OpenAI made a big move earlier this month. Ahead of ChatGPT 5’s release on August 7, the company released two open-eight models. This was the first time the AI startup had launched open-weight models since GPT 2 in 2019. OpenAI CEO Sam Altman has now accepted that Chinese rivals played a key role in this decision.
The two open-weight models launched were gpt-oss-120b and gpt-oss-20b. The former is a large model meant to work with data systems and high-end laptops. On the other hand, gpt-oss-20b can work on most laptops, desktops, and even on phones with relatively modest hardware, per OpenAI. These models which can be run locally and customised by researchers, developers, and companies.
Earlier this year, DeepSeek shook the AI space with its R1 model. Not only did R1 match the likes of ChatGPT and Gemini, it was also open-source. This allowed users to get much more freedom compared to closed AI models like ChatGPT.
This sparked fears within OpenAI. Sam Altman claimed that releasing open-weight models became a necessity to avoid Chinese dominance. He told CNBC, “It was clear that if we didn’t do it, the world was gonna head to be mostly built on Chinese open-source models.”
Altman accepted that this was a serious reason behind the release. However, he clarified that it was not the only reason.
What open-weight model really means
An open-weight model like gpt-oss is not the same as an open-source model like DeepSeek R1. In an open-weight model, users are given access to ‘weights.’ Weights refer to the characteristics or elements that are you used to train a Large Language Model (LLM).
For certain queries, the AI gives more weight to certain words or sequences. An open-weight model gives access of these weights to users. Developers can then see these weights and how they’re used in the creation of AI models.
However, the way the AI was trained or the information used to train the model remain restricted. Thus, the code or the information used to train gpt-oss is not available to the public.
Yet, ChatGPT’s open-weight models can be crucial. Developers can not only understand the weights of the models, but use them locally or add them to pre-existing programs. This will help negate the dependence on Chinese open-source models, strengthening US’ position.
This move comes at a time when the US government is concerned about China’s rise in the AI race. The Trump administration has even put stricter restrictions on advanced chip sales to Beijing.
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