For the first time since GPT-2 in 2019, OpenAI is releasing new open-weight large language models. It’s a major milestone for a company that has increasingly been accused of forgoing its original stated mission of “ensuring artificial general intelligence benefits all of humanity.” Now, following multiple delays for additional safety testing and refinement, gpt-oss-120b and gpt-oss-20b are available to download from Hugging Face.
Before going any further, it’s worth taking a moment to clarify what exactly OpenAI is doing here. The company is not releasing new open-source models that include the underlying code and data the company used to train them. Instead, it’s sharing the weights — that is, the numerical values the models learned to assign to inputs during their training — that inform the new systems. According to Benjamin C. Lee, professor of engineering and computer science at the University of Pennsylvania, open-weight and open-source models serve two very different purposes.
“An open-weight model provides the values that were learned during the training of a large language model, and those essentially allow you to use the model and build on top of it. You could use the model out of the box, or you could redefine or fine-tune it for a particular application, adjusting the weights as you like,” he said. If commercial models are an absolute black box and an open-source system allows for complete customization and modification, open-weight AIs are somewhere in the middle.
OpenAI has not released open-source models, likely since a rival could use the training data and code to reverse engineer its tech. “An open-source model is more than just the weights. It would also potentially include the code used to run the training process,” Lee said. And practically speaking, the average person wouldn’t get much use out of an open-source model unless they had a farm of high-end NVIDIA GPUs running up their electricity bill. (They would be useful for researchers looking to learn more about the data the company used to train its models though, and there are a handful of open-source models out there like Mistral NeMo and Mistral Small 3.)
With that out of the way, the primary difference between gpt-oss-120b and gpt-oss-20b is how many parameters each one offers. If you’re not familiar with the term, parameters are the settings a large language model can tweak to provide you with an answer. The naming is slightly confusing here, but gpt-oss-120b is a 117 billion…