For an AI model specifically to be considered truly open, the OSI says its developers must provide detailed information about its training data and give people the ability to study, use and modify the system for any purpose.
While DeepSeek is “open,” some details are left behind the wizard’s curtain. DeepSeek doesn’t disclose the datasets or training code used to train its models. This is a point of contention in open-source communities. Most “open” models only provide the model weights necessary to run or fine-tune the model. The full training dataset, as well as the code used in training, remains hidden. Stefano Maffulli, director of the Open Source Initiative, has repeatedly called out Meta on social media, saying its decision to label its Llama model as open source is an “outrageous lie.”
While there are multiple claims to DeepSeek’s ‘open source’ AI model, in reality it is not open source. While both the model weights and the model architecture were shared in a technical paper, neither the code nor the training or evaluation data were shared openly. An analyst for the Open Source Initiative also confirmed that Deepseek is not Open Source AI and doesn’t meet the requirements of the Open Source AI definition. It joins other models which claim to be open source, but score poorly on data transparency.
Ai2’s fully open approach, which includes data, training code and models, ensures users can easily customize their pipeline for everything from data selection through evaluation.
The Open Source Initiative, after years of planning, in October 2024 introduced its initial definition of open source AI, which addresses four different kinds of data and requires those building and sponsoring AI technology to share what data they can as well as the model’s parameters and the source code used to train and run the system.
Open source AI models are in widespread use, enabling developers around the world to build custom AI solutions and host them where they choose.
Open-source AI, according to the Open Source Initiative, is “an AI system made available under terms and in a way that grants the freedom to use the system for any purpose and without having to ask for permission, study how the system works and inspect its components, modify the system for any purpose, including to change its output, share the system for others to use with or without modifications, for any purpose.”
Technically, R1 is “open” in that the model is permissively licensed, which means it can be deployed largely without restrictions. However, R1 isn’t “open source” by the widely accepted definition because some of the tools used to build it are shrouded in mystery. Like many high-flying AI companies, DeepSeek is loathe to reveal its secret sauce.
While debates about the definition of Open Source AI continue, with the Open Source Initiative (OSI) recently publishing its first draft, this ambiguity hasn’t slowed the adoption of modern AI models.
There are two broad kinds of licenses that meet the formal open source definition as laid out by the Open Source Initiative (OSI).
In October 2024, the Open Source Initiative established a definition for open-source AI. According to the initiative, open-source AI has four key elements: the freedom to use, study, modify, and share the system for any purpose.
The Open Source Initiative (OSI) defines what open source is. For a model to truly be open source, its license should allow, among other things, the free redistribution and creation of derivative works, for example, by fine-tuning the model. If this permission is not granted, it’s not open source.
