# Desklib vs Fast-DetectGPT, which AI detector is more accurate?

Source: https://toolbenchmarks.com/compare/desklib-vs-fast-detectgpt/  
Tested: 30 October 2026. Publisher: Tool Benchmarks. Data licence: CC BY 4.0.

> For most readers Desklib, because it wrongly flags less human writing, 6.3% of human texts against 15.9% for Fast-DetectGPT, and its AUROC was higher, 0.877 against 0.815. Fast-DetectGPT caught more AI text, 68.1% against 58.3%. Their balanced accuracy was almost the same, 76.1% and 76.0%, and Fast-DetectGPT's threshold was tuned on our calibration split.

| Measure | Desklib AI text detector | Fast-DetectGPT (Qwen2.5-1.5B) |
|---|---|---|
| Balanced accuracy | 76.0% | 76.1% |
| Catches AI text | 58.3% | 68.1% |
| Flags human text | 6.3% | 15.9% |
| Catches humanized AI text | 32.5% | 47.6% |
| AUROC | 0.877 | 0.815 |
| Flags human text: Academic abstracts | 8.0% | 40.0% |
| Flags human text: Q&A answers | 3.6% | 21.4% |
| Flags human text: Encyclopedia articles | 0.0% | 8.0% |
| Flags human text: Fiction | 0.0% | 0.0% |
| Flags human text: News reports | 20.8% | 8.3% |

## Two routes to the same score

Fast-DetectGPT ranks first on our leaderboard and Desklib second, with balanced accuracy of 76.1% against 76.0%. They get there in opposite ways. Fast-DetectGPT catches more AI text, and Desklib flags less human text.

One caveat favours Desklib. Fast-DetectGPT has no published threshold for the model we ran, so we chose one on our 144 calibration texts, which are kept out of every reported number. Desklib used the threshold from its model card. AUROC, which does not depend on any threshold, puts Desklib ahead at 0.877 against 0.815.

## Results by kind of writing

Genre by genre, the two trade places. On academic abstracts Fast-DetectGPT flagged 40.0% of the human ones, against Desklib's 8.0%, while catching 84.0% of AI abstracts against 50.0%. Its method treats predictable wording as a sign of AI, and abstracts are written in a predictable register, which is the likely cause. Forum answers lean the same way, with 21.4% of human answers flagged by Fast-DetectGPT and 3.6% by Desklib.

News goes the other way. Fast-DetectGPT flagged 2 of 24 human news reports and Desklib 5, while both caught most AI news, 93.8% and 90.6%. In fiction neither flagged a single human passage, and Fast-DetectGPT caught 62.5% of the AI ones where Desklib caught 20.8%.

Fast-DetectGPT also caught more of the text that gives Desklib trouble. It caught 46.0% of Claude Fable 5.1 texts against 32.5%, and 47.6% of humanized Claude Opus 5.5 texts against 32.5%.

## Where Fast-DetectGPT costs more

It flagged 17 of 30 famous public-domain texts, more than any detector except TMR, including Hamlet's soliloquy and The Federalist No. 10, which no other detector flagged. Desklib flagged 4. It was also the one detector of the pair that changed with formatting: with line breaks removed it caught 57.9% of AI texts, while Desklib stayed at 58.3%.

It is a zero-shot method that runs the Qwen2.5-1.5B language model, the slowest setup we tested at 0.99 seconds per 1,000 words. Desklib, a trained classifier, took 0.57.

## Which to use for what

If a flag could count against a student or an employee, use Desklib. If you are screening your own content pipeline for AI text and a false alarm only costs a second look, Fast-DetectGPT catches more, especially in fiction and news. Neither is evidence on its own: Desklib still flagged 8 of 126 human texts. See the [Desklib](/ai-detectors/desklib/) and [Fast-DetectGPT](/ai-detectors/fast-detectgpt/) pages, and the [paragraph break guide](/guides/paragraph-breaks-change-ai-detector-results/) for the formatting effect.

## Questions people ask

### Is Desklib or Fast-DetectGPT the best AI detector?

They finished first and second on balanced accuracy, Fast-DetectGPT at 76.1% and Desklib at 76.0%. Desklib flags fewer human texts and Fast-DetectGPT catches more AI text, so the better one depends on which mistake costs you more.

### Which is better for academic writing?

Desklib makes far fewer false accusations there. Fast-DetectGPT flagged 10 of 25 human academic abstracts and Desklib 2. Fast-DetectGPT did catch more AI abstracts, 84.0% against 50.0%.

### Which is better for fiction?

Fast-DetectGPT. Neither flagged any human fiction, and Fast-DetectGPT caught 62.5% of AI fiction passages against Desklib's 20.8%.