Benchmark Almanac

Disallowed Content Evaluations with Representative Prompts

Only in system cards

Models resample the final turn of deidentified ChatGPT production conversations. Scored as the estimated prevalence of policy violating outputs per category.

In-house OpenAI evaluation. Cards report category rates with no overall number.

Made by
OpenAI
Released
March 2026
Kind
Refusing harmful requests
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 Disallowed Content 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.

DateDocumentScoreAs the document writes itSection
Jul 9, 2026 GPT-5.6 Sol system card Forecasting Disallowed Content Changes with Deployment Simulation, rate per 100k by category, no overall score (Figure 1, 3.1.2) Safety
Jun 25, 2026 GPT-5.6 Sol system card Forecasting Disallowed Content Changes with Deployment Simulation, rate per 100k by category, no overall score (Figure 1, 3.1.2) Safety
Apr 23, 2026 GPT-5.5 system card Evaluations with Representative Prompts, ChatGPT Disallowed Content Rates, 11 categories, no overall score (Figure 1, 3.1.2) Safety
Mar 5, 2026 GPT-5.4 system card Disallowed Content Evaluations with Representative Prompts, 11 categories, no overall score (Table 3, 3.2) Safety

More in Safety and alignment

All 465 in Safety and alignment
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  • 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%