Comment by lukan
4 hours ago
Not sure about the level of irony here, but I keep hearing models have plateaued since a while now, but I keep being impressed with the latest model performance.
4 hours ago
Not sure about the level of irony here, but I keep hearing models have plateaued since a while now, but I keep being impressed with the latest model performance.
I'll take the opposite here. If someone put in frontier AI models from like .... last june I guess? in a box and let me run it with "decent" token throughput I would be happy.
I think it's worth acknowledging that the power of LLMs at this point is not really so much in the smarts, but in the coordination and the surrounding harness tech. "Written english" turning into sequences of commands[0]. The whole agentic "stuff" in general. Tools + coordination is the superpower. The reasoning... it doesn't have to be _that_ good for the rest of the stuff to work. On good codebases and infra, at least.
And I say this as someone who really would rather most of this stuff disappear!
[0]: programming is obviously text to commands, but there's a loooooooot of futziness that LLM reasoning has let us remove in some flows
> If someone put in frontier AI models from like .... last june I guess? in a box and let me run it with "decent" token throughput I would be happy.
You can have that! Qwen 3.8 Flash-Next is ~Opus 4.6 and runs nicely on a DGX Spark. And that’s just an architecture preview. The Qwen 4 family is expected to arrive this fall.
I don't think "plateaued" is the right word, but I do feel like there's been something like a logistic curve compression in the difference between smaller and larger models as the field evolves. For inference at least, the scale of practical difference between a single high-VRAM GPU or SFF UMA box, a whole rack, and a whole data center seems to be falling far short of what we might have imagined just a few years ago. The conversations I've heard have largely turned away from breathless anticipation of the next frontier model and toward attempts at hard-nosed evaluation of which tokens are worth the cost.
I think it’s more that pushing frontier is extremely costly and there is no free lunches in same way as 2024.
Maybe, though that's another kind of progress in itself. Very impressive progress!
Anything in particular? My experience has been like seeing the addition of retractable cupholders, but maybe different domains.
I have a pet project I have been working away on for some time that involves building GPU backends for various cards in Zig, lots of complex stuff in it. Lately I mostly use Opus 5, it can pretty reliably plug away at things but it does mess stuff up occasionally. For this codebase, Fable 5.1 was noticeably better at getting things right and doing things in a good reliable way. Of course, I can only use Fable for a bit before I hit the usage cap for the week, so I save it for the tougher things. That said, I absolutely abhor the way recent Anthropic models write prose, especially comments.
I recently tried doing a fairly normal task for this codebase with codex, as I have seen a lot of people talking it up on here. A single task running for ~1-2 hours burned through over half of my usage for the week on the $125/month plan, not on a top model (I don't remember which one specifically I used). It struggled to get the basics done, then got absolutely stuck on a follow up. Handed it over to Claude and it 1-shot it.
I really liked codex in the last few weeks, especially its ability to clean up after Claude's (prose) messes and do reviews.
But in the last few days something seems to have happened that made Codex's models massively stupider (for what I am doing).
Really weirdly, it suddenly refused to even run tests it previously wrote itself (and previously ran), because of some false positive about cybersecurity.
That by itself is not evidence of stupidity. Trying to make a 200+ file PR full of research notes is, and the PR didn't even solve the problem I asked it to.
astra is more parlor tricks than real gains tbh
i swear they trained in on threejs in particular so those idiots on twitter could spam their garbage demos
I'm sure that's part of it, but I run it side by side in my review bot, and Astra medium effort consistently catches more issues than Sol 5.6, using fewer tokens.
For coding it's a little harder to tell, but at least the prose feels a little better.
They've not plataued but they're certainly not as impressive as the hype would have them to be.
The reality is, it doesnt matter if LLMs keep getting more powerful because they still need a human to steer it. Without the human providing inputs to the LLM it just sits there and does nothing.
You don't need human input. Any coherent input will do the trick.
You can, for example, hook it up to a logging system and have it fix errors as they occur on your platform.
Have you tried this? How did it go?
I’d be curious about:
- your setup. How it all works - The types of errors it fixed and how quickly - Any regressions or issues it caused - The cost
Thanks!
Impressed with the model performance or the chatbot/agent performance?
Really? My employer rolled back to opus 4.8 because 5 was expensive AND crap. Didnt even consider fable because it didn’t add any additional value.
For most software eng and design work opus 4.6-4.8 just works fine. For everyday joe asking ai to plan a trip or home diy work even sonnet works fine.
Any cybersecurity or other areas are niches that cannot support trillion $ valuations. What am I missing? Genuinely curious
No idea what you are missing and yes, Opus is quite solid, but Fable is clearly way better for me.
I just did a direct comparison, big change in a quite complex codebase. Same prompt for Opus, same for Fable. Fable clearly won and delivered very good results, while Opus delivered mediocre, so I did not let it finish. I expected both to fail and was prepared to do lots of manual steering, but not necessary with Fable one shotting it, and all this with 35$ of credits for fable. I am still impressed. If I would have had to hire a human, it would have cost me thousands of dollar for the same task - and a way longer time. So maybe the valuations are overblown, but they clearly provide value for me.
If Fable doesn't add additional value in your workplace, it means you aren't being ambitious enough in how you integrate agents into your workstream.
Yes, it's probably comparable to 4.8 if you are just using it to write code and put up a couple pull requests. That's not where things are now.
You shouldn't be down voted, AI native companies have already moved up to the next level beyond writing individual PRs.
1 reply →
This is just "you're holding it wrong" with a little smooch of condescension. If only we plebeians could comprehend what magnificent works those who have ambitiously integrated agents into the workstream have wrought!
4 replies →
And where are things now?
By ambitious if you mean we are not like all the linkedin influencers with their “i one shotted an app this morning…” then no, we are not. Nobody is. I have been in software engineering for 18 years and 6 different companies including FANG and 99% of the people, on 99% of the days arnt writing new apps from scratch. Thats simply not how anything works.
And what even are these ambitious companies and people one shotting and building with Fable? AI has been around for almost 3 years now. Tell me one app or software you use which has gotten significantly better and has amazing new useful features landing on a weekly basis? If anything, every single software product I use has gotten worse.