# Fakespot AI text detector accuracy test

Source: https://toolbenchmarks.com/ai-detectors/fakespot/  
Tested: 30 October 2026. Publisher: Tool Benchmarks. Data licence: CC BY 4.0.

> The Fakespot AI text detector caught 66.3% of AI-written texts in our test but flagged 34.9% of human texts as AI. News writing fared worst, with 70.8% of human news reports called AI-written, all of them published years before ChatGPT.

Verdict: Catches a fair share of AI text, but it flags about a third of human writing and most human news, so its verdicts cannot be trusted alone.

| Measure | Result |
|---|---|
| Catches AI text | 66.3% (334 of 504) |
| Flags human text | 34.9% (44 of 126) |
| Catches humanized AI text | 47.6% |
| AUROC | 0.741 |
| Catches Claude Fable 5.1 | 50.0% |
| Catches Claude Haiku 5.5 | 81.0% |
| Catches Claude Opus 5.5 | 65.1% |
| Catches Claude Sonnet 5.5 | 69.0% |
| Flags human text: Academic abstracts | 12.0% |
| Flags human text: Q&A answers | 39.3% |
| Flags human text: Encyclopedia articles | 40.0% |
| Flags human text: Fiction | 12.5% |
| Flags human text: News reports | 70.8% |

## What it is

This RoBERTa-base model comes from Fakespot, the team at Mozilla that built tools for spotting fake reviews. Its model card ships a text cleaning function, which we applied before scoring, and we used the standard probability threshold of 0.5.

## Results

Fakespot caught 66.3% of AI texts. It did best on encyclopedia articles and news, catching 95.0% and 100.0% of the AI versions, and worst on academic abstracts, at 33.0%. Among the models, it caught 81.0% of Claude Haiku 5.5 texts and 50.0% of Claude Fable 5.1 texts.

It also flagged human writing in the same genres where it catches the most AI text, calling 70.8% of human news reports and 40.0% of human encyclopedia articles AI-written. It seems to react to the style of a genre more than to who wrote the text.

## Length and rewrites

Its catch rate climbed with length, from 43.3% for AI texts under 200 words to 76.6% for those of 300 words or more. False positives also rose with length: it flagged 57.1% of human texts of 300 words or more. Longer texts give it more of whatever it reacts to, in both directions.

After a humanizer rewrite, it caught 47.6% of Claude Opus 5.5 texts, down from 65.1%.

## Questions people ask

### Is the Fakespot AI detector accurate?

Not reliably. It caught 66.3% of AI texts and flagged 34.9% of human texts in our test, for a balanced accuracy of 65.7%.

### Why does Fakespot flag news articles?

We cannot see inside the model. Human news reports were its most flagged genre, at 70.8%, while it flagged only 12.0% of human academic abstracts and 12.5% of fiction, which suggests it reacts to the style of a genre more than to who wrote the text.

### Is the Fakespot detector fast?

Yes. It took 0.07 seconds per 1,000 words on an Apple M4 Pro, among the fastest in the test.