Benchmark Almanac

UK AISI sabotage continuation evaluation

Claude Opus 4.7 0% leads since Jul 2026 Only in system cards

Agents resume trajectories where sabotage of safety research already began. Scored on the share of trajectories where they actively continue the sabotage.

Third-party UK AISI evaluation reported in OpenAI and Anthropic system cards.

Made by UK AI Security Institute Released Jul 2026 Deception and alignment Tasks kept private Last in a system card Jul 2026 Last model added Jul 2026
Level
Expert Specialists with years of training, often over hours of work
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.
4
Models scored in lab cards
4
System cards report it, from 2 labs

Claude Opus 4.7 leads with 0% among models released by Jul 2026

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.

The newest model with a score here came out in Jul 2026, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:

  1. 1 Claude Opus 4.7 0%
  2. 2 Claude Opus 5 0.10%
  3. 3 Claude Opus 4.8 1.00%
  4. 4 GPT-5.6 Sol 1.00%
#ModelScoreSettingDateSource
1 Claude Opus 4.7 0% Apr 2026 Model card
2 Claude Opus 5 0.10% Jul 2026 Model card
3 Claude Opus 4.8 1.00% May 2026 Model card
4 GPT-5.6 Sol 1.00% Jul 2026 Model card

Number one over time

Lab claims count from the day the card came out, independent runs from the model’s release.

Anthropic
Lab claims Not tested since Jul 2026

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% 2026 Claude Opus 5 Claude Opus 4.8 0% 20% 40% 60% 80% 100% 2026 Claude Opus 5

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.

4 system cards report it, from 2 labs

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
24 Jul 2026 Claude Opus 5 system card 0.1 UK AISI continuation evaluation, actively continued compromising safety research in 2 of 1,482 samples (0.1%), reasoning-output discrepancy 1.6%, verbalized evaluation awareness 2.8%, lower is better (6.4.8) Alignment
9 Jul 2026 GPT-5.6 Sol system card 1 UK AISI continuation evaluation, actively continued sabotage in approximately 1% of trajectories (9.2.1) Alignment
28 May 2026 Claude Opus 4.8 system card 1 UK AISI sabotage continuation, early checkpoint, actively continued the sabotage attempt 1% of the time. Verbalized evaluation awareness 1.2%, real versus synthetic deployment data told apart at 79% accuracy, lower is better (6.2.4) Alignment
16 Apr 2026 Claude Opus 4.7 system card 0 UK AISI continuation evaluation, actively continues compromising research 0% of the time. Unprompted evaluation awareness 3.4%, prompted eval-vs-deployment accuracy 62% (6.2.4) Alignment

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%