The point (which they make quite explicitly) is that an individual or small organization can only run open source models locally, and those open source models are less sophisticated than the “frontier” models.
Obviously we can’t run GPT-5 or the cutting edge version of Claude or whatever locally, because OpenAI or Anthropic are keeping those weights as closely kept secrets.
But there is nothing inherent about that. The companies that want to run local models, or the cloud and hardware providers that want to sell hardware to run them, can get together and publish better local models.
Moreover, even that's presuming that you would only use the best available model, but that's also likely to be the one which is the most resource intensive and the most expensive, and then you can't afford it anyway. Meanwhile to use their smaller models you're still paying their margin, whereas if you use a local model you can spend that money on hardware. The bigger local model can beat the smaller proprietary one for the same price.
You're absolutely right. I find the kind of reasoning employed in the article to be fallacious at best and malicious at worst, as it's trying to attribute conclusions about one thing to something else entirely, on wholly contingent grounds.
This reminds me of a debate thread on Reddit some years back where people were arguing about the calorie content of coffee: most people were correctly recognizing that coffee itself has negligible calories, but one person was insisting that coffee has a high calorie count because it is often consumed with cream and sugar. This article is on the level of the "coffee is high in calories" argument.
Obviously we can’t run GPT-5 or the cutting edge version of Claude or whatever locally, because OpenAI or Anthropic are keeping those weights as closely kept secrets.