Free Gemini Detector.

Gemini text in the wild

Gemini sits inside the Google ecosystem, which gives its output a particular distribution: Workspace documents, drafted emails in Gmail, summaries pulled into Docs, and school writing from students who live in Google’s tools. If your suspect text came out of that world, this is the page for it. The detector reads the same statistical signals as for any model: uniformity of rhythm, predictability of phrasing, the evenness that machine drafting leaves behind. Unedited Gemini longform lands in the AI band like its peers.

Gemini, Docs and the classroom

A common scenario: a student drafts with Gemini directly inside Google Docs, polishes lightly, submits. Two separate signals exist in that workflow and they answer different questions. The detector score on the final text tells you how machine-like the prose reads. The Docs version history tells you how the document came to exist, and a file that appeared in three large pastes reads very differently from one with two hundred incremental edits. Teachers comparing both signals make better calls than either alone, which is why we wrote up the Google Docs situation and what Canvas can actually see.

Short snippets and the sample floor

Gemini powers a lot of short-form output: AI Overview snippets, quick email replies, two-line summaries. Most of it falls under this tool’s 120-character floor, and that is by design rather than limitation. No detector can score a sentence meaningfully; tools that do are reading noise. For anything paragraph-length and up, paste it in. For the attribution question, the honest answer is the same as on every page of this site: the dial reads machine versus human, not which machine. See how detection works for why.

Checking Workspace-origin text without folklore

Because Gemini lives inside Docs and Gmail, this page attracts a specific anxiety: can the recipient tell the draft came from the assistant button. Strip the folklore and three facts remain. There is no watermark or metadata flag in exported Gemini text, so nothing in the file announces its origin. The prose itself carries ordinary machine texture, so a detector reads it like any assistant output: high when unedited, lower as you revise. And inside school or company accounts, document history often tells a richer story than any score, because a file that materialized in one paste reads differently from one that grew by edits. The practical guidance follows directly: revise drafts into your own rhythm, keep history on for anything that might be questioned, and use the dial here to see how much machine pattern your revision actually removed.