routing is not arbitrary and not for every subject; Anthropic says the fallback is triggered by a narrow set of topics and appears in less than 5% of sessions on average.在 X 查看被引用的帖子
来源：Rohan Paul · x.com