Best AI detector for forum posts and Q&A answers (tested)
Desklib is the best AI detector for forum posts and Q&A answers in our test. On Stack Exchange answers it reached a balanced accuracy of 73.2%, flagging 1 of 28 human answers while catching 50.0% of AI-written ones, so it still passed many AI answers as human. Fast-DetectGPT came second at 61.2% and flagged 6 of 28 human answers.
Tested
AI detectors ranked for forum posts and Q&A answers
| # | Detector | Balanced accuracy | Catches AI text | Flags human text |
|---|---|---|---|---|
| 1 | Desklib AI text detector | 73.2% | 50.0% | 3.6% |
| 2 | Fast-DetectGPT (Qwen2.5-1.5B) | 61.2% | 43.8% | 21.4% |
| 3 | MAGE | 57.1% | 21.4% | 7.1% |
| 4 | Fakespot AI text detector | 50.4% | 40.2% | 39.3% |
| 5 | TMR (Target Mining RoBERTa) | 50.0% | 100.0% | 100.0% |
| 6 | OpenAI RoBERTa detector | 44.6% | 0.0% | 10.7% |
| 7 | E5-small LoRA detector | 42.4% | 59.8% | 75.0% |
Numbers behind this chart
| Item | Rate | Texts | 95% interval |
|---|---|---|---|
| Desklib AI text detector | 3.6% | 1 of 28 | 0.6 to 17.7% |
| Fast-DetectGPT (Qwen2.5-1.5B) | 21.4% | 6 of 28 | 10.2 to 39.5% |
| MAGE | 7.1% | 2 of 28 | 2.0 to 22.6% |
| Fakespot AI text detector | 39.3% | 11 of 28 | 23.6 to 57.6% |
| TMR (Target Mining RoBERTa) | 100.0% | 28 of 28 | 87.9 to 100.0% |
| OpenAI RoBERTa detector | 10.7% | 3 of 28 | 3.7 to 27.2% |
| E5-small LoRA detector | 75.0% | 21 of 28 | 56.6 to 87.3% |
Why Q&A answers are hard to judge
A good Stack Exchange answer and a chatbot reply do the same job. Both explain something to a stranger who asked, open with the answer, walk through an example and speak to the reader as “you”. Detectors seem to find the two hard to separate, and two of them flagged human answers more often than AI ones, which is worse than chance. E5-small LoRA flagged 75.0% of human answers but caught only 59.8% of AI ones. The OpenAI RoBERTa detector caught 0 of 112 AI answers and flagged 3 of 28 human ones.
The human answer that drew the most false flags, “Is asking to pay off principal first a placebo?”, is a 253-word answer posted in 2016 on Stack Exchange’s personal finance site that walks through a mortgage example step by step. Six of the seven detectors flagged it as AI. Desklib was the only one that passed it.
How far Desklib gets you
Desklib flagged a single human answer, a worldbuilding reply about how a society that cannot count could hold a vote, which MAGE, TMR and E5-small LoRA also flagged. That gives it a 3.6% false positive rate on this genre.
Its weakness is the other side. It caught 50.0% of AI answers, with a 95% interval from 40.9% to 59.1%, so a clean result says very little. Fast-DetectGPT, the overall co-leader, did worse here. It caught 43.8% of AI answers, its lowest catch rate in any genre, and flagged 6 of 28 human answers, even though its threshold was tuned on our calibration split and the others ran on their authors’ defaults.
Using a detector on a forum or Q&A site
For moderators, Desklib is the clear pick. MAGE also flagged few human answers, 2 of 28, but it caught only 21.4% of AI ones. Treat a Desklib flag as one signal among others, such as posting speed, account history and whether the answer fits the question. Our false positives page shows how many genuine human texts the other detectors flagged across every genre, and the leaderboard has the overall ranking.
Questions people ask
Can AI detectors spot AI-written forum answers?
Not reliably. Desklib, the best detector on our Stack Exchange set, caught 50.0% of AI answers written by four Claude models. The OpenAI RoBERTa detector caught none of 112.
Which AI detectors flag real forum posts?
TMR flagged all 28 human answers and E5-small LoRA flagged 21. Fakespot flagged 11 while catching only 40.2% of AI answers, which leaves it at 50.4% balanced accuracy, no better than a coin.
Is 1 false positive in 28 good enough for moderation?
It is the best result here, but 28 answers is a small sample. The 95% interval for Desklib's false positive rate runs from 0.6% to 17.7%, so do not ban or penalize a user on its verdict alone.