I've been testing AI content detectors for years - these are your best options in 2025 (www.zdnet.com)

ZDNET reran a practical head-to-head of AI content detectors in 2025 using five text samples (two human, three ChatGPT) and a >70% threshold to call a sample “AI” or “human.” Across 11 detectors and several chatbots, results were highly variable: Pangram and QuillBot scored 100% this round, GPTZero and Originality.ai around 80%, Hugging Face’s GPT‑2 detector ~60%, while BrandWell, Grammarly and Writer.com sat near 40% and Undetectable.ai plunged to 20%. Some prior winners slipped as vendors tightened free access (Monica and Writefull were dropped), and Copyleaks’ accuracy claims proved overstated. Notably, off-the-shelf chatbots outperformed many standalone detectors in these tests, suggesting conversational models could replace or supplement traditional detectors. For the AI/ML community this underscores two realities: detection remains brittle and transient, and an arms race between generators and detectors continues. Methodological details matter — ZDNET’s five-sample suite, repeated runs, and fixed probability cutoff make differences visible — but the inconsistent false positives (human text flagged as AI) and false negatives (AI text missed) mean institutional reliance on a single tool is unsafe. Practitioners and educators should treat detector outputs as signals, not proofs, prefer multi-tool or chatbot cross-checks, push for transparent benchmarks, and expect ongoing model updates to shift performance rapidly.