11 Total
4 High severity
4 Medium severity
3 Low severity
Summary

This is OpenAI's system card for GPT-5, a multi-model AI system that routes user queries across fast, reasoning, and mini model variants based on conversation complexity, tool needs, and explicit user intent. The document discloses that gpt-5-thinking has been classified as High capability in the Biological and Chemical domain under OpenAI's internal Preparedness Framework, activating associated safeguards, even though OpenAI states it lacks definitive evidence the model meets its own defined threshold for enabling novice users to cause severe biological harm. The routing system is disclosed as continuously trained on real user signals including when users switch models, response preference rates, and measured correctness.

Technical / Legal Breakdown

This document is a system card published by OpenAI for GPT-5, a unified AI system comprising multiple model variants including gpt-5-main, gpt-5-main-mini, gpt-5-thinking, gpt-5-thinking-mini, gpt-5-thinking-nano, and gpt-5-thinking-pro, deployed across ChatGPT and the API. The document discloses that GPT-5 incorporates a real-time routing system trained on user behavior signals including model-switching events, response preference rates, and measured correctness, and states that all GPT-5 models feature a safety training approach called safe-completions designed to prevent disallowed content. The document states that gpt-5-thinking has been classified as High capability in the Biological and Chemical domain under OpenAI's Preparedness Framework, activating associated safeguards, while explicitly noting the company does not have definitive evidence the model meets its defined threshold for meaningful novice uplift toward severe biological harm; the precautionary classification and the stated absence of definitive evidence create an interpretive gap that compliance teams and regulators may scrutinize. The document engages considerations relevant to the EU AI Act, given the model's classification under a risk-tiered internal framework and its general-purpose AI status, as well as FTC oversight of AI system disclosures and safety representations in the United States; applicability of specific regulatory obligations depends on jurisdiction, deployment context, and how regulators classify the system. Material compliance considerations include the adequacy of the safe-completions safety training mechanism, the operational scope of the Preparedness Framework's High capability designation, and the transparency obligations associated with disclosing routing logic trained on real user interaction data.

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Featured — High severity
Featured — Medium severity
Featured — Low severity

Complete Provision Index

Every distinct legal provision identified in this document. Featured provisions appear above with analysis.

11 provisions
11 featured
8 clause types
4 high severity
platform_discretion 3
ai_automated 2
content_moderation 1
developer_api 1
disclosure_requirements 1
enforcement_actions 1
policy_changes 1
restricted_content 1

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Mapped Governance Frameworks

California AB 2013 AI Training Data Transparency
US-CA
View official text ↗
CFAA
United States Federal
View official text ↗
DMCA
United States Federal
View official text ↗
DSA
European Union
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Trump Executive Order on AI Policy Framework
US
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Archival ProvenanceSource & Archival Record
Last Captured July 6, 2026 21:53 UTC
Capture Method Automated scheduled archival capture
Document ID CA-D-000923
Version ID CA-V-004521
SHA-256 69b6f6c6c1b9cd51d6a1ea03282a0aad54853f436ff7d52476917723688de5ab
✓ Snapshot stored ✓ Text extracted ✓ Change verified ✓ Hash verified

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