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    Home » Russia Approves Regulatory Framework for Large-Scale AI Foundation Models
    Technology

    Russia Approves Regulatory Framework for Large-Scale AI Foundation Models

    July 20, 2026
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    MOSCOW, RUSSIA / RankWire.AI / – Russia’s Federation Council has approved a legislative framework on July 17 that establishes national regulations for the development and deployment of large artificial intelligence foundation models. The law defines key terms, grants regulatory authority, and provides support for domestic developers meeting specific criteria. It also introduces standards for model oversight, data storage, user notifications, and AI-generated content. Having passed the State Duma on July 8, the bill now awaits presidential approval before becoming law.

    Russia approves AI framework for large foundation models
    Russia sets legal framework for large AI models.

    According to the legislation, a large foundation model is software capable of executing numerous intellectual tasks at a level comparable to human performance. The definition encompasses systems that supply information, make decisions, or predict outcomes based on human-defined objectives. To qualify, a model must contain at least 1 billion parameters. The framework emphasizes principles including technological sovereignty, human rights, personal choice, security, and legal compliance within Russia.

    The law establishes distinct categories for sovereign and national models. A sovereign model must originate from a Russian legal entity and stay under domestic control, utilizing data centers located within Russia. Developers are required to maintain the technical capacity to reproduce the full development cycle, including training and original parameters. A national model adheres to similar ownership and data processing rules but may incorporate foreign components distributed under open licenses.

    Official recognition for domestic models

    The government may implement support measures for entities involved in creating, deploying, or operating qualifying foundation models. Such support could include access to state-held data necessary for training. The law also authorizes authorities to designate specific environments where only sovereign or national models are permitted, particularly in government information systems and other sensitive sectors. Additional laws and presidential decrees may establish regulations related to defense, security, public order, and property protection.

    Websites, applications, and social media platforms will be subject to a new content regulation. Platforms with over 500,000 daily users must provide a mechanism for marking AI-generated audio or visual content. This allows users to add an information notice to qualifying materials. The format of such labels will be determined by service agreements between developers and users. While automatic labeling of all AI content is not mandatory, platforms must offer the technical capability to do so.

    Copyright and implementation regulations outlined

    AI service providers are required to inform users about ownership rights concerning generated content. They must also clarify access conditions and whether content can be transferred. The law separately addresses the use of copyrighted works for machine learning, considering analysis for extraction, comparison, classification, and pattern detection lawful when developers have legal access. Training datasets may include protected works if no technical restrictions designed to limit access were bypassed.

    Most of the rules are set to take effect on September 1, 2026, pending presidential approval and publication. Regulations concerning domestic model status, developer responsibilities, content labeling, and intellectual property will come into force on March 1, 2027. Existing systems will have a transition period until September 1, 2032, during which their data processing and storage must remain within Russia. Until the measure is officially enacted and published, it remains an approved bill rather than law.

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