Accuracy
Every number on this page comes straight from the measurement file of the Engine that judges your Scans. We never type them in by hand, and they change only when we measure again.
How we measure
We test on our own evaluation set: about 5,000 human texts and 2,200 AI texts per language. The human texts were all written before ChatGPT existed: news, encyclopedia articles and research abstracts, including English written by authors in Spain and Latin America. The AI texts come from twelve current models made by nine companies, in five genres, and some of them were paraphrased by a second model to hide their origin.
Half of the set sets the thresholds. The other half, which is never used for anything else, gives the rates below. Each rate shows how many texts it rests on and a 95% confidence interval.
The thresholds are cautious on purpose. Likely AI starts at the score that only 1 in 100 human texts reaches in our tests. Likely human ends at the score that only 1 in 100 AI texts falls below. Anything in between is Unclear, and that is an honest answer.
Engine 2026.11-oculus-v0
English: Passes the launch gate
| Likely AI above | 0.941 |
|---|---|
| Likely human below | 0.123 |
| Human texts called Likely AI | 1.2 % (0.9–1.7) · 2490 texts |
| Raw AI texts called Likely AI | 89.2 % (87.1–91.0) · 961 texts |
| Paraphrased AI texts called Likely AI | 90.1 % (83.5–94.2) · 121 texts |
Human texts called Likely AI, by source
| English research abstracts by authors in Spain and Latin America, 2010–2021 | 5.1 % (3.6–7.2) · 585 texts |
| Research papers by non-native English authors, 2015–2021 (TextSight benchmark) | 0.0 % (0.0–4.2) · 88 texts |
| English Wikipedia revisions before 2022 (TextSight benchmark) | 0.0 % (0.0–4.9) · 75 texts |
| English Wikinews, 2004–2021 | 0.0 % (0.0–0.5) · 838 texts |
| English Wikipedia, March 2022 | 0.0 % (0.0–0.4) · 904 texts |
Raw AI texts called Likely AI, by model
anthropic/claude-haiku-5.5 | 93.1 % (86.4–96.6) · 101 texts |
anthropic/claude-sonnet-5.5 | 71.4 % (52.9–84.8) · 28 texts |
deepseek/deepseek-v4.1-flash-1017 | 86.8 % (79.9–91.6) · 129 texts |
google/gemini-3.7-flash | 92.5 % (83.7–96.8) · 67 texts |
google/gemini-4-argon | 89.3 % (72.8–96.3) · 28 texts |
meta-llama/llama-4-maverick | 92.1 % (84.6–96.1) · 89 texts |
mistralai/mistral-small-2603 | 100.0 % (96.9–100.0) · 119 texts |
openai/gpt-6-luna | 85.7 % (78.3–90.9) · 119 texts |
openai/gpt-6.1-terra | 66.7 % (47.8–81.4) · 27 texts |
qwen/qwen3.8-flash | 100.0 % (96.3–100.0) · 101 texts |
x-ai/grok-4.3 | 89.2 % (75.3–95.7) · 37 texts |
z-ai/glm-5.3 | 76.7 % (68.3–83.5) · 116 texts |
Spanish: Passes the launch gate
| Likely AI above | 0.132 |
|---|---|
| Likely human below | 0.088 |
| Human texts called Likely AI | 1.4 % (1.0–2.0) · 2434 texts |
| Raw AI texts called Likely AI | 99.5 % (98.8–99.8) · 1005 texts |
| Paraphrased AI texts called Likely AI | 99.2 % (95.7–99.9) · 129 texts |
Human texts called Likely AI, by source
| Spanish Wikinews, 2004–2021 | 1.4 % (1.0–2.0) · 2434 texts |
Raw AI texts called Likely AI, by model
anthropic/claude-haiku-5.5 | 100.0 % (97.2–100.0) · 131 texts |
anthropic/claude-sonnet-5.5 | 96.6 % (82.8–99.4) · 29 texts |
deepseek/deepseek-v4.1-flash-1017 | 100.0 % (97.2–100.0) · 131 texts |
google/gemini-3.7-flash | 100.0 % (95.0–100.0) · 73 texts |
google/gemini-4-argon | 100.0 % (87.9–100.0) · 28 texts |
meta-llama/llama-4-maverick | 100.0 % (95.8–100.0) · 88 texts |
mistralai/mistral-small-2603 | 100.0 % (96.8–100.0) · 117 texts |
openai/gpt-6-luna | 98.4 % (94.4–99.6) · 127 texts |
openai/gpt-6.1-terra | 95.0 % (76.4–99.1) · 20 texts |
qwen/qwen3.8-flash | 100.0 % (97.0–100.0) · 124 texts |
x-ai/grok-4.3 | 100.0 % (92.3–100.0) · 46 texts |
z-ai/glm-5.3 | 98.9 % (94.0–99.8) · 91 texts |
What these numbers do not cover
- Our human texts include no student essays yet, because the collections we found do not allow commercial use. Student writing may behave differently.
- Research abstracts written in English by authors whose first language is Spanish are flagged more often than other human texts (see the table by source). If you write in your second language, read an Unclear or Likely AI Verdict with that in mind.
- No detector, this one included, can prove who wrote a text, and we cannot predict what Turnitin or any other tool will say.