This makes sense but I am not comfortable with the open source picture either. It depends on the use case and long term strategy. If you're handling customer support tickets or something, beyond some capability I can't imagine the ROI would be worth needing the absolute frontier. You are then in a wonderfully lovely place: absolutely full control over the model and inference stack (if you want).

But

- Plenty of businesses are stuck between a rock and a hard place: make 3p models load bearing, or sacrifice performance to the competitors that are willing to swallow that risk

- I just cannot imagine a viable equilibrium where OSS models compete on capabilities with the frontier without a hidden payer and shaky economics. Quant funds, some sovereign AI effort, cloud business, sanctioned distilled frontier models; all of these are demonstrably viable vehicles for OSS development. But the optimal position for these purposes is not to be the best, it's to be good enough (which I think is the position they find themselves in). I can imagine temporary points where open models pull ahead but not sustainably.

I agree there are many many use cases where the optimal choice is to reach for open weight models (I assume yours is one of them).

But the economics of frontier model development necessitates that these models are behind and thats a problem for other cases.