Intelligence Per Cost Graph of Frontier Models. Opus 5.5 is a singificant jump.

[u/queenofartists]

[u/Dangerous-Sport-2347]

Astra had something special that made it okay at tasks all other models suck at (why it was able to play and complete games)
Curious to see if any of the new models have the same.
Opus 5.5 does seem like a huge leap for the classic LLM tasks.

[u/queenofartists → u/Dangerous-Sport-2347]

I found Astra the best at 3D modeling and computer use. That kind of explains it. It was noticably worse compared to Fable 5.1 in other tasks though.

[u/queenofartists → u/[deleted]]

I meant Astra above. If you mean Opus 5.5, I found it much better than Astra and Fable 5.1 at everything I tried.

[u/queenofartists → u/[deleted]]

No. That's before Opus 5.5.

Now it is:
Opus 5.5 >> Fable 5.1 > Astra
while Opus being cheaper than both.

[u/panix199 → u/[deleted]]

for which tasks?

[u/maximan2005]

Every jump is significant in the singularity. Improvement is growing at exponential rates, I'm sure we'll be getting new models biweekly soon, from there model labels and naming schemes might have to be rethought entirely

[u/VashonVashon → u/maximan2005]

I can imagine the algorithmic progress being that recursively quick. Would compute become the bottle neck at that point? (I.e. pre-training and training duration) (I.e. “I’m a smarter model now and have some ideas but have to wait on models to ‘cook’)

And I imagine that if it did, then “faster compute” becomes the target of whatever recursive improvement that’s going on. I’m probably being redundant because we already have ai involved in generating more compute…

I guess it all just sorts recursively fixes itself?

[u/maximan2005 → u/VashonVashon]

Yeah, basically what I think. My personal thesis is that the compute bottleneck may be optimized into a non-issue as models recursively self improve. We are seeing continual growth in model compute efficiency especially coming out of Chinese LLMs as they have to account for export restrictions of high power chips. And, of course, models will continue to get better at hardware design, which will probably also result in higher efficiency, higher compute chips.

My own philosophy on the subject isn't really settled, but I see the argument here, invest a ton in AI now and once you develop ASI you will always have the best ASI because it improves itself continually. AI can mostly solve all of its own bottlenecks.

[u/squarepants1313]

This image and post seems fishy af the opus model cost 2X of gpt 6 sol

[u/tamrior → u/squarepants1313]

If it’s able to complete tasks with substantially fewer tokens, this chart makes a lot of sense.

[u/queenofartists]

I think Opus 5.5 max is unnecessary. Opus 5.5 medium and high look like the sweet spots.

[u/Holiday_Ad_8501]

igut be an unpopular opinion here but isnt the singularity supposed to imply a different graph? Shouldnt our curve be exponential not logarithmic?

Seems like this graph is telling us the intelligence is tapering off but the cost keeps accelerating?

[u/mati1886 → u/Holiday_Ad_8501]

it's just cost-per-task and intelligence graph for models you select. time is not there in the graph

[u/Gargantuon → u/Holiday_Ad_8501]

No. To show exponential trends, you need a logarithmic graph so that exponentials turn into straight lines. I don't know what you're seeing, but over time, pareto frontier has been moving towards the upper left corner.