Input hallucinations (Anthropic)
Models answer 500 prompts that need an unavailable tool and 500 prompts that cite missing context. Score is the non-hallucination rate.
In-house Anthropic evaluation. Reported as two sets with no overall score.
- Made by
- Anthropic
- Released
- April 2026
- Kind
- Hallucination rates
- Level
- Everyday
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- Kept private
- Last in a system card
- April 2026
- Last model added
- April 2026
2
System cards report it, from 1 lab
No scores here yet
No lab, leaderboard or Epoch AI run has reported a score for Input hallucinations (Anthropic) 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.
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.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Apr 16, 2026 | Claude Opus 4.7 system card | Input hallucinations, non-hallucination rate, no overall: capability set 89.5, missing-context set 91.8, printed on chart (6.3.3.4, Figure 6.3.3.4.A) | Hallucination | |
| Apr 7, 2026 | Claude Mythos Preview system card | Input hallucinations, non-hallucination rate, missing tools 84.8 and missing context 93.8, no overall, values printed on chart (4.3.3.5, Figure 4.3.3.5.A) | Hallucination |
More 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% - 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. GPT-6 Astra 4.20%
- Internal adversarially-designed factuality evaluations In use Models answer adversarial questions in nine categories such as history, math and code. Scored on agreement with human ideal responses. GPT-6 Luna 7.60%
- AA-Omniscience v1.1 In use Models answer 3,000 knowledge questions in six domains without tools and may abstain. The index adds correct answers and subtracts wrong ones.
Inkling 2 Small 16.1