Version matching
Gemini 1.5 vs. 2.0 vs. 2.5 indication when signal supports it.
Model-specific · Gemini
Gemini AI detector, tuned for Google's model family.
Gemini output patterns differ from both GPT and Claude. This detector is weighted for Gemini, including the long-context 1M-token variants.
- Gemini 1.5 Pro, 2.0, 2.5
- Long-context-aware scoring
- Free, 5,000 characters, no account
About the Gemini detector
Gemini is Google's model family, and like the GPT and Claude families it has its own fingerprint. The detectors best-known for AI-essay detection were trained primarily on GPT output; those detectors underperform on Gemini. Our Gemini-specific classifier closes that gap.
What Gemini output looks like
- Structured bullet defaults. Gemini defaults to structured output more often than the GPT baseline, headers, bullets, numbered lists. Often removed in edited output, but traces remain in sentence rhythm.
- Factual density. Gemini leans toward fact-dense prose, with more specific numbers and dates than the GPT baseline. This is a tell when the context doesn't call for it.
- Closer patterns. Specific closing constructions ("I hope this analysis is helpful" or "Please let me know if you'd like me to elaborate") appear at higher rates than GPT.
- Long-context uniformity. Gemini's 1M-token context means outputs can reference material across very long inputs. When the reference pattern is too mechanical, that's a signal.
Versions supported
Gemini 1.5 Pro, 1.5 Flash, 2.0 Pro, 2.0 Flash, 2.5 Pro. Gemini 2.5 is the current generation and the hardest to classify confidently.
Failure modes
Same story as the other model-specific detectors: strong stylistic prompting, heavy editing, and very short passages degrade confidence. Gemini-specific failure mode: when Gemini is asked to produce code-heavy or highly structured output (which it's often used for), the prose-detector has less signal to work with. Our result UI flags low-signal cases.
Privacy
Pasted text is stored 30 days and deleted. We do not train on user submissions.
Long-context-aware
The classifier handles longer passages that reference material across the input. Gemini's strength and its tell.
Structure-pattern weighting
Appropriate weight on Gemini's structured-output tendencies instead of reading structure as formality.
Gemini-family performance
Multimodal-trained text leaves a different fingerprint.
0.91
AUC vs Gemini 1.5/2.5
Lower than GPT/Claude due to varied output styles.
1.5 Pro → 2.5
Versions covered
Including Flash variants and multimodal output.
Long-ctx
Tuned for
Gemini's distinct long-context summarization patterns.
Q4 2025
Last retrain
Fresh signal coverage on 2.5 Pro release.
Frequently asked questions
Does this work on Gemini output from Google Workspace (Docs, Gmail)?
Yes, same model family, same output patterns. Workspace integration doesn't change the underlying text.
What about Gemini Advanced / Gemini 2.5 Pro specifically?
Tuned for. Confidence on version best-match is highest for 1.5 and 2.0 and lower for 2.5, we surface that in the result.
How does this compare to running the generic detector?
On Gemini-specific input, this detector is measurably more accurate. On non-Gemini input, the generic detector is the right choice. Use /ai-detector to pick.
Is this free?
Yes. Anonymous use up to 5,000 characters and 5 checks/day. A free account raises limits.
Ready to check passage?
Free up to 3,000 characters. No account required for a single check.
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