Detecting Claude, Gemini, and GPT-5 Writing

Why model-specific detection matters

AI writing is no longer tied to one model. A document may include text drafted with Claude, Gemini, GPT-5, another assistant, or several tools across revision stages. Model-specific pages help searchers understand the limits of detection and the right review process.

Use the Claude detector, Gemini detector, and GPT-5 detector resources as entry points for model-aware review. For broad checks, use the main AI detector.

What changes between models

Different assistants can produce different sentence rhythm, hedging patterns, citation behavior, and summary style. Those signals are useful, but they are not identity proofs. A careful review asks whether the passage is unusually generic, whether sources are verifiable, and whether the style matches the writer.

How to avoid overclaiming

Do not say that a detector proves a specific model wrote the text. Instead, describe whether the text resembles model-generated writing and which review evidence supports that concern. This protects students, teams, and publishers from making decisions based on a single label.

FAQ

Can detection identify the exact model?

Usually no. A detector can show that a passage resembles AI-generated writing, but exact model attribution needs much stronger evidence. Treat model pages as workflow guidance, not forensic proof.

What if text was edited after AI drafting?

Mixed authorship is common. Review the final draft, the revision trail, and the claims inside the text. Heavy human editing may reduce AI-like signals while still requiring disclosure in some policies.

How should teams document model concerns?

Use neutral wording such as AI-like writing patterns or model-assisted drafting indicators. Avoid claiming that a specific model wrote the text unless the author disclosed it or tool logs confirm it.