Anthropic 前研究员称 Mythos 重训算力已大幅下降
Anthropic 前研究员 Jacob Coxon 称，公司已能用“原始所需算力的一小部分”重新训练 Mythos 模型，并指出 IPO 路演中一张算力增长曲线图是他离职的关键原因。该说法暗示算法效率提升可能显著压低前沿模型的训练成本，但目前仅为个人转述，缺乏官方数据佐证。
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Anthropic can already retrain Mythos with "a fraction of the compute originally needed," says former researcher Coxon
[Matthias Bastian](https://the-decoder.com/author/matthias-bastian/) [View the LinkedIn Profile of Matthias Bastian](https://www.linkedin.com/in/matthias-bastian-128b71b1/) Nov 14, 2026 
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Jacob Coxon, former OpenAI and Anthropic researcher who brought AI fears into the mainstream, says a slide from Anthropic's IPO roadshow was a major reason he quit.
Coxon says a slide Anthropic released for its IPO roadshow was a key reason he left the company after only about four months. The chart shows how much compute Anthropic needs over time to train its models, and the axis is compressed so that a 10x and a 100x increase barely look different.
Yet the curve still climbs steeply, which Coxon says shows that algorithmic efficiency is improving not just quickly but at an accelerating rate. "It's an insane plot and I'm surprised they made it public," he writes.
Coxon argues that Anthropic's Mythos model, a major capability jump in the spring, was part of this accelerating trend. "Mythos was not a one-time deviation, but a point on a superexponential. They could already retrain Mythos with a fraction of the compute originally needed," he writes.
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This slide from Anthropic's IPO roadshow shows the "Pre-training compute multiplier" for code over time. The y-axis is logarithmic. Former Anthropic researcher Jacob Coxon says the steep climb from July 2024 to October 2026 points to superexponential algorithmic progress. Anthropic notes that the data points are based on internal estimates and are for illustration only. | Image: Anthropic
He says algorithmic improvements are "on the verge of being automated," which is why he wants frontier model development paused next year so competitors can catch up. A pause, he writes, would "commoditize human-level intelligence. It would only harm OpenAI and Anthropic."
Coxon previously trained AI models at OpenAI and, most recently, Anthropic. He drew wide attention in September with public warnings about the risks of advanced AI systems, echoed by other protagonists in the industry. One of their fears is that advanced, self-improving AI could get out of control.