Fable and the End of the Free Lunch
The release of Anthropic's Fable model marks a turning point: the era of cheap, ever-improving AI coding is over. As Moore's Law once did for hardware, new models used to paper over inefficiencies in our coding workflows. But Fable's high cost—and its stringent data policies—have forced developers to reconsider where to allocate their work. The author now uses Fable for design and interrogation, then hands off to cheaper models like GLM 5.2 for routine coding, a strategy that may persist even as prices fall.
When Moore's Law slowed in the mid-2000s (specifically, single-threaded performance stagnated), we suddenly had to think about parallelization, architecture, memory locality, etc.
- nchmy
The real revolution is Deepseek v4 flash and similar models (GPT 5.6 Luna, muse spark 1.2, mimo, etc...) - Genuinely good performance for a tiny fraction of the cost of Fable and even GLM etc...
I think a lot of people would be very content if they never got smarter, and just kept getting even cheaper/faster. Of course, both things continue to happen on a seemingly monthly basis
- rmast
Most of the things I work on are at least security adjacent. At some point chatting with Fable inevitably leads to it thinking about the security related aspects, tripping the safeguards.
Maybe Fable can do the same things better than other models, but having to tiptoe around to avoid tripping safeguards makes GPT 5.6 so much easier to work with that I don’t even bother with Fable (or Opus 5) now.
- peteforde
A few months ago folks were understandably annoyed when Microsoft dropped their heavily subsidized per-request pricing model because it was figuratively burning cash.
Well, I'm here to tell you that whatever is going on behind the scenes at Cursor with this Space-X acquisition in the works, the Auto setting is clearly routing all prompts through "Cursor Grok 4.6 High" right now.
This is a degree of subsidy that makes the Microsoft thing look quaint.
I reduced my $200/month subscription to the $20/month level and have proceeded to do what I would have paid about $1500 to do with Opus 4.7 or thereabouts, which is how Grok 4.6 High feels like it compares. I don't have anything remotely like hard evidence to back this estimate up beyond what I'm watching it do and I still somehow have ~10% of my monthly Auto capacity left on my account. It's completely nuts.
Can't say much more because I have more backlog to run before someone comes to their senses.
- g42gregory
I have really good experience with GLM-5.3 The subscription limits are generous, code quality is comparable to old (good) version of Opus 4.8 Some people report issues with it’s being slow, but I didn’t feel it. I use OMP harness (Pi derivative) and Matt Pocock skills.
- mholm
As models train up the intelligence ladder, many common tasks will hit fully diminished returns, and instead it'll just get progressively cheaper to do that task. But the tasks that AI is capable of doing are also expanding. I'm not sure 'Some tasks don't require the peak of the frontier' is worth worrying about, from an AI finance perspective.
- pigpop
Reading this as someone who switched over to ChatGPT after (and largely because of the changes made in) the Fable release, it reads a bit naive. Not only do I find Sol to be as good, if not better than, Fable it is also faster, better behaved and has a much more coherent writing style. You also don't randomly get the Opus downgrade. OpenAI seems to be pulling this off due to their partnership with Cerebras so I wouldn't make any comparisons to Moore's law just yet considering it seems like we're just getting started in that department. Anthropic could (and should) do the same thing. It certainly feels like model development is at a point where it would be worthwhile building special purpose silicon for the models we have now since they are capable enough that they would still be useful even when/if further advancements are made. If anything, I think Anthropic's problem has more to do with their micromanagement of what users can do with their models, they're creating an undue amount of overhead for themselves by over-policing usage and capabilities.
- zkmon
I guess Moore's law analogy is weak. CPU speed has hit a limit in that case. What has hit a limit in AI case? Newer versions of the models are still flowing with more and more capability.
For the users, I feel it is more like "free lunch started", with all these awesome open-weight models being thrown around, breaking the monopoly of a few biggies.
- blfr
What are all these rote coding tasks people do that they can farm it out to lesser models?