is scaling working? It is also my understanding that Opus 5.5 is probably a well under 10T parameter model. Probably a similar size class to Fable 5 earlier. And supposedly even GPT-4 was a 1T model. Clearly most of the gains are coming from something other than scaling up the model size. Yes, scaling up RL counts as scaling too, but the fact that labs have pivoted to a different axis of scaling is evidence that it's not just a "straight highway" to improve LLMs.
From the outside it seemed like GPT 4.5 was the apogee of parameter size scaling and since then a huge investment in RLVR became the new scaling axis.
So yeah, LLMs keep getting more powerful/useful but because of an industry wide pivot not a "straight highway" as imagined in the GPT-4 era, when simply going bigger and bigger seemed like a reasonable roadmap for the foreseeable future.