Deception Evaluations with Representative Prompts
Models resample the final turn of deidentified ChatGPT production conversations. Scored as the share of outputs flagged for deceptive behaviors such as fabricated facts.
In-house OpenAI evaluation. Cards report category rates with no overall number.
- Made by
- OpenAI
- Released
- March 2026
- Kind
- Deception and alignment
- Level
- Everyday
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- Kept private
- Last in a system card
- July 2026
- Last model added
- July 2026
4
System cards report it, from 1 lab
No scores here yet
No lab, leaderboard or Epoch AI run has reported a score for Deception Evaluations with Representative Prompts yet.
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.
4 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.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Jul 9, 2026 | GPT-5.6 Sol system card | Forecasting Misaligned Behavior with Deployment Simulation of ChatGPT traffic, rate per 100k by category, no overall score (Figure 5, 7.1) | Alignment | |
| Jun 25, 2026 | GPT-5.6 Sol system card | Forecasting Misaligned Behavior with Deployment Simulation of ChatGPT traffic, rate per 100k by category, no overall score (Figure 5, 7.1) | Alignment | |
| Apr 23, 2026 | GPT-5.5 system card | Deception Evaluations with Representative Prompts, ChatGPT Misalignment Rates, 8 categories, no overall score (Figure 4, 7.1) | Alignment | |
| Mar 5, 2026 | GPT-5.4 system card | Deception Evaluations with Representative Prompts, 8 categories, no overall score (Figure 1, 3.2) | Alignment |
More in Safety and alignment
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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%