Model Registries

Overview

Model registries represent a foundational governance tool for managing risks from advanced AI systems. Like drug registries that enable pharmaceutical regulation or aircraft registries that support aviation safety, AI model registries would create centralized databases containing information about frontier AI systems—their capabilities, training details, deployment contexts, and safety evaluations. This infrastructure provides governments with the visibility necessary to implement more sophisticated AI governanceParameterAI GovernanceThis page contains only component imports with no actual content - it displays dynamically loaded data from an external source that cannot be evaluated. measures.

The policy momentum is significant. The U.S. Executive Order on AI (October 2023) mandated quarterly reporting for models trained above 10^26 FLOP. The EU AI ActPolicyEU AI ActComprehensive overview of the EU AI Act's risk-based regulatory framework, particularly its two-tier approach to foundation models that distinguishes between standard and systemic risk AI systems. ...Quality: 55/100 requires registration of high-risk AI systems and general-purpose AI models. California's SB 53 (signed September 2025) requires transparency reports and incident reporting for frontier models above 10^26 FLOP. New York's RAISE Act requires incident reporting within 72 hours. These requirements create the skeleton of a registry system, though implementation remains fragmented and early-stage.

The strategic value of model registries lies in their enabling function. A registry alone doesn't prevent harm—but it provides the information foundation for safety requirements, pre-deployment review, incident tracking, and international coordination. Without knowing what models exist and what capabilities they possess, governments cannot effectively regulate AI development. Model registries transform AI governance from reactive to proactive by creating visibility into the development pipeline before deployment.

Current Implementation Landscape

United States

Federal Level: The October 2023 Executive Order directed the Bureau of Industry and Security (BIS) to establish reporting requirements for advanced AI models. Under the proposed rule:

• Entities must report models trained with >10^26 FLOP
• Quarterly reporting on training activities
• Six-month forward-looking projections required
• Information includes ownership, compute access, safety testing

State Level:

European Union

The EU AI Act (Regulation EU 2024/1689), which entered into force August 1, 2024, establishes the most comprehensive registry requirements to date:

• General-Purpose AI Models: Registration with EU AI Office if trained above 10^25 FLOP
• High-Risk AI Systems: Registration in EU database before market placement
• Systemic Risk Models: Additional transparency and safety requirements
• Required Information: Technical documentation, compliance evidence, intended use

The EU database will be publicly accessible for high-risk AI systems, with confidential technical documentation available to regulators. Per Article 49, providers must register themselves and their systems before placing high-risk AI systems on the market. High-risk obligations become applicable in August 2026-2027.

China

China has implemented registration requirements since 2023 under the Interim Measures for Generative AI Services:

• Deep synthesis (deepfake) algorithms must register with CAC
• Generative AI services require registration before public offering
• Algorithmic recommendation services subject to separate registry
• As of November 2025, 611 generative AI services and 306 apps had completed filing
• Apps must publicly disclose which filed model they use, including filing number
• Focus on content moderation and political sensitivity

Comparison Table

Strategic Assessment

Benefits of Model Registries

Limitations and Challenges

Relationship to Other Governance Tools

Model registries are necessary but not sufficient for AI governance. They enable but don't replace:

Implementation Recommendations

Minimum Viable Registry

For jurisdictions establishing initial AI model registries:

1. Compute-based threshold: 10^25-10^26 FLOP (adjustable)

2. Pre-deployment notification: 30-90 days before public release

3. Required information:

   • Developer identity and contact
   • Training compute and data sources (categorical)
   • Intended use cases and deployment scope
   • Safety evaluation summary
   • Known risks and mitigations

4. Incident reporting: 72 hours for critical harms

5. Annual updates: Mandatory refresh of all information

6. Tiered access: Public summary + confidential technical details

Best Practices from Research

Based on analysis by the Institute for Law & AI:

Avoiding Common Pitfalls

Don't:

• Set thresholds so high only 2-3 models qualify (too narrow)
• Require disclosure of trade secrets unnecessarily (industry opposition)
• Create registry without enforcement mechanism (toothless)
• Assume static thresholds will remain appropriate (obsolescence)
• Ignore international coordination from the start (jurisdiction shopping)

Future Trajectory

Near-Term (2025-2026)

• California SB 53 effective January 2026 (transparency reports, incident reporting)
• EU high-risk AI database operational (August 2026-2027 compliance deadlines)
• GovAI forecasts 103-306 models exceeding 10^25 FLOP (EU threshold) by 2028
• 5-10 jurisdictions with some form of registry
• Initial international coordination discussions

Medium-Term (2027-2030)

• Potential international registry framework
• Capability-based triggers supplement compute thresholds
• Integration with compute monitoring
• Real-time incident reporting systems
• Cross-border data sharing agreements

Key Uncertainties

Quick Assessment

Risks Addressed

Complementary Interventions

• Compute Governance - Hardware-based verification complements software registration
• Export ControlsPolicyUS AI Chip Export ControlsComprehensive empirical analysis finds US chip export controls provide 1-3 year delays on Chinese AI development but face severe enforcement gaps (140,000 GPUs smuggled in 2024, only 1 BIS officer ...Quality: 73/100 - Control inputs to models in registry
• AI Safety InstitutesPolicyAI Safety Institutes (AISIs)Analysis of government AI Safety Institutes finding they've achieved rapid institutional growth (UK: 0→100+ staff in 18 months) and secured pre-deployment access to frontier models, but face critic...Quality: 69/100 - Institutions to review registered models
• Responsible Scaling PoliciesPolicyResponsible Scaling Policies (RSPs)RSPs are voluntary industry frameworks that trigger safety evaluations at capability thresholds, currently covering 60-70% of frontier development across 3-4 major labs. Estimated 10-25% risk reduc...Quality: 64/100 - Industry commitments that registries can verify

Sources

Policy Analysis

• Convergence Analysis (2024): "AI Model Registries: A Foundational Tool for AI Governance" - Comprehensive design framework developed in collaboration with Gillian Hadfield; influenced US BIS consultation and EU GPAI Code of Practice
• Institute for Law & AI (2024): "The Role of Compute Thresholds for AI Governance" - Threshold design considerations
• GovAI (2024): "Trends in Frontier AI Model Count: A Forecast to 2028" - Projects 45-148 models exceeding 10^26 FLOP by 2028
• Heim et al. (2024): "Training Compute Thresholds: Features and Functions in AI Regulation" - Analysis of compute thresholds as governance metrics
• Hooker (2024): "On the Limitations of Compute Thresholds as a Governance Strategy" - Critiques threshold gaming via distillation and MoA approaches

Legislation and Regulation

• US Executive Order 14110 (October 2023): "Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence" - Established 10^26 FLOP reporting threshold
• EU AI Act (2024): Regulation (EU) 2024/1689 - Article 49 covers registration requirements
• California SB 53 (2025): Transparency in Frontier Artificial Intelligence Act - First US state frontier AI safety law; effective January 2026
• New York RAISE Act (2024): Requiring AI Safety and Excellence - 72-hour incident reporting

Implementation Resources

• NIST: AI Risk Management Framework integration guidance
• EU AI Office: High-risk AI system registration requirements
• Future of Privacy Forum (2025): "California's SB 53: The First Frontier AI Law, Explained"

AI Transition Model Context

Model registries improve the Ai Transition Model through Civilizational CompetenceAi Transition Model FactorCivilizational CompetenceSociety's aggregate capacity to navigate AI transition well—including governance effectiveness, epistemic health, coordination capacity, and adaptive resilience.:

Registries are necessary but not sufficient infrastructure; they enable rather than replace safety requirements, evaluations, and enforcement mechanisms.