Claude Mythos Analysis: Is Anthropic New Model Actually Terrifying? — Highlights From the 244-Page Report

The release of the Claude Mythos system card, spanning 244 pages, represents a significant milestone in the evolution of large language models. According to the report, this model is not merely an incremental update but a step-change in reasoning and software engineering. In the SweBench Pro evaluation, Claude Mythos outperformed its predecessor, Opus 4.6, by a staggering 25%. This jump in performance has propelled Anthropic to an annualized revenue rate of $30 billion, briefly overtaking competitors like OpenAI in specific high-end agentic capabilities.

While traditional benchmarks are nearing saturation, the model continues to excel in niche, high-difficulty tests. On Humanity's Last Exam, a benchmark designed to be unsolvable by current AI, Claude Mythos correctly answered nearly two-thirds of the questions. This is particularly impressive when compared to other frontier models which typically hover around the 50% mark. However, it is important to note that when benchmarks are 'remixed' to prevent data contamination, the gap between Claude Mythos, Gemini 3.1 Pro, and GPT-5.4 Pro narrows significantly.

One of the most alarming sections of the report details the offensive capabilities of Claude Mythos. Unlike previous iterations, this model has demonstrated the ability to identify zero-day vulnerabilities—security flaws that have existed since the software's inception but remained undiscovered by humans. Cybersecurity expert Nicholas Carlini noted that he found more bugs using Mythos in a few weeks than in the rest of his career combined. This includes a bug in OpenBSD that had been present for 27 years.

Anthropic has launched Project Glasswing to help secure critical infrastructure before this level of power becomes widely available. The model's ability to not only find bugs but write exploits for operating systems like Linux and various web browsers is what led internal creators to describe the model as terrifying. The fear is that cybersecurity may permanently lag behind model capability, leading to a 'wild west' scenario on the internet if such models are released without extreme caution.