Open vs. Proprietary LLMs refers to two different approaches to building and using large language models.
Open-source LLMs make their model weights and architecture publicly available. This allows organizations to customize, self-host, and inspect how the model works, giving more control over data privacy and cost—but often requiring more technical effort to deploy and maintain.
Proprietary (closed-source) LLMs are owned and managed by companies. Users typically access them via APIs without seeing the underlying model. These models are usually easier to use, highly optimized, and continuously updated, but offer less transparency and control, and may involve usage costs and data-sharing considerations.
In practice, the choice comes down to control vs. convenience, transparency vs. performance/scale, and customization vs. ease of use.
