In case you're unaware, this is for the max setting. The (recommmended) high setting uses only 80k tokens.
I really don't get the value proposition of these massive models, seems like they're just loss leaders simply to say you're the in the top 3. There's not much use cases outside of niche academic research (and even then I question the need). They mostly function as marketing tools, like a casino that offers high roller accommodations.
People will say "cyber" but companies didnt want to spend on security before, not sure why they would all of a sudden be compelled to spend even more.
Security is mandatory now in a way that it wasn't, now that AI has eliminated the skill barrier to hacking.
You dont need Fable to do most things. Your video game is still a "CRUD" app and you certainly wont make a great video game because you have access to fable. But marketing works well, people actually believe they can buy competency for themselves.
It hasnt eliminated the barrier to hacking. Please go find me a valid crit on any program on h1 with your fable 5.2 within the next 3 days, Ill bet my entire life savings it can't, and if you did it would cost 3x the bounty. You've been reading too much engagement farming articles/posts
Security has always been highly important, not any more than it is now. Companies are not going to suddenly start spending six figures on fable to protect themselves from imaginary AI powered hackers.
Its there for people who fall for cheap marketing who thnk they can shortcut meritocracy and make video games, or do security research with no skill. Good luck! Dont max out your CCs on llms.
*Scale numbers to whatever suits you.
Fable class models are for people who fall for cheap marketing and are lazy and think they can now bypass a meritocracy and buy themselves competency. Really they'll just continue to be lazy, and the people with more competency will run circles around them with 1/10th the amount or llm usage, or none at all.
I used to work on evals/observability at Opik: https://github.com/comet-ml/opik And I can say from working with lots of users running agents at scale, there is definitely a pretty commonly reached frontier of difficulty/complexity/abstraction where the capability difference between something like Fable/Astra and smaller models is a big deal. I find this to be especially true the more autonomous your workflow gets. You can still often tackle the hardest tasks with something like Opus, it just typically involves more direct intervention and design work from the user.
But again, this is just anecdata on my part. All of this is still pretty ambiguous and lots of companies are trying to solve the problem of matching models to task difficulty (I.e. routers), with varying degrees of success.