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LLMs: Intelligence vs. Cost

openteams.com

11–20 of 48 posts

Re: LLMs: Intelligence vs. Cost

#11
Well done. The inability to switch between log and linear always bothered me.

Another thing is if you're using the subscriptions with OpenAI or Anthropic you get an order of magnitude discount relative to the per-token price. So you need to move their models ~10x to the left on the plots to get a fair comparison.

Re: LLMs: Intelligence vs. Cost

#12
post #10

Complaining about "bad charting" and posting a chart with y-axis that doesn't start at 0 is kinda weird.

Yeah, this doesn't include older models, some of which were already saturating many common tasks a year ago. I'll often add them to the AA graph for reference.

Re: LLMs: Intelligence vs. Cost

#13
post #3

> Why AA’s plot is misleading > The first issue I have with it is that it uses a logarithmic scale on the cost axis. Using a log scale is the only way to make you spot the difference between a model that costs $0.015 per task and one that costs $0.032, while the same plot contains a model that costs $3.69 — almost 250 times as expensive. However, the net result is that the viewers can no longer appreciate the immensi…

It’s funny they state log plot is “the only way” to keep the cheap area readable, say they hate it, and then immediately have to zoom into their non-log plot cheap area because it’s unreadable.

Re: LLMs: Intelligence vs. Cost

#14
post #10

Complaining about "bad charting" and posting a chart with y-axis that doesn't start at 0 is kinda weird.

to be fair, you don't need to start the y-axis at zero [0] but for some of the graphs where the lowest value is close to 0 the best practice is to do so

there's a fun Excel artifact where it auto-selects the 'relevant' range with no adjustment for how proportionally close to 0 the values are - a professional researcher publishing to a journal should know better (and should be ridiculed for not incorporating best practices) but for a personal blog by an SWE this really isn't the worst sin

[0] https://digitalblog.ons.gov.uk/2016/06/27/does-the-axis-have...

Re: LLMs: Intelligence vs. Cost

#15
Is there a case in which a heavy agentic coding user of mid or mid++ tier (remotely hosted) models is better off using PAYG/API pricing than just getting a subscription? (Assuming no easy access to high end local hardware and I've deliberately left the top tier/cutting edge models out becau).

Re: LLMs: Intelligence vs. Cost

#16
post #14
post #10

Complaining about "bad charting" and posting a chart with y-axis that doesn't start at 0 is kinda weird.

to be fair, you don't need to start the y-axis at zero [0] but for some of the graphs where the lowest value is close to 0 the best practice is to do so there's a fun Excel artifact where it auto-selects the 'relevant' range with no adjustment for how proportionally close to 0 the values are - a professional researcher publishing to a journal should know better (and should be ridiculed for not incorporating best prac…

IMO in this case is mandatory to start from 0 because it alters the visual perception.

Just look at the first chart: the distance between Fable 5.1 and Sol is <5%, but it looks like 25 or 30%.

Re: LLMs: Intelligence vs. Cost

#17
There is an immense difference in cost between the state-of-the-art models from Anthropic and OpenAI and the much cheaper Chinese models ... How much extra intelligence emptying the wallet purchases obeys the law of diminishing returns: while a top-tier engineer or scientist is probably going to be able to appreciate how much better Fable 5.1 [is] ... most people will have a hard time doing so.

Nebari is officially listed as a JATIC product as part of the next-gen toolchain supporting DoD AI development.

Are we officially ~one degree of Kevin Bacon from the DoD endorsing running Chinese OSS models because they're self-hosted and we're all too dumb to tell the difference?

https://openteams.com/open-source-isnt-the-real-risk-in-nati...

Re: LLMs: Intelligence vs. Cost

#18
post #8

This looks great! I also think speed should be part of the metric (i.e. how long does the model take to actually solve a task). For me, I prefer to run expensive models such as Sol on light reasoning, which usually gives me good answers with quick responses. For my style of coding (quick back-and-forths and corrections) it makes a big difference if a model comes back in 1-2 minutes compared to 5-10, and I am happy to…

I agree on both: indeed a nice article, and I'd like to see a chart with speed as x axis.

As someone who only needs AI for a couple of tasks per day, I don't really care how much it costs, especially when subscriptions are subsidized. I want to filter by speed (eg, max task time feels great and are affordable for infrequent tasks.

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