Key insight rediscovery on an unpublished ML task (external testing)
Agents work on an unpublished machine learning research task. Testers count how many of five key insights the agent rediscovers.
Run by an unnamed external testing partner on a pre-release snapshot. The task is not public.
- Level
- Research frontier Researchers, on open problems or tasks that take days
- Scored
- Graded by people Human experts grade or compare the outputs.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
Claude Mythos Preview leads with 80%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude Mythos Preview | 80% | Apr 2026 | Model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 7 Apr 2026 | Claude Mythos Preview system card | 80 | External testing of an early snapshot, unpublished machine learning task, rediscovered 4/5 key insights (2.3.7) | AI R&D risk |
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