AI text detector

DeepSeek detector

DeepSeek’s free chatbot and open-weight models made capable AI writing available everywhere, including in apps that never mention it. Paste a text to check it for the signs of AI writing.

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Open models everywhere

DeepSeek, a Chinese AI lab, released chat and reasoning models in late 2024 and early 2025 that matched leading commercial systems at a fraction of the cost, and published the weights openly. Its free app briefly topped app-store charts, and its models were quickly built into thousands of products, from writing assistants to customer-service bots. Together with other open families such as Qwen, Llama and gpt-oss, they mean a growing share of AI text comes from models people run themselves.

For detection, the origin rarely matters: these models learned from similar data and similar human feedback, so they share most of the habits Wikipedia editors catalogued. GPTTrace doesn’t try to name the model; it reports the signs and how strongly they point to AI writing.

Signs typical of DeepSeek output

  • Reasoning leftovers. Paragraphs that think aloud — “Hmm, the user wants…”, “Wait, but…”, “Let me double-check” — copied from a reasoning model’s visible chain of thought.
  • Exhaustive structure. Numbered sections with bold headings, sub-bullets, a comparison table and a final summary, even for simple questions.
  • Familiar vocabulary. The same significance and transition phrases as other assistants: “crucial”, “comprehensive”, “Additionally”, “In summary”.
  • Markdown and emoji. Headings, bold labels and emoji bullets pasted into places that don’t render them.

GPTTrace highlights each of these in your text. For a stronger check on longer texts, switch on Deep scan, which adds a neural model trained on output from many different generators.

Bots and automated content

Because open models are cheap to run at scale, they power much of the automated content online: spam blogs, review farms, reply bots and auto-generated product descriptions. Individual pieces may be short, but patterns across many texts — identical structures, the same phrases recurring, posting at machine speed — are more telling than any single detector score. If you moderate a community or marketplace, look at accounts as well as posts.

Checking a translated or bilingual text

Many people use DeepSeek and other assistants to translate their own writing into English. Machine-translated human writing can show some AI-writing signs, especially smooth, formal phrasing, without being AI-authored in the usual sense. If a text was written in another language and translated, say so when you check it, and judge it by the ideas and sources rather than by its English style. GPTTrace’s statistics are designed for text written in English and are less reliable on translations.

If you are unsure, ask the writer for the original-language version: a person who translated their own work can usually provide it at once.

How accurate is it? Our measured numbers

We test GPTTrace on labelled text samples and publish the results, including where it does badly. It is tuned to keep false accusations rare, so it misses some AI content rather than flag real work.

standard text check: AUC 0.795 (cross-validated)

2,467 labelled samples (1,258 AI, 1,209 human), run 2026-10-08. At the “Likely AI” line it caught 34% of AI samples and wrongly flagged 5% of human ones.

SourceTruthSamplesResult at “Likely AI”
gpt-oss-120bAI12100% caught
qwen-3.8-27bAI863% caught
pd-literatureHuman3061% wrongly flagged
human-pmc-eslHuman1835% wrongly flagged
human-wikipedia-pre2022Human1558% wrongly flagged
hc3-open_qaHuman714% wrongly flagged
hc3-wiki_csaiHuman5586% wrongly flagged

text check with deep scan: AUC 0.91 (cross-validated)

2,467 labelled samples (1,258 AI, 1,209 human), run 2026-10-08. At the “Likely AI” line it caught 56% of AI samples and wrongly flagged 5% of human ones.

SourceTruthSamplesResult at “Likely AI”
gpt-oss-120bAI12100% caught
qwen-3.8-27bAI875% caught
pd-literatureHuman3060% wrongly flagged
human-pmc-eslHuman1831% wrongly flagged
human-wikipedia-pre2022Human1551% wrongly flagged
hc3-open_qaHuman70% wrongly flagged
hc3-wiki_csaiHuman5589% wrongly flagged

Data sources and method: methodology & accuracy.

Frequently asked questions

Is DeepSeek’s writing different from ChatGPT’s?
Somewhat. DeepSeek’s chat models were trained in part to imitate the style of leading assistants, so they share many habits — structured answers, bold labels, summary endings. They also tend toward long, very thorough answers and sometimes slip into Chinese-influenced phrasing or terms.
What are “reasoning traces”?
DeepSeek’s R1-style reasoning models write out a long internal monologue before answering (“Okay, so the user is asking… Wait, let me check…”). When people copy the whole output, that monologue comes along, and it is an unmistakable sign of a reasoning model.
Do you test against open-weight models?
Our evaluation includes text from open-weight models such as gpt-oss and Qwen alongside commercial ones. The per-source numbers are in the accuracy table on this page.
Can DeepSeek text be detected when run locally?
Yes — running a model on your own computer doesn’t change how it writes. Local runs simply add no metadata, which text never carries anyway.