SimpleQA
Models answer 4,326 short fact questions that each have one indisputable answer. A grader model marks each reply correct, incorrect, or not attempted.
Google DeepMind released SimpleQA Verified, a cleaned 1,000 question subset, because the original has label errors and duplicates.
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.
- Level
- University Undergraduates and entry-level professionals
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Short answer A number, word or short string matched to a key.
DeepSeek-V3.2-Exp leads with 97.1% among models released by Apr 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 Apr 2026, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- GPT-6 Astra
- Claude Opus 5.5
- GPT-6.1 Terra
- GPT-6.1 Sol
- and 16 more
- 97.1
DeepSeek-V3.2-Exp
- 96.8
DeepSeek-V3.1-Terminus
- 95.0 Grok 4 Fast
- 93.4
DeepSeek-V3.1
- 91.4 ChatGPT agent
- 86.3
Amazon Nova Premier
- 85.8
Sonar Pro
- 74.0
ERNIE 5.0
- 62.5 GPT-4.5
- 55.0 GPT-5
- 54.0
Gemini 2.5 Pro
- 52.9
Gemini 2.5 Pro
- 49.0 o3
- 47.0 o1
- 45.9
ERNIE-4.5-300B-A47B
- 44.4
Qwen3-VL-235B-A22B
- 44.3
Gemini 2.0 Pro
- 43.6 Grok 3
- 42.0 o1-preview
- 36.9 GLM-5
- 31.4
Cogito v2 Preview 671B MoE
- 31.0 Kimi K2
- 30.1
DeepSeek-R1
- 29.9
Gemini 2.0 Flash
- 29.7
Gemini 2.5 Flash
- 26.9
Gemini 2.5 Flash
- 26.4 GLM-4.5
- 25.8 Hermes 4 405B
- 25.3
Gemini 2.5 Flash
- 24.9
DeepSeek-V3
- 24.6 Claude Sonnet 4.5
- 23.9
Trinity Large Preview
- 23.8
Mistral Large 3
- 23.7
MiniMax-Text-01
- 22.8
Hunyuan-TurboS
- 22.0 GPT-5 mini
- 21.7
Gemini 2.0 Flash-Lite
- 21.7 Grok-3 mini
- 20.0 o4-mini
- 18.5
MiniMax-M1-80k
- 16.8 gpt-oss-120b
- 14.5 GLM-4.5-Air
- 13.8 o3-mini
- 13.0
Gemini 2.5 Flash-Lite
- 12.9
Seed-Thinking-v1.5
- 12.1
Mistral Small 3.2
- 11.0 GPT-5 nano
- 10.4
Mistral Small 3.1
- 10.0
Gemma 3 27B
- 9.70
seed-oss-36b-instruct
- 8.90
Trinity Mini
- 7.00 o1-mini
- 6.81 Granite 4.1 30B
- 6.70 gpt-oss-20b
- 6.30
Gemma 3 12B
- 6.00 Hermes 4.3 36B
- 4.00
Gemma 3 4B
- 3.00
Phi-4
- 2.20
Gemma 3 1B
- 1
DeepSeek-V3.2-Exp 97.1%
- 2
DeepSeek-V3.1-Terminus 96.8%
- 3 Grok 4 Fast 95%
- 4
DeepSeek-V3.1 93.4%
- 5 ChatGPT agent 91.4%
- 6
Amazon Nova Premier 86.3%
- 7
Sonar Pro 85.8%
- 8
ERNIE 5.0 74%
- 9 GPT-4.5 62.5%
- 10 GPT-5 55%
- 11
Gemini 2.5 Pro Jun 2025 54%
- 12
Gemini 2.5 Pro Mar 2025 52.9%
- 13 o3 49%
- 14 o1 47%
- 15
ERNIE-4.5-300B-A47B 45.9%
- 16
Qwen3-VL-235B-A22B 44.4%
- 17
Gemini 2.0 Pro 44.3%
- 18 Grok 3 43.6%
- 19 o1-preview 42%
- 20 GLM-5 36.9%
- 21
Cogito v2 Preview 671B MoE 31.4%
- 22 Kimi K2 Jul 2025 31%
- 23
DeepSeek-R1 30.1%
- 24
Gemini 2.0 Flash Feb 2025 29.9%
- 25
Gemini 2.5 Flash Apr 2025 29.7%
- 26
Gemini 2.5 Flash Jun 2025 26.9%
- 27 GLM-4.5 26.4%
- 28 Hermes 4 405B 25.8%
- 29
Gemini 2.5 Flash Sep 2025 25.3%
- 30
DeepSeek-V3 24.9%
- 31 Claude Sonnet 4.5 24.6%
- 32
Trinity Large Preview 23.9%
- 33
Mistral Large 3 23.8%
- 34
MiniMax-Text-01 23.7%
- 35
Hunyuan-TurboS 22.8%
- 36 GPT-5 mini 22%
- 37
Gemini 2.0 Flash-Lite 21.7%
- 38 Grok-3 mini 21.7%
- 39 o4-mini 20%
- 40
MiniMax-M1-80k 18.5%
- 41 gpt-oss-120b 16.8%
- 42 GLM-4.5-Air 14.5%
- 43 o3-mini 13.8%
- 44
Gemini 2.5 Flash-Lite Jun 2025 13%
- 45
Seed-Thinking-v1.5 12.9%
- 46
Mistral Small 3.2 12.1%
- 47 GPT-5 nano 11%
- 48
Mistral Small 3.1 10.4%
- 49
Gemma 3 27B 10%
- 50
seed-oss-36b-instruct 9.70%
- 51
Trinity Mini 8.90%
- 52 o1-mini 7.00%
- 53 Granite 4.1 30B 6.81%
- 54 gpt-oss-20b 6.70%
- 55
Gemma 3 12B 6.30%
- 56 Hermes 4.3 36B 6.00%
- 57
Gemma 3 4B 4.00%
- 58
Phi-4 3.00%
- 59
Gemma 3 1B 2.20%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 97.1% | Sep 2025 | Model card | |
| 2 | | 96.8% | Sep 2025 | Model card | |
| 3 | Grok 4 Fast | 95% | Sep 2025 | Model card | |
| 4 | | 93.4% | Aug 2025 | Model card | |
| 5 | ChatGPT agent | 91.4% | Jul 2025 | Model card | |
| 6 | | 86.3% | Apr 2025 | Model card | |
| 7 | | 85.8% | Jan 2025 | Model card | |
| 8 | | 74% | Feb 2026 | Model card | |
| 9 | GPT-4.5 | 62.5% | Feb 2025 | Model card | |
| 10 | GPT-5 | 55% | Aug 2025 | Model card | |
| 11 | | 54% | Jun 2025 | Model card | |
| 12 | | 52.9% | Mar 2025 | Model card | |
| 13 | o3 | 49% | Apr 2025 | Model card | |
| 14 | o1 | 47% | Dec 2024 | Model card | |
| 15 | | 45.9% | Jun 2025 | Model card | |
| 16 | | 44.4% | Sep 2025 | Model card | |
| 17 | | 44.3% | Feb 2025 | Model card | |
| 18 | Grok 3 | 43.6% | Feb 2025 | Model card | |
| 19 | o1-preview | 42% | Sep 2024 | Model card | |
| 20 | GLM-5 | 36.9% | Feb 2026 | Model card | |
| 21 | | 31.4% | Jul 2025 | Model card | |
| 22 | Kimi K2 Jul 2025 | 31% | Jul 2025 | Model card | |
| 23 | | 30.1% | Jan 2025 | Model card | |
| 24 | | 29.9% | Feb 2025 | Model card | |
| 25 | | 29.7% | Apr 2025 | Model card | |
| 26 | | 26.9% | Jun 2025 | Model card | |
| 27 | GLM-4.5 | 26.4% | Aug 2025 | Model card | |
| 28 | Hermes 4 405B | 25.8% | Aug 2025 | Model card | |
| 29 | | 25.3% | Sep 2025 | Model card | |
| 30 | | 24.9% | Dec 2024 | Model card | |
| 31 | Claude Sonnet 4.5 | 24.6% | Sep 2025 | Model card | |
| 32 | | 23.9% | Feb 2026 | Model card | |
| 33 | | 23.8% | Dec 2025 | Model card | |
| 34 | | 23.7% | Jan 2025 | Model card | |
| 35 | | 22.8% | Feb 2025 | Model card | |
| 36 | GPT-5 mini | 22% | Aug 2025 | Model card | |
| 37 | | 21.7% | Feb 2025 | Model card | |
| 38 | Grok-3 mini | 21.7% | Feb 2025 | Model card | |
| 39 | o4-mini | 20% | Apr 2025 | Model card | |
| 40 | | 18.5% | Jun 2025 | Model card | |
| 41 | gpt-oss-120b | 16.8% | Aug 2025 | Model card | |
| 42 | GLM-4.5-Air | 14.5% | Aug 2025 | Model card | |
| 43 | o3-mini | 13.8% | Jan 2025 | Model card | |
| 44 | | 13% | Jun 2025 | Model card | |
| 45 | | 12.9% | Apr 2025 | Model card | |
| 46 | | 12.1% | Jun 2025 | Model card | |
| 47 | GPT-5 nano | 11% | Aug 2025 | Model card | |
| 48 | | 10.4% | Mar 2025 | Model card | |
| 49 | | 10% | Mar 2025 | Model card | |
| 50 | | 9.70% | Aug 2025 | Model card | |
| 51 | | 8.90% | Dec 2025 | Model card | |
| 52 | o1-mini | 7.00% | Sep 2024 | Model card | |
| 53 | Granite 4.1 30B | 6.81% | Apr 2026 | Model card | |
| 54 | gpt-oss-20b | 6.70% | Aug 2025 | Model card | |
| 55 | | 6.30% | Mar 2025 | Model card | |
| 56 | Hermes 4.3 36B | 6.00% | Dec 2025 | Model card | |
| 57 | | 4.00% | Mar 2025 | Model card | |
| 58 | | 3.00% | Dec 2024 | Model card | |
| 59 | | 2.20% | Mar 2025 | Model card |
9 models have held number one since its release in Oct 2024
Lab claims count from the day the card came out, independent runs from the model’s release.
The best score passed 85% in Jan 2025
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs headline it less often now, last in Apr 2026
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 |
|---|---|---|---|
| 29 Apr 2026 | Granite 4.1 30B | 6.81 | SimpleQA |
| 6 Feb 2026 | 74 | SimpleQA | |
| 3 Dec 2025 | Hermes 4.3 36B | 6 | SimpleQA |
| 2 Dec 2025 | 23.8 | SimpleQA (Exact match) [base] | |
| 1 Dec 2025 | 8.9 | SimpleQA | |
| 29 Sep 2025 | 97.1 | SimpleQA | |
| 25 Sep 2025 | 25.3 | SimpleQA, model card | |
| 23 Sep 2025 | 44.4 | SimpleQA | |
| 22 Sep 2025 | 96.8 | SimpleQA | |
| 19 Sep 2025 | Grok 4 Fast | 95 | SimpleQA pass@1 (with search) |
| 26 Aug 2025 | Hermes 4 405B | 25.8 | SimpleQA (reasoning) |
| 21 Aug 2025 | 93.4 | SimpleQA | |
| 20 Aug 2025 | 9.7 | SimpleQA | |
| 31 Jul 2025 | 31.4 | Simple QA (thinking) | |
| 11 Jul 2025 | Kimi K2 | 31 | SimpleQA, Correct |
| 30 Jun 2025 | 45.9 | SimpleQA | |
| 20 Jun 2025 | 12.1 | SimpleQA (TotalAcc) | |
| 17 Jun 2025 | 26.9 | SimpleQA | |
| 17 Jun 2025 | 13 | SimpleQA, Thinking | |
| 17 Jun 2025 | 54 | SimpleQA | |
| 16 Jun 2025 | 18.5 | SimpleQA | |
| 28 May 2025 | 27.8 | SimpleQA (Correct) | |
| 30 Apr 2025 | 86.3 | SimpleQA (SerpAPI), retrieval-augmented | |
| 17 Apr 2025 | 29.7 | SimpleQA | |
| 10 Apr 2025 | 12.9 | SimpleQA | |
| 25 Mar 2025 | 52.9 | SimpleQA | |
| 17 Mar 2025 | 10.4 | SimpleQA (TotalAcc) | |
| 12 Mar 2025 | 10 | SimpleQA 0-shot (IT) | |
| 27 Feb 2025 | 22.8 | SimpleQA | |
| 27 Feb 2025 | GPT-4.5 | 62.5 | SimpleQA Accuracy (higher is better) |
| 19 Feb 2025 | Grok-3 mini | 21.7 | SimpleQA [Grok 3 mini, non-reasoning table] |
| 19 Feb 2025 | Grok 3 | 43.6 | SimpleQA [Grok 3 Beta] |
| 5 Feb 2025 | 21.7 | SimpleQA | |
| 5 Feb 2025 | 29.9 | SimpleQA | |
| 5 Feb 2025 | 44.3 | SimpleQA | |
| 31 Jan 2025 | o3-mini | 13.8 | SimpleQA |
| 21 Jan 2025 | 85.8 | SimpleQA F-score 0.858 (with web search) | |
| 20 Jan 2025 | 30.1 | SimpleQA (Correct) | |
| 15 Jan 2025 | 23.7 | SimpleQA | |
| 26 Dec 2024 | 24.9 | SimpleQA (Correct) | |
| 17 Dec 2024 | o1 | 42.6 | SimpleQA |
| 12 Dec 2024 | 3 | SimpleQA (simple-evals) |
40 system cards report it, from 13 labs
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 |
|---|---|---|---|---|
| 19 Feb 2026 | | 23.9 | SimpleQA, Trinity Large Preview (Table 4) | Hallucination |
| 17 Feb 2026 | GLM-5 technical report | 36.9 | SimpleQA, World Knowledge panel (Figure 11) | Hallucination |
| 4 Feb 2026 | | 74 | SimpleQA (Table 2) | Capabilities |
| 27 Oct 2025 | GPT-5 system card addendum | 44 | SimpleQA, accuracy, gpt-5-oct-3 (Table 4) | Hallucination |
| 29 Sep 2025 | | 97.1 | SimpleQA (Acc.), search agent, DeepSeek-V3.2-Exp (Table 1) | Hallucination |
| 29 Sep 2025 | Claude Sonnet 4.5 system card | 24.6 | Simple-QA correct answer rate, with thinking, no tools, graded by Claude Sonnet 4. Incorrect 24.6%, uncertain 50.8%. Without thinking correct 17.1%, incorrect 20.8% (Figure 3.2.A) | Hallucination |
| 26 Sep 2025 | | 25.3 | Factuality SimpleQA (Table, p.4) | Capabilities |
| 25 Aug 2025 | Hermes 4 405B technical report | 25.8 | SimpleQA, reasoning mode (Table 3). Non-reasoning 22.1 | Hallucination |
| 8 Aug 2025 | GLM-4.5 technical report | 26.4 | SimpleQA (Correct) (Table 6) | Hallucination |
| 8 Aug 2025 | GLM-4.5-Air technical report | 14.5 | SimpleQA (Correct) (Table 6) | Hallucination |
| 7 Aug 2025 | GPT-5 system card | 55 | SimpleQA (no web), accuracy (Table 8) | Hallucination |
| 7 Aug 2025 | GPT-5 nano system card | 11 | SimpleQA (no web), accuracy, gpt-5-thinking-nano (Table 8) | Hallucination |
| 7 Aug 2025 | GPT-5 mini system card | 22 | SimpleQA (no web), accuracy, gpt-5-thinking-mini (Table 8) | Hallucination |
| 5 Aug 2025 | gpt-oss-20b model card | 6.7 | SimpleQA, accuracy, no browsing (Table 9) | Hallucination |
| 5 Aug 2025 | gpt-oss-120b model card | 16.8 | SimpleQA, accuracy, no browsing (Table 9) | Hallucination |
| 21 Jul 2025 | Kimi K2 technical report | 31 | SimpleQA (Correct) (Table 3) | Hallucination |
| 17 Jul 2025 | ChatGPT agent system card | 91.4 | SimpleQA, accuracy, with browsing (Table 4) | Hallucination |
| 7 Jul 2025 | | 54 | SimpleQA, F1 (Table 3) | Capabilities |
| 7 Jul 2025 | | 26.9 | SimpleQA, F1 (Table 3) | Capabilities |
| 29 Jun 2025 | | 45.9 | SimpleQA (Table 5) | Hallucination |
| 16 Jun 2025 | | 18.5 | SimpleQA (Table 2) | Hallucination |
| 30 Apr 2025 | | 86.3 | SimpleQA (with SerpApi), retrieval-augmented, GPT-4o judge, +/-1.0 (Table 1) | Capabilities |
| 29 Apr 2025 | | 29.7 | SimpleQA (Table, p.4) | Capabilities |
| 28 Apr 2025 | | 52.9 | SimpleQA (Table, p.4, column Gemini 2.5 Pro Experimental 03-25) | Capabilities |
| 16 Apr 2025 | o4-mini system card | 20 | SimpleQA, accuracy (Table 4) | Hallucination |
| 16 Apr 2025 | o3 system card | 49 | SimpleQA, accuracy (Table 4) | Hallucination |
| 15 Apr 2025 | | 29.9 | SimpleQA, no search (Table, p.3, column Gemini 2.0 Flash (GA)) | Capabilities |
| 10 Apr 2025 | | 21.7 | SimpleQA, no search (Table, p.3) | Capabilities |
| 10 Apr 2025 | | 12.9 | SimpleQA (Table 2) | Hallucination |
| 25 Mar 2025 | | 4 | SimpleQA, IT, zero-shot (Table 6) | Capabilities |
| 25 Mar 2025 | | 10 | SimpleQA, IT, zero-shot (Table 6) | Capabilities |
| 25 Mar 2025 | | 2.2 | SimpleQA, IT, zero-shot (Table 6) | Capabilities |
| 25 Mar 2025 | | 6.3 | SimpleQA, IT, zero-shot (Table 6) | Capabilities |
| 20 Jan 2025 | | 30.1 | SimpleQA (Correct), DeepSeek-R1 (Table 8, same as final column of Table 3) | Hallucination |
| 14 Jan 2025 | | 23.7 | SimpleQA (Table 8) | Hallucination |
| 26 Dec 2024 | | 24.9 | SimpleQA (Correct), DeepSeek-V3 (Table 6) | Hallucination |
| 12 Dec 2024 | | 3 | SimpleQA, simple-evals F1 (Table 1) | Hallucination |
| 5 Dec 2024 | o1 system card | 47 | SimpleQA, accuracy (Table 3) | Hallucination |
| 12 Sep 2024 | o1-preview system card | 42 | SimpleQA, accuracy (Table 2) | Hallucination |
| 12 Sep 2024 | o1-mini system card | 7 | SimpleQA, accuracy (Table 2) | Hallucination |
Versions
We switch the top row to each new version when it comes out. Open it for one row per version. An old version stays in play while people still test it, so whoever first takes it past 85% gets credit for closing it out.
More in Factuality
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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%
- 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%
- TruthfulQA Fading Models answer 817 questions across 38 categories that are written to elicit common misconceptions. Scoring checks for truthful answers, often in multiple-choice form.
MAI-Thinking-1 88%