These are not really open source models. They are open weight, which is like sharing an executable instead of the actual source code. You don’t have the things you need to reproduce the model weights. What’s actually needed for these to be open source is the training source code, the training data sets, any applicable pre- or post- processing code, evaluation code, etc.

Although training the actual model is not feasible for people without the funds and hardware, having those things would at least allow the model to be auditable. Otherwise, we really have no idea what these open weight models are doing. They could be biasing themselves in various ways that are invisible but damaging.

Another thing to watch out for is licensing. Only a few models use an actual open source license from OSI (like Apache). Many are using proprietary licenses that reference external terms that can change over time, or limit how you use their model. These restrictions are definitely not in the spirit of open source.

In other words, much of this is “openwashing”, which is a new trend like “greenwashing”.

Anyways, I think it’s great that these models are able to challenge the really big proprietary models like ones from OpenAI or Anthropic. This shows the models are not that interesting or unique, and that the differentiation will come from who has access to training data. That is why Microsoft is scrambling to violate users’ privacy with Copilot agents autolaunched at startup (https://www.pcmag.com/news/microsoft-tests-having-copilot-la...) and why Apple does not let you disable Siri training easily but only one by one for individual apps (https://www.imore.com/how-stop-siri-learning-how-you-use-app...). And that’s also why OpenAI and others seem to be pushing for regulations that restrict AI using excuses like “safety” or “ethics”, when it is really about regulatory capture.