This article is part of VentureBeat’s special issue, “The Real Cost of AI: Performance, Efficiency and ROI at Scale.” Read more from this special issue.
For the last two decades, enterprises have had a choice between open-source and closed proprietary technologies.
The original choice for enterprises was primarily centered on operating systems, with Linux offering an open-source alternative to Microsoft Windows. In the developer realm, open-source languages like Python and JavaScript dominate, as open-source technologies, including Kubernetes, are standards in the cloud.
The same type of choice between open and closed is now facing enterprises for AI, with multiple options for both types of models. On the proprietary closed-model front are some of the biggest, most widely used models on the planet, including those from OpenAI and Anthropic. On the open-source side are models like Meta’s Llama, IBM Granite, Alibaba’s Qwen and DeepSeek.
Understanding when to use an open or closed model is a critical choice for enterprise AI decision-makers in 2025 and beyond. The choice has both financial and customization implications for either options that enterprises need to understand and consider.
Understanding the difference between open and closed licenses
There is no shortage of hyperbole around the decades-old rivalry between open and closed licenses. But what does it all actually mean for enterprise users?
A closed-source proprietary technology, like OpenAI’s GPT 4o for example, does not have model code, training data, or model weights open or available for anyone to see. The model is not easily available to be fine-tuned and generally speaking, it is only available for real enterprise usage with a cost (sure, ChatGPT has a free tier, but that’s not going to cut it for a real enterprise workload).
An open technology, like Meta Llama, IBM Granite, or DeepSeek, has openly available code. Enterprises can use the models freely, generally without restrictions, including fine-tuning and customizations.
Rohan Gupta, a principal with Deloitte, told VentureBeat that the open vs. closed source debate isn’t unique or native to AI, nor is it likely to be resolved anytime soon.
Gupta explained that closed source providers typically offer several wrappers around their model that e …