With the rapid development of artificial intelligence technology, compliance in the use of distilled models by foreign enterprises in China has become a focus. Especially for systems like DeepSeek, Kimi/Moonshot, and MiniMax, alleged to be “distilled” from Anthropic Claude models, ensuring legal compliance under both Chinese and European Union legal frameworks is particularly important. This article offers a detailed analysis from three major dimensions: Chinese laws, the EU AI Act and GDPR regulations, and practical operations, supplemented with rich cases and professional advice, providing enterprises with a systematic and practical compliance path.
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## Understanding Compliance in China for Foreign Companies Using Distilled Models
Under Chinese legal frameworks, distilled technology itself is not illegal. This is because current laws such as China’s Cybersecurity Law, Data Security Law, and Personal Information Protection Law do not directly prohibit the technology itself. As a technique for model simplification and optimization, as long as data usage and model invocation comply with legal requirements, no illegal issues arise. The 2021 MIIT’s “AI Technology Compliance Guidelines” clearly states the principle of technological neutrality.
However, risks mainly lie in contract and trade secret protection. Violating agreements with Anthropic or other model providers, infringing trade secrets, or circumventing API access restrictions may lead to civil compensation or even criminal liability. For example, some multinational companies suffered heavy penalties for unauthorized commercial use.
Recommended risk prevention measures include:
– Confirming the scope of authorization with the model provider before use and signing detailed compliance agreements.
– Establishing internal compliance and audit mechanisms to regularly review API usage.
– Keeping comprehensive logs of model calls, data sources, versions, and use cases as evidence.
This triple approach can significantly reduce potential risks even under legal scrutiny and ensure safe deployment.
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## Key Compliance Points and Practical Guidelines under EU AI Act and GDPR
Foreign enterprises targeting the EU market must comply with both Chinese laws and the stricter requirements of the EU AI Act and GDPR.
### EU AI Act Regulatory Framework
The EU AI Act employs risk-based classification, with special rigor for “high-risk” applications such as recruitment and financial credit decisions. If models like DeepSeek are involved in decisions affecting EU users, enterprises must:
– Conduct risk assessments and Data Protection Impact Assessments (DPIA).
– Provide transparency statements informing end-users about AI decision mechanisms and model origins.
– Submit to third-party compliance audits to ensure conformance.
Since the AI Act details are still evolving, particularly about “capability safety” and “model data legality,” enterprises should closely monitor legislative developments and adapt their strategies accordingly.
### GDPR Personal Data Protection Obligations
GDPR requires processing personal data under legal bases such as user consent, contract necessity, or legitimate interests. If models process personal data of EU residents, enterprises must:
– Ensure lawful processing with clear purposes and data minimization.
– Respect data subject rights with access, deletion, correction, and objection to automated decisions (Article 22), offering human review channels.
– Comply with cross-border data transfer rules using Standard Contractual Clauses (SCCs) or adequacy decisions.
Given China’s Personal Information Protection Law (PIPL) mandates data localization, enterprises should design a “dual-layer compliance architecture” to manage data according to both jurisdictions.
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## Practical Perspectives: Scenario Differentiation and Risk Management
Compliance requires practical implementation depending on scenarios:
### Scenario A — Testing Only Within China Without Processing EU Personal Data
Use of distilled models for R&D testing only faces lower compliance pressure. Still, enterprises should sign authorization agreements, conduct security audits, and strictly manage internal compliance.
### Scenario B — Providing Services Globally or to the EU Market
Must ensure model legality, complete DPIA and risk reports, transparent user disclosures, third-party certifications, and strong contracts.
### Scenario C — High-Sensitivity Industries (Government, Finance)
These industries require highest standards for data security and compliance. Adoption of traceable and highly compliant models is advised to mitigate significant risks.
### Case Study
A well-known multinational bank used MiniMax distilled models for credit decisions in China and extended services to the EU. They implemented a multi-layer compliance framework including in-country closed testing with strict API monitoring, DPIA, data encryption, user rights protection in the EU, and multi-party licensing agreements. This balanced innovation with legal compliance.
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## FAQ
**Q1: Is distilled model technology illegal in China?**
A1: No, the law focuses on data compliance and contracts; technology itself is not prohibited.
**Q2: What legal risks arise from using restricted APIs like DeepSeek?**
A2: Risks include contract breach and trade secret infringement, leading to damages or criminal liability.
**Q3: How to meet EU AI Act risk classification requirements?**
A3: Complete risk and DPIA assessments, transparency, audits, and ensure compliance authorization.
**Q4: What preparations are needed under GDPR for automated decisions?**
A4: Provide human intervention, explanation rights, and objection channels to protect data subjects.
**Q5: How to handle cross-border EU-to-China data transfers compliantly?**
A5: Use SCCs or adequacy decisions and design dual-layer compliance considering PIPL’s localization.
**Q6: Recommendations for distilled model use in sensitive industries?**
A6: Use traceable, highly compliant model products to avoid major risks.
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Whether you are a startup AI R&D team or a global enterprise, understanding and implementing distilled model compliance is foundational for success and legal security. For more AI compliance consulting and technical service solutions, visit [De-Line Information Technology](https://www.de-line.net) to explore how to navigate change robustly.
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