Claude Mythos Cracks AI Benchmark Ceiling, Super‑Exponential Leap Toward 2027 Singularity

The METR benchmark measures an AI model’s ability to autonomously complete long‑horizon tasks by defining a “50% success‑rate timeline” – the duration at which a model has a 50% chance of finishing a task that would take a human X hours.

In the latest METR test, Claude Mythos achieved a 50% success rate on a task estimated to require 16 hours of human effort, a level no previous model could reach; earlier models topped out at minutes‑scale tasks.

Historical progression shows the gap widening dramatically: 2021 models handled 8‑second code edits, early 2023 reached 1‑minute functions, mid‑2024 managed ~1‑hour feature implementations, and by April 2026 Mythos hit the 16‑hour mark, each generation improving faster than the last.

The METR trend graph (log‑scale Y‑axis for task duration, X‑axis for model release year) plots each model as a point; connecting them yields a curve steeper than exponential, described as a “super‑exponential” arc that already sits above the projected AGI trajectory for 2027.

Because METR’s vertical axis is not a traditional score but a task‑duration metric, the organization admits it cannot reliably measure beyond the 16‑hour region – the “measurement ceiling” is broken, leaving the true depth of AI capability unknown.

Security analysts at Palo Alto Networks, with early unrestricted access to Mythos and GPT‑5.5‑Cyber, reported that Mythos can perform vulnerability analysis equivalent to a year‑long penetration‑testing effort in just three weeks, stitching together thousands of minor bugs into a lethal attack chain.

Anthropic initially withheld a full release of Claude Mythos citing safety concerns, while Mozilla used it to patch a record 423 security issues in Firefox within a single month. Nvidia’s massive 400 billion‑USD investment in the AI stack further accelerates the race toward the singularity.

The overall picture is one of accelerating AI capability that outpaces both academic measurement tools and traditional security defenses, urging a shift from hour‑scale response times to minute‑or‑second automated AI‑vs‑AI defenses.