It depends what you’re doing. I have no problem using an open source model to build a static website or other simple tasks. And of course, open source is catching up and the things you can trust it with grows every month.

Not to mention the way the proprietary models patronize you if they think you’re up to no good. The other day I was trying to use Claude to transcribe a song on YouTube to sheet music; the link was broken and it had not been available for purchase for years. Of course I first had to prove to Claude that I was not just being cheap and trying to get around paying the $5 for the download, which I would have had no problem with. “I am going to be up front with you —- my research raises some red flags with your initial premise that the sheet music is no longer available…”

I think in the next 5-10 years inference costs will come down substantially and the open source models will get so advanced that only someone in an extremely niche, cutting edge field will need a frontier model. Everyone else will have a dedicated box somewhere on their network that runs their LLM of choice. No tokens, none of your data getting sent to a third party, no arguing with it over whether or not a link is actually broken or if you’re just trying to be cheap.

I think OpenAI and Anthropic realize this which is the reason they’re in a rush to go public.