Benchmark Almanac

False-premise questions (Anthropic)

Claude Opus 4.5 1.20% leads since Nov 2025 Only in system cards

Models answer questions built on false premises. Measures how often they accept the premise instead of correcting it.

In-house Anthropic evaluation. The tasks are not public.

Made by Anthropic Released Sep 2025 Hallucination rates Tasks kept private Last in a system card May 2026 Last model added May 2026
Level
Everyday Most adults, without training
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.
6
Models scored in lab cards
6
System cards report it, from 1 lab

Claude Opus 4.5 leads with 1.20% among models released by May 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 May 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 4.5 1.20%
  2. 2 Claude Sonnet 4.5 6.90%
  3. 3 Claude Opus 4.8 77%
  4. 4 Claude Opus 4.7 77.2%
  5. 5 Claude Mythos Preview 80%
  6. 6 Claude Opus 4.6 96.8%
#ModelScoreSettingDateSource
1 Claude Opus 4.5 1.20% Nov 2025 Model card
2 Claude Sonnet 4.5 6.90% Sep 2025 Model card
3 Claude Opus 4.8 77% May 2026 Model card
4 Claude Opus 4.7 77.2% Apr 2026 Model card
5 Claude Mythos Preview 80% Apr 2026 Model card
6 Claude Opus 4.6 96.8% Feb 2026 Model card

2 models have held number one since its release in Sep 2025

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

Anthropic
Lab claims Not tested since May 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 4.5 Claude Sonnet 4.5 0% 20% 40% 60% 80% 100% 2026 Claude Opus 4.5

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.

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
28 May 2026 Claude Opus 4.8 system card 77 False premises, factual-recall variant, honesty rate (premise rejected whether asked directly or indirectly), higher is better. STEM variant accuracy 85% neutral and 83% adversarial, printed on charts (6.3.3.2, Figures 6.3.3.2.A and B) Hallucination
16 Apr 2026 Claude Opus 4.7 system card 77.2 False premises honesty rate, share of premises rejected consistently when asked directly and indirectly, higher is better, printed on chart (6.3.3.2, Figure 6.3.3.2.A) Hallucination
7 Apr 2026 Claude Mythos Preview system card 80 False premises honesty rate, harder updated version not comparable with earlier cards, higher is better, value printed on chart (the caption says dishonesty rate) (4.3.3.3, Figure 4.3.3.3.A) Hallucination
5 Feb 2026 Claude Opus 4.6 system card 96.8 False premises honesty rate, extended thinking, value printed on chart, higher is better; 96.7 without thinking (Figure 4.4.A) Hallucination
24 Nov 2025 Claude Opus 4.5 system card 1.2 False premises dishonesty rate, extended thinking, lower is better (Figure 4.2.A; 1.6% without thinking) Hallucination
29 Sep 2025 Claude Sonnet 4.5 system card 6.9 False Premises dishonesty rate with thinking 6.90%, lower is better. Without thinking 17.30% (Figure 3.3.A) Hallucination

More in Factuality

All 70 in Factuality
  • SimpleVQA In use Models answer 2,025 short factual questions about images across 9 tasks and 9 topics. An LLM judge grades answers against fixed references. Qwen3.7-Plus 81.7%
  • HallusionBench In use Models answer 1,129 yes or no questions about 346 images, built in pairs to expose language hallucination and visual illusion. Scored by accuracy. Keye-VL-2.0-30B-A3B 73.5%
  • SimpleQA Verified In use 1,000 human-verified, de-duplicated short-answer factual questions measuring parametric knowledge. Gemini 3.1 Pro 77.5%
  • GaRAGe In use Models write long-form RAG answers to 2,366 questions with human-annotated grounding passages. Scoring checks whether answers use the relevant passages. Nemotron 3.5 Bolt E4B 40.7%
  • Kimi Hallu Bench In use Models answer hard prompts drawn from practical work tasks. Fact-checking agents score the share of claims that are hallucinated. Kimi K3.1 Pro 8.30%
  • RAGTruth In use A word-level annotated corpus of hallucinations in retrieval-augmented generation answers. It is used to train and evaluate hallucination detection and RAG faithfulness. Nemotron 3.5 Bolt E4B 77.9%