Pangram Outperforms AI Detectors in Accuracy and Cost

Pangram Leads AI Text Detection with Unmatched Accuracy

A comprehensive study by the University of Chicago has identified Pangram as the most reliable and cost-effective AI text detection tool currently available. The research compared multiple detection systems across six text categories and four major language models.

Methodology: Rigorous Testing Framework

The team assembled a dataset of 1,992 human-written texts spanning:

  • Amazon product reviews
  • Blog posts
  • News articles
  • Novel excerpts
  • Restaurant reviews
  • Resumes

These were paired with AI-generated counterparts from GPT-4.1, Claude Opus4, Claude Sonnet4, and Gemini 2.0 Flash. Performance was measured using:

  • False Positive Rate (FPR): Human texts misclassified as AI
  • False Negative Rate (FNR): Undetected AI-generated content

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Performance Breakdown: Pangram Dominates Rankings

The findings show Pangram achieved:

  • Near-perfect detection (0% errors) for medium/long texts
  • Minimal error rates (<0.01) even in short samples
  • Consistent performance across all four AI models tested

The open-source RoBERTa-based detectors performed worst, incorrectly flagging 30%-69% of human writing as machine-generated.

Model-Specific Detection Variations

The study revealed significant differences in how detectors handle outputs from various AI systems:

Detector Strengths Weaknesses

The research notes that while all detectors perform well on long-form content like novels, Pangram maintains superior accuracy even with brief restaurant reviews.

Anti-Evasion Capabilities Tested

The team evaluated systems against StealthGPT, a tool designed to bypass detection:

  • Pangram's performance remained stable (<5% variance)
  • Competitors showed 20%-40% accuracy drops Image

    Economic Advantages Emerge

The cost analysis revealed:

  • Pangram identifies AI content for just $0.0228 per sample
  • Half the cost of OriginalityAI ($0.045)
  • One-third GPTZero's expense ($0.068)

The "Policy Cap" feature allows institutions to set maximum acceptable error rates (e.g., 0.5%), with Pangram being the only system maintaining high accuracy under such constraints.

Key Points:

  1. Pangram demonstrates superior accuracy across all tested text types and lengths
  2. Open-source detectors performed poorly compared to commercial solutions
  3. Detection effectiveness varies significantly by source AI model
  4. Cost analysis shows Pangram offers best value at $0.0228 per accurate detection
  5. Researchers recommend regular "stress tests" as AI generation tools evolve

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