Signal Brief

Anthropic Opus 5 表现与基准值失衡、指令优先级争议

用户分析发现,Anthropic Opus 5 在基准测试中表现超出 Fable 5 并引发基准值有效性质疑。根据 Kun Chen 的观察,尽管 Opus 5 在多项指标上胜过 Fable 5,但实际应用场景中两者效能差异显著。研究指出公司在 5 系列模型训练策略上发生变化,将 Mythos 作为...

twitter关注列表 Orange AI (@oran_ge) 发布 2026-07-26 收录 2026-07-26 值得跟进

一句话判断

需关注基准测试方法论修正及训练策略调整可能性,同时留意人性化交互优化方向

核心信息

用户分析发现,Anthropic Opus 5 在基准测试中表现超出 Fable 5 并引发基准值有效性质疑。根据 Kun Chen 的观察,尽管 Opus 5 在多项指标上胜过 Fable 5,但实际应用场景中两者效能差异显著。研究指出公司在 5 系列模型训练策略上发生变化,将 Mythos 作为先导模型后通过蒸馏生成 Sonnet 和 Opus,但此策略可能导致生成效能未达预期。同时指出人性化交互体验下降,用户更偏好 Grok 和 Kimi 的使用体验。

原始内容

非常吊诡的是,Opus 5 几乎在每一项指标上都超越了 Fable 5 也许这只能说明我们的所有指标都已经失效了 而且 Claude 系列的模型用起来的味道不太对劲,现在味道比较对的是 Kimi 和 Grok 对 RLVR 而言,重要的只有结果本身,而人类的偏好并没有那么重要 对齐计划,失败了吗? > **引用原帖 Kun Chen (@kunchenguid):** > opus 5 is a VERY interesting release for a few reasons > 1. it showed that the general benchmarks we use today are almost completely useless now > opus 5 is nowhere near fable in practical use, not even close. anyone who’s used it meaningfully can tell this very quickly after a few tasks. yet opus beats fable on many benchmarks > i now trust domain specific benchmarks built with private datasets a lot more than the popular ones. perhaps the future is everyone running their own evals because the public ones are really not telling us much > 2. it seems with the 5 series, anthropic is trying a new way of training models > previously, the same generation of sonnet and opus were often released at the same time or sonnet comes out before opus, which indicates sonnet and opus were trained by separate pipelines in parallel > with the 5 series, it was very clear that they trained mythos first, and then distilled it into sonnet and opus. it seems this approach has a big influence on the models > seeing sonnet 5 being a flop and opus 5 getting pretty mixed reviews already, i’m not sure this is working out > 3. “how pleasant is it to work with the model” used to be a strength in claude, but now it’s not. honestly, grok is my favorite right now on the “pleasant” dimension. kimi is not bad either > it feels like both anthropic and openai are giving RLHF less care, in favor of scalable RL that’s machine verifiable > this almost looks like AI is directing humans to build a world that’s more friendly for machines rather than humans, and most humans don’t even realize they are being manipulated to help with that > almost every new generation of frontier models now talk more jargons, need more steering to do what you want, and are just less fun to work with > if this continues, AI will start to speak their own language that looks like English but average humans can’t understand. they will choose to do things that their human user never asked for. are we already failing at alignment? > https://x.com/kunchenguid/status/2081125298050060694

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