Open-weight models and Chat-GPT 5 launched concurrently, with open models poised to deliver broad practical impact for researchers, small businesses, and other users. Open source AI per the Open Source Initiative allows inspection, modification, use, and sharing without permission, though the new open-weight models do not fully meet that strict definition. Open models can reduce cost and improve privacy by enabling offline deployment and free usage. Proprietary models often outperform open ones but require costly infrastructure and external servers. Open models are rapidly improving and can be run locally or within company premises as self-managed alternatives.
ChatGPT maker OpenAI made headlines this month with two major launches: the release of two so-called open weight models and the debut of the long-anticipated next generation Chat-GPT 5. While most of the media and industry buzz focused on the latter, it's the open models, and the rapidly advancing ecosystem around them, that could make a bigger difference for everyone from researchers to small businesses.
The idea of open versus closed (or proprietary) models is familiar to anyone who has worked in software, and the definition is the same when it comes to AI. According to our partners at the Open Source Initiative (OSI), open source AI means anyone can look at how the model works, change it, use it, and share it freely without needing to ask for permission.
Proprietary AI models often deliver stronger performance, but they require costly infrastructure and must run on an external provider's servers, which requires a business to hand over its data. Open source models, by contrast, are improving quickly, and as they narrow the performance gap. Already, it is possible to run certain models locally, or even on a laptop or within a company's own walls-options that can offer a powerful, self-managed alternative in the right circumstances.
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