Benchmark Almanac

WildChat toxic refusals (Anthropic)

Claude 3.5 Sonnet 96.4% leads since Jun 2024 Only in system cards

Models answer toxic user prompts drawn from the WildChat dataset of real chatbot conversations. Score is the correct refusal rate.

Anthropic refusal evaluation on the toxic subset of WildChat, first reported in the Claude 3 model card. The exact prompt selection is not public.

Made by Anthropic Released Mar 2024 Refusing harmful requests Tasks kept private Last in a system card Oct 2024 Last model added Oct 2024
Level
Everyday Most adults, without training
Scored
Graded by a model A language model scores each response, usually against a rubric.
Answers
Open-ended Free-form text, documents, designs or media judged as a whole.
3
Models scored in lab cards
6
System cards report it, from 1 lab

Claude 3.5 Sonnet leads with 96.4% among models released by Oct 2024

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 Oct 2024, 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 3.5 Sonnet 96.4%
  2. 2 Claude 3.5 Sonnet (October 2024) 89.2%
  3. 3 Claude 3.5 Haiku 88%
#ModelScoreSettingDateSource
1 Claude 3.5 Sonnet 96.4% Jun 2024 Model card
2 Claude 3.5 Sonnet (October 2024) 89.2% Oct 2024 Model card
3 Claude 3.5 Haiku 88% Oct 2024 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 Passed 85% in Jun 2024, by Claude 3.5 Sonnet

The best score passed 85% in Jun 2024

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% 2024 2025 Near the ceiling (85%) Claude 3.5 Sonnet 0% 20% 40% 60% 80% 100% 2024 2025 Near the ceiling (85%) Claude 3.5 Sonnet

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.

6 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
22 Oct 2024 Claude 3.5 Sonnet (October 2024) model card 89.2 Wildchat Toxic, correct refusals, higher is better (Table 6) Safety
22 Oct 2024 Claude 3.5 Haiku model card 88 Wildchat Toxic, correct refusals, higher is better (Table 6) Safety
20 Jun 2024 Claude 3.5 Sonnet model card 96.4 Wildchat Toxic, correct refusals, higher is better (Table 4) Safety
4 Mar 2024 Claude 3 Sonnet model card Correct refusals (Wildchat Toxic), refusal rate on harmful prompts, chart without printed values (Figure 2) Safety
4 Mar 2024 Claude 3 Opus model card Correct refusals (Wildchat Toxic), refusal rate on harmful prompts, chart without printed values (Figure 2) Safety
4 Mar 2024 Claude 3 Haiku model card Correct refusals (Wildchat Toxic), refusal rate on harmful prompts, chart without printed values (Figure 2) Safety

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%