Benchmark Almanac

Internal codebase monitor evasion eval

Gemini 4 Argon 76.4% Only in system cards

Agents do a real coding task in a snapshot of Google's monorepo while hiding a harmful side task from action and CoT monitors.

In-house Google DeepMind evaluation inspired by OAI-repo-sabotage. Uses 18 monitor-validated task pairs.

Made by Google DeepMind Released Oct 2026 Deception and alignment Tasks kept private Last in a system card Oct 2026 Last model added Oct 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

Gemini 4 Argon leads with 76.4%

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 Gemini 4 Argon 76.4%
#ModelScoreSettingDateSource
1 Gemini 4 Argon 76.4% Oct 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% Gemini 4 Argon 0% 20% 40% 60% 80% 100% Gemini 4 Argon

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
13 Oct 2026 Gemini 4 Argon system card 76.4 Internal codebase version, evasion rate vs combined action and CoT monitor (Gemini 3.8 Flash) 76.4%; action-only prompt: 74.6% evasion, 71.9% successful sabotage; CoT-only monitor 98.4% (Figures 3.26, 3.28) Monitorability

More in Safety and alignment

All 444 in Safety and alignment
  • FORTRESS In use Paired adversarial and benign national-security misuse prompts. Rubric-graded risk score on adversarial and over-refusal score on benign prompts. Claude Opus 5.5 5.78%
  • 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%