⚖️ Free2AI Nexus Index

The Comprehensive Impact Index for Open-Source AI

The S&P 500 of Open-Source AI

🎯 Our Mission

FNI (Free2AI Nexus Index) is not just another leaderboard. It's an objective, transparent, and verifiable comprehensive evaluation index. We believe: Credibility = Explainability. Only when we can clearly tell users "why it's ranked #1" can we be considered authoritative.

📐 The Formula

FNI = P × 25% + V × 25% + C × 30% + U × 20%
🔥

P - Popularity (25%)

Community recognition

  • • HuggingFace Likes
  • • Downloads
  • • GitHub Stars
🚀

V - Velocity (25%)

Recent growth trends

  • • 7-day growth rate
  • • Community activity
  • • Rising star detection
🛡️

C - Credibility (30%)

Academic & engineering endorsement

  • • ArXiv paper association
  • • README completeness
  • • Author/institution reputation
🔧

U - Utility (20%)

Real-world usability

  • • Ollama support
  • • GGUF format
  • • Runtime ecosystem

🏛️ Three Pillars of Fairness

📜 Forensic Data Traceability

All data has a complete audit trail (source_trail). When you question rankings, we can show raw data snapshots, collection timestamps, and content hashes. Data is traceable, conclusions are verifiable.

⚖️ Radical Neutrality

The FNI scoring system (L5 Analyst) and commercial recommendation system (L6 Merchant) are physically separated. We explicitly prohibit "pay-to-rank." Commercial recommendations are based on technical matching, not bidding.

🔮 Holistic Perspective

We don't just look at benchmarks. A model with high benchmark scores but terrible documentation will be appropriately penalized in FNI. We focus on real-world usability, not just ideal laboratory metrics.

🛡️ Anti-Manipulation Mechanisms

We detect anomalous behavior through multi-dimensional cross-validation:

  • ❌ Anomalous Growth Detection: Alerts triggered when 7-day growth exceeds 10x the average
  • ❌ Ratio Anomaly Detection: Download/like ratios outside reasonable ranges
  • ❌ Content Match Detection: High popularity but no substantial content

Anomalous models are flagged for manual review and their scores are appropriately adjusted.

🔓 Open Source Commitment

FNI's calculation logic is completely open source:

// github.com/mosesy5688-cell/ai-nexus/scripts/calculate-fni.js

Anyone can audit our algorithm and propose improvements. Transparency is the foundation of trust.

Public Trust Is Our Currency
Explainability Is Our Moat

Fair · Transparent · Explainable

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