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Over Eight Months of Progress in Two: Analyzing the Mythos Preview Capability Jump
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Over Eight Months of Progress in Two: Analyzing the Mythos Preview Capability Jump

LessWrong · May 7, 2026, 4:19 PM

Anthropic’s most powerful model, Claude Mythos Preview, has alarmed and excited many people, especially given its cybersecurity capabilities[1]. But what concerns me most is something else: in two months, Anthropic appears to have made as much progress in AI development as would normally take half a year.What if this isn’t a temporary boost in capabilities, but the start of a faster trend in AI progress?Thanks to Benjamin Schmidt, Luke Mc Nally, and Bisesh Belbase for their feedback on this article!The Epoch Capabilities Index (ECI) combines many AI benchmarks into a single score, allowing for comparing general capability across models. It doesn’t saturate like many individual benchmarks, and is very well-suited for studying capability trends.Anthropic measured ECI scores for Mythos Preview and previous models using both external and internal benchmarks, which means that their scores are not directly comparable to public ECI scores. Their results show a stable trend with capabilities increasing along a straight line — until Mythos Preview:Anthropic provides estimates of the ECI trend with a breakpoint at the release of different models. Set the breakpoint at Opus 4.5, and growth jumps from 15.5 ECI/year to 28.8 ECI/year (1.86×). Set it at Opus 4.6, and growth jumps from 15.7 ECI/year to 67.4 ECI/year (4.28×).Eyeballing the graph, it seems Opus 4.6 scored ~153, while Mythos Preview scored ~161. In the two months between Opus 4.6 (5 Feb 2026) and Mythos Preview (7 Apr 2026), the score jumped ~8 points; a gain that previously took roughly six months[2]. However, the speedup of 4.28× implies that the capability jump corresponds to roughly 8.6 months of progress[3]. Perhaps my eyeballing is off.In my last article I speculated about future development pace, but completely failed to anticipate this.As noted in that article, the length of software engineering tasks (measured in human completion time) that AIs can complete with 50% success rate (the 50% time horizon) has been

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