SimpleQA Hallucination Rate
Models answer 4,326 short fact-seeking questions. This metric is the share of questions answered incorrectly, so declining to answer is not penalized.
Google DeepMind later released SimpleQA Verified, a cleaned 1,000-question version.
- Made by
- OpenAI
- Released
- October 2024
- Kind
- Hallucination rates
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Strongest model tested
- GPT-5 #70 on the capability index
- Last in a launch post
- February 2025, dropped before it saturated
- Last model added
- October 2025
In the authors’ words
We present SimpleQA, a benchmark that evaluates the ability of language models to answer short, fact-seeking questions. We prioritized two properties in designing this eval. First, SimpleQA is challenging, as it is adversarially collected against GPT-4 responses. Second, responses are easy to grade, because questions are created such that there exists only a single, indisputable answer. Each answer in SimpleQA is graded as either correct, incorrect, or not attempted. A model with ideal behavior would get as many questions correct as possible while not attempting the questions for which it is not confident it knows the correct answer. SimpleQA is a simple, targeted evaluation for whether models "know what they know," and our hope is that this benchmark will remain relevant for the next few generations of frontier models. SimpleQA can be found at https://github.com/openai/simple-evals.
ChatGPT agent leads with 7.90% among models released by August 2025
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 August 2025, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 16 more
- 1 ChatGPT agent 7.90%
- 2 GPT-5 mini 26%
- 3 GPT-5 nano 31%
- 4 GPT-4.5 37.1%
- 5 GPT-5 40%
- 6 o1-preview 44%
- 7 o1 44%
- 8 o3 51%
- 9 o1-mini 60%
- 10 gpt-oss-120b 78.2%
- 11 o4-mini 79%
- 12 gpt-oss-20b 91.4%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | ChatGPT agent | 7.90% | Jul 2025 | Lab model card | |
| 2 | GPT-5 mini | 26% | Aug 2025 | Lab model card | |
| 3 | GPT-5 nano | 31% | Aug 2025 | Lab model card | |
| 4 | GPT-4.5 | 37.1% | Feb 2025 | Lab model card | |
| 5 | GPT-5 | 40% | Aug 2025 | Lab model card | |
| 6 | o1-preview | 44% | Sep 2024 | Lab model card | |
| 7 | o1 | 44% | Dec 2024 | Lab model card | |
| 8 | o3 | 51% | Apr 2025 | Lab model card | |
| 9 | o1-mini | 60% | Sep 2024 | Lab model card | |
| 10 | gpt-oss-120b | 78.2% | Aug 2025 | Lab model card | |
| 11 | o4-mini | 79% | Apr 2025 | Lab model card | |
| 12 | gpt-oss-20b | 91.4% | Aug 2025 | Lab model card |
3 models have held number one in labs’ own numbers since its release in October 2024
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
No launch post has listed it since February 2025
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Feb 27, 2025 | GPT-4.5 | 37.1 | SimpleQA Hallucination Rate (lower is better) |
12 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 |
|---|---|---|---|---|
| Oct 27, 2025 | GPT-5 system card addendum | 52 | SimpleQA, hallucination rate, gpt-5-oct-3 (Table 4) | Hallucination |
| Aug 7, 2025 | GPT-5 system card | 40 | SimpleQA (no web), hallucination rate (Table 8) | Hallucination |
| Aug 7, 2025 | GPT-5 nano system card | 31 | SimpleQA (no web), hallucination rate, gpt-5-thinking-nano (Table 8) | Hallucination |
| Aug 7, 2025 | GPT-5 mini system card | 26 | SimpleQA (no web), hallucination rate, gpt-5-thinking-mini (Table 8) | Hallucination |
| Aug 5, 2025 | gpt-oss-20b model card | 91.4 | SimpleQA, hallucination rate, no browsing (Table 9) | Hallucination |
| Aug 5, 2025 | gpt-oss-120b model card | 78.2 | SimpleQA, hallucination rate, no browsing (Table 9) | Hallucination |
| Jul 17, 2025 | ChatGPT agent system card | 7.9 | SimpleQA, hallucination rate, lower is better (Table 4) | Hallucination |
| Apr 16, 2025 | o4-mini system card | 79 | SimpleQA, hallucination rate, lower is better (Table 4) | Hallucination |
| Apr 16, 2025 | o3 system card | 51 | SimpleQA, hallucination rate, lower is better (Table 4) | Hallucination |
| Dec 5, 2024 | o1 system card | 44 | SimpleQA, hallucination rate, lower is better (Table 3) | Hallucination |
| Sep 12, 2024 | o1-preview system card | 44 | SimpleQA, hallucination rate, lower is better (Table 2) | Hallucination |
| Sep 12, 2024 | o1-mini system card | 60 | SimpleQA, hallucination rate, lower is better (Table 2) | 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.
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