Join the discussion
Write your take first — we'll ask for email only when you're ready to publish.
- Hacker News
- 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.by mholm
- >> GLM 5.2 is worth focusing on. It came out the same week as Fable and is roughly 1/9th the cost (and ~1/5th the cost of Opus 5). Is GLM 1/9th the quality of Fable? Perhaps, for certain classes of tasks. But for most rote coding it’s more than sufficient. Especially when provided with great context. I frequently chat with Fable to interrogate and shape a design, before handing off a brief to GLM.
People say stuff like this a lot, but I have a different take.
The whole "such-and-such model is 90% as good as Fable at 1/10th the price" assumes that the value increase of intelligence is linear. But I think it's exponential: that last 10% makes a massive amount of difference. It can result in a key insight that helps you strategize more effectively, a novel approach that saves a huge amount of time, a feature design that is lot more user-friendly (because top models like Fable also possess substantial non-software domain knowledge that help bridge the gap between user and software), or the depth and breadth of engineering expertise that helps avoid a nasty bug that would otherwise have cost you users and revenue.
Yes, it is totally possible to use Fable as the planner and delegate implementation to lesser models. I do that. But, my theory (which I unfortunately do not have the money to test and prove) is that a codebase designed and implemented by Fable would be substantially better than one that is designed by Fable and implemented by Opus 5, GPT 5.6 Sol, GLM, Qwen, Deepseek, etc. The reason I believe this is because I read the code Fable writes and compare it to code that any other model writes and the difference is night and day. It's not just 10% better. It's mid-level engineer vs. principal/staff-level engineer. And the thing is, even for rote tasks, a more senior engineer is going to be more likely to come up with a clean design than a mid-level engineer. They will also be much more likely to take a step back and ask important questions or propose different approaches.
So if you're using Fable and everyone else is using lesser models, sure they might be saving a lot of money, but there's a higher likelihood that your product will be higher quality, perhaps to a significant extent. And models that are released in the future will benefit from it as well.
- Why are we not just in a free lunch moment but with harnesses, rather than models?
Right now a lot of people have a lot of opinions on which model to use for which task. They get better results for less money by judiciously switching between Fable and Opus and whatever else. Spending my time learning this skill would have an immediate benefit for me.
But on the other hand, maybe the harness vendors will just solve it in 6 months? I'll ask a question, something in Claude Code (or whatever we're using by then) will figure out the most effective model based on the question and the context and my apparent willingness to get it right. I'll get billed X or 10x as appropriate, and I'll be happy with that, because that's what I would have paid if I made my own choice of model every time.
Claude Code already does this a bit, sometimes it will tell me it picked Sonnet for such and such a sub agent, or some other detail I'd rather not care about. The best humans seem to be better at deciding what model to use than any of the tools is, but surely that won't last long.
by dmurray - 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.by pigpop
- I find it somewhat funny that the author starts by talking about how Moore's law enabled inefficient software and that we then had to make it more efficient, when almost all software today is horrendously inefficient compared to even 10 years ago, let alone 20-30. We've somehow even achieved a state where it doesn't matter how fast your CPU and memory are, the software will just perform horribly on any machine.
- 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.
by rmast - 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.
by peteforde - 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
by nchmy