Businesses gain greater control over model stability, data, infrastructure, costs, security and the knowledge they build with open weights.

On July 24, Nvidia joined Microsoft, Meta, IBM, Hugging Face, Mistral and other technology organizations in signing Open Weights and American AI Leadership. The letter argues that AI leadership will depend not only on developing powerful frontier models, but also on creating an open ecosystem that distributes those capabilities throughout the economy.

For governments, sovereignty means maintaining control of critical technology. For businesses, it operates at several levels. It includes control of model behavior, company data, hosting infrastructure, costs and the knowledge accumulated through years of work.

According to NIST’s definition of a model weight, a weight is “a numerical parameter within an AI model that helps determine the model’s outputs.” In practical terms, weights contain much of what a model learned during training.

An open-weight model makes those parameters available for download. Subject to its licence, an organisation can run the model, evaluate it, adapt it and deploy it on infrastructure of its choice.

The licence defines how published weights may be used. Under the Apache License 2.0, they can generally be used commercially, modified and redistributed, provided the required notices are preserved. Businesses should still check each model’s specific licence before deployment.

A closed weight model keeps those parameters private. Customers access the model through an application or API, while the provider controls the underlying model, its hosting and usually its update cycle.

When a company deploys an open-weight checkpoint, the underlying weights remain fixed.

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