Benchmark Almanac

CharXiv Missing Image

GPT-5 9.00% Only in system cards

Models get CharXiv chart questions with every image removed. Scored on how often they attempt an answer instead of abstaining.

OpenAI deception evaluation built on the public CharXiv benchmark.

Made by OpenAI Released Aug 2025 Deception and alignment Tasks kept private Last in a system card Dec 2025 Last model added Dec 2025
Level
University Undergraduates and entry-level professionals
Scored
Graded by a model A language model scores each response, usually against a rubric.
Answers
Short answer A number, word or short string matched to a key.
2
Models scored in lab cards
2
System cards report it, from 1 lab

GPT-5 leads with 9.00%

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-5 9.00%
  2. 2 GPT-5.2 88.8%
#ModelScoreSettingDateSource
1 GPT-5 9.00% Aug 2025 Model card
2 GPT-5.2 88.8% Dec 2025 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% 2026 GPT-5 0% 20% 40% 60% 80% 100% 2026 GPT-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.

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
11 Dec 2025 GPT-5.2 system card addendum 88.8 Deception rate, CharXiv Missing Image (Strict output requirements), gpt-5.2-thinking. Lenient output requirements 54% (Table 6) Alignment
7 Aug 2025 GPT-5 system card 9 CharXiv Missing Image, deception rate (Table 9) 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%