Realistically, local/open weight models will always be limited in idiosyncratic world knowledge compared to the proprietary frontier. There's just very limited upside to releasing tens or hundreds of terabytes of open weights for something that literally can only run in very large AI data centers, and Fable/Mythos is near enough to that class. Smaller models can be smart in very real ways, but the extent to which those "smarts" can apply to real-world problems will be limited.
I think the best bet is that that at some point going from 30B params to 9T params is realistically going to give the closed model a 10% edge in niche tasks, but that the open model would be very useful most of the time still.
I don't know how realistic that expectation is, but if you think about the difference between say 10,000 USD speakers and 50,000 speakers then the 50k ones may sound slightly better but certainly not enough to justify the 40k difference