# MAGE AI detector accuracy test

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

> MAGE caught 46.4% of AI-written texts in our test, fewer than half, and flagged 19.0% of human texts as AI. It did especially badly on encyclopedia writing, flagging 40.0% of human Wikipedia excerpts, and it caught only 20.6% of AI texts under 200 words.

Verdict: A research detector that misses most AI text from current models and flags a fifth of human writing, so it is not useful for checking real documents.

| Measure | Result |
|---|---|
| Catches AI text | 46.4% (234 of 504) |
| Flags human text | 19.0% (24 of 126) |
| Catches humanized AI text | 23.8% |
| AUROC | 0.666 |
| Catches Claude Fable 5.1 | 28.6% |
| Catches Claude Haiku 5.5 | 66.7% |
| Catches Claude Opus 5.5 | 45.2% |
| Catches Claude Sonnet 5.5 | 45.2% |
| Flags human text: Academic abstracts | 12.0% |
| Flags human text: Q&A answers | 7.1% |
| Flags human text: Encyclopedia articles | 40.0% |
| Flags human text: Fiction | 4.2% |
| Flags human text: News reports | 33.3% |

## What MAGE is

MAGE comes from the paper "MAGE: Machine-generated Text Detection in the Wild" by Li and colleagues, published at ACL 2024. The detector is a Longformer model trained on text from many earlier language models. We used the exact decision rule from the authors' own deployment code, which flags a text when the model's machine score passes 3.0858, and cleaned each text the way their code recommends.

## Results

MAGE caught 46.4% of AI texts. It did best on news, catching 91.7% of AI news articles, and worst on academic abstracts, at 12.0%. It caught 66.7% of Claude Haiku 5.5 texts and 28.6% of Claude Fable 5.1 texts.

On human writing it flagged 19.0% overall, with encyclopedia articles at 40.0% and news at 33.3%. Fiction and Q&A answers were rarely flagged.

## Length and editing

Short texts were MAGE's biggest weakness. Its catch rate rose from 20.6% under 200 words to 57.6% at 300 words or more. After a humanizer rewrite it caught 23.8% of Claude Opus 5.5 texts, down from 45.2%.

It ran at 0.39 seconds per 1,000 words on an Apple M4 Pro.

## Questions people ask

### Is the MAGE AI detector accurate?

Not on modern AI text. It caught 46.4% of AI texts and flagged 19.0% of human texts in our test, a balanced accuracy of 63.7%.

### Does MAGE work on short texts?

Poorly. It caught 20.6% of AI texts under 200 words, against 57.6% of those with 300 words or more.