The White House is preparing to bring powerful open AI models into its secretive safety-review framework.
The administration’s current framework applies to closed models from leading AI companies, including OpenAI and Anthropic. But White House officials are now expected to expand it to open models once they reach frontier-level capabilities, according to WIRED.
A White House official told WIRED that open models could face prerelease testing when their capabilities reach the level of Anthropic’s Mythos-class models and OpenAI’s GPT-5.6.
The framework remains voluntary and has not been publicly released. Axios reported that the administration has generally viewed models with frontier capabilities and national security risks as requiring some form of government collaboration, regardless of whether they are open or closed.
That puts the administration in a difficult position. Open models can be downloaded and modified after their weights are released, making them fundamentally different from proprietary systems that their developers can update, restrict or shut down.
A balancing act for Washington
The potential policy shift comes after growing pressure to keep open models competitive in the US AI market. Companies including Meta, Microsoft and Palantir have backed efforts to protect open-weight development. Nvidia CEO Jensen Huang has also argued for maintaining both open and closed frontier models.
“Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty,” Huang said. “The world needs both frontier closed models and frontier open models.”
The administration also faces a practical concern: If government approval becomes associated primarily with closed models, businesses could view open models as riskier, potentially hurting US developers working on them. At the same time, officials worry that highly capable open models could be misused for cyberattacks and other national security threats.
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A new test for open-weight AI
The emerging debate highlights a growing reality for AI companies: the distinction between open and closed models may matter less to regulators than the capabilities of the systems themselves.
For businesses building AI products, broader oversight could provide greater confidence in the safety of advanced models. For developers of open-weight systems, however, additional reviews could slow releases and increase compliance costs.
The challenge for policymakers is finding a middle ground. Open models have become a critical part of the US AI ecosystem and are increasingly viewed as a strategic response to China’s advances in the field. Yet the same accessibility that fuels innovation also raises concerns about misuse.
As frontier AI capabilities continue to spread beyond a handful of closed providers, the administration appears to be moving toward a capability-based approach rather than one defined by whether a model is open or closed.
Why this matters
For businesses adopting advanced AI, the White House’s approach could become another signal for evaluating model risk. If open and closed models undergo similar safety reviews once they reach frontier capabilities, enterprises may have more information to weigh alongside performance, cost, and deployment flexibility.
For open-model developers, however, broader oversight could introduce new friction. Prerelease testing may slow launches, increase compliance costs and make it harder for smaller developers to compete with companies that have larger legal and policy teams.
The bigger shift is regulatory. Rather than treating open and closed AI as separate categories, Washington appears increasingly focused on what a model can do and the risks those capabilities create. If that approach takes hold, capability thresholds could become a much more important factor in how advanced AI is developed, released and adopted.
Also read: For another example of how openness can create security trade-offs, 77 counterfeit Open VSX extensions recently exposed developer and CI/CD environments to supply-chain risk.
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