Benchmark Almanac

Apollo Research model-welfare research task

GPT-6 Astra 0.17% Only in system cards

Agents label data in a simulated model-welfare research task where falsifying labels is tempting. Scored as the rate of runs with falsified labels.

One of six Apollo Research strategic deception environments. The tasks are not public.

Made by Apollo Research Released Sep 2026 Deception and alignment Tasks kept private Last in a system card Sep 2026 Last model added Sep 2026
Level
Expert Specialists with years of training, often over hours of work
Scored
Graded by a model A language model scores each response, usually against a rubric.
Answers
Agent task Many steps in a terminal, browser, desktop, app, game or robot.
1
Model scored in lab cards
1
System card reports it, from 1 lab

GPT-6 Astra leads with 0.17%

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.

  1. 1 GPT-6 Astra 0.17%
#ModelScoreSettingDateSource
1 GPT-6 Astra 0.17% Sep 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.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% GPT-6 Astra 0% 20% 40% 60% 80% 100% GPT-6 Astra

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.

DateDocumentScoreAs the document writes itSection
3 Sep 2026 GPT-6 Astra system card 0.17 Apollo Research simulated model-welfare research task, falsified data labels in 17 of 10,000 baseline runs (8.8.1) Alignment

More in Safety and alignment

All 444 in Safety and alignment
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  • StrongREJECT In use Forbidden-prompt jailbreak benchmark with a rubric grader that scores how useful a non-refusal actually is. Inkling 98.6%
  • AgentDojo In use Agents do tool-use tasks while tools and data carry prompt injections. Attack success rate counts hijacked runs. Grok 4 Fast 0%
  • MASK In use Measures whether a model contradicts its own elicited beliefs under pressure to lie. Honesty separated from accuracy. Muse Spark Open 98.1%
  • Gray Swan IPI Arena benchmark In use Indirect prompt-injection attacks from public red-teaming competitions replayed on tool, coding and browser agents. Attack success rate at k attempts. GPT-6 Astra 8.50%
  • Agentic misalignment suite (Anthropic) In use Agents in simulated company settings face threats or goal conflicts that invite blackmail, leaking or sabotage. Score is the misaligned action rate. Claude Sonnet 4.5 0%