3 ms·

A sample of one, but I was getting more stuff done despite Fable uses tokens twice as fast as Opus, because it understood the goals so well and worked to achiev

A sample of one, but I was getting more stuff done despite Fable uses tokens twice as fast as Opus, because it understood the goals so well and worked to achieve them.

consumer451 4mo ago
Same here, now n=2.
- toss1 4mo ago
  Same here, not n=3, plus the above 3 reporting, so n=6 and rising Fable was definitely better for a variety of tasks, even accounting for using 2X the token rate, like the way it used the tokens faster reduced the wasted tokens, as least for the subset of those who already knew at least some optimizations...?
2001zhaozhao 4mo ago
> more stuff done More stuff done per dollar or more stuff done for more dollars? Seems to be an important distinction
- itopaloglu83 4mo ago
  Given the same usage limits, I was able to get more stuff done and not even hit the usage limits, because I wasn't working on constantly fixing what Opus was trying to do, Fable just understands the task correctly and works great with the given context.
pshc 4mo ago
Same, I was actually having interesting thought experiments with Fable.
malshe 4mo ago
I even upgraded my Max plan because Fable was doing so well.
hodgehog11 4mo ago
Same experience. Wouldn't waste my tokens on easy stuff for it. It blasted through some of my toughest problems and produced some truly great code.
- mk89 4mo ago
  Can you give an example of what those "toughest problems/great code" are? I don't need to know the prompt nor the output, but the general idea, what it is about.
  - deleted 4mo ago
    [deleted]
  - hodgehog11 4mo ago
    Some very tough computational geometry problems I couldn't solve on my own, nor with the assistance of other AIs or my colleagues. Fable did them all first go. The most impressive built a custom optimizer with a ludicrous number of adaptive switches that absolutely crunched through an error surface with a bunch of nontrivial nullspaces and some wild curvature. That optimizer is of independent interest; it's not totally novel in theory, but the implementation is an impressive piece of engineering.
    - mk89 4mo ago
      Was it a better prompt? Have you tried giving the same prompt to other models? I have found out that the mistakes of other models (which I choose first to save money) help me refine the prompt more and more, until I am fed up and pick Opus 4.8 (for example) which magically seems to get it right, but there is a lot of pre-work there...
      - hodgehog11 4mo ago
        Yes I have tried giving these same prompts to other models. The difference has been painfully clear. Switching back to Opus, it is completely unable to do anything that I had asked of Fable without significant conceptual and engineering errors. Functioning code, sure, but not even remotely capable of accomplishing the task to the accuracy I need. Sonnet, GPT 5.5, Gemini, DeepSeek, it's all the same deal. I accepted this in the past because that was just how it was. Now it's tremendously irritating. I wish Fable really was only a minor upgrade so that it wouldn't be missed, but this feels like the difference between having a post-doctoral colleague and educating a student that I have to constantly guide and correct. It's so profound for me that some of the reactions in this thread feel like they come from another reality entirely. Or maybe they just got instantly diverted to Opus, who knows.

A sample of one, but I was getting more stuff done despite Fable uses tokens twice as fast as Opus, because it understood the goals so well and worked to achieve them.

consumer451 4mo ago

Same here, now n=2.

toss1 4mo ago
Same here, not n=3, plus the above 3 reporting, so n=6 and rising Fable was definitely better for a variety of tasks, even accounting for using 2X the token rate, like the way it used the tokens faster reduced the wasted tokens, as least for the subset of those who already knew at least some optimizations...?

2001zhaozhao 4mo ago

> more stuff done More stuff done per dollar or more stuff done for more dollars? Seems to be an important distinction

itopaloglu83 4mo ago
Given the same usage limits, I was able to get more stuff done and not even hit the usage limits, because I wasn't working on constantly fixing what Opus was trying to do, Fable just understands the task correctly and works great with the given context.

pshc 4mo ago

Same, I was actually having interesting thought experiments with Fable.

malshe 4mo ago

I even upgraded my Max plan because Fable was doing so well.

hodgehog11 4mo ago

Same experience. Wouldn't waste my tokens on easy stuff for it. It blasted through some of my toughest problems and produced some truly great code.

mk89 4mo ago
Can you give an example of what those "toughest problems/great code" are? I don't need to know the prompt nor the output, but the general idea, what it is about.
- deleted 4mo ago
  [deleted]
- hodgehog11 4mo ago
  Some very tough computational geometry problems I couldn't solve on my own, nor with the assistance of other AIs or my colleagues. Fable did them all first go. The most impressive built a custom optimizer with a ludicrous number of adaptive switches that absolutely crunched through an error surface with a bunch of nontrivial nullspaces and some wild curvature. That optimizer is of independent interest; it's not totally novel in theory, but the implementation is an impressive piece of engineering.
  - mk89 4mo ago
    Was it a better prompt? Have you tried giving the same prompt to other models? I have found out that the mistakes of other models (which I choose first to save money) help me refine the prompt more and more, until I am fed up and pick Opus 4.8 (for example) which magically seems to get it right, but there is a lot of pre-work there...
    - hodgehog11 4mo ago
      Yes I have tried giving these same prompts to other models. The difference has been painfully clear. Switching back to Opus, it is completely unable to do anything that I had asked of Fable without significant conceptual and engineering errors. Functioning code, sure, but not even remotely capable of accomplishing the task to the accuracy I need. Sonnet, GPT 5.5, Gemini, DeepSeek, it's all the same deal. I accepted this in the past because that was just how it was. Now it's tremendously irritating. I wish Fable really was only a minor upgrade so that it wouldn't be missed, but this feels like the difference between having a post-doctoral colleague and educating a student that I have to constantly guide and correct. It's so profound for me that some of the reactions in this thread feel like they come from another reality entirely. Or maybe they just got instantly diverted to Opus, who knows.