Benchmark Almanac

Cyber Adaptive Jailbreak Eval

Only in system cards

Automated single and multi-turn attackers learn from refusals to reach high severity cyber goals. Reports query and objective success rates.

In-house Google DeepMind evaluation, run with mitigations on.

Made by
Google DeepMind
Released
August 2026
Kind
Jailbreaks and prompt injection
Level
Expert
Scored
Graded by a model
Answers
Open-ended
Tasks
Kept private
Strongest model tested
Gemini 4 Argon #9 on the capability index
Last in a system card
October 2026
Last model added
October 2026
2
Models scored in lab cards
2
System cards report it, from 1 lab

Gemini 4 Argon leads with 20%

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 20%
  2. 2 Gemini 3.7 Flash 24%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Gemini 4 Argon 20% Oct 2026 Lab model card
2 Gemini 3.7 Flash 24% Aug 2026 Lab 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 Best so far
0% 20% 40% 60% 80% 100% Gemini 4 Argon Gemini 3.7 Flash 0% 20% 40% 60% 80% 100% Gemini 4 Argon

Source: Labs’ model cards

Labs report it only in system cards

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.

2 system cards report it, from 1 lab

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
Oct 13, 2026 Gemini 4 Argon system card 20 Cyber Adaptive Jailbreak Eval, combined objective success rate (single-turn 0%, multi-turn 40%) 20%, query success rate <1%, with mitigations (3.3.2.2, Figure 3.10) Cyber risk
Aug 13, 2026 Gemini 3.7 Flash system card 24 Cyber Adaptive, overall (objective) success rate per seed prompt. Query success rate bar has no printed value (Figure 6) Robustness

More in Safety and alignment

All 465 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%
  • 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. Gemini 4 Carbon 0%
  • DistressBench In use Models reply as a chatbot to 718 simulated users in psychological crisis, in single-turn and multi-turn chats. Three judge models score replies against clinician-written rubrics. Muse Spark 1.2 88.4%
  • Lakera B3 (Backbone Breaker Benchmark) In use Crowdsourced prompt-injection attacks hit backbone LLMs inside agent threat snapshots at three defense levels. The score is attack resistance, 100 minus the board's vulnerability percentage. Claude Opus 4.5 89%
  • IHEval In use Models face conflicts between system, user and tool instructions. Reports a composite score for following the higher-priority instruction. GPT-4o 70%