Yes, without a question. Fable 5 and Opus 5.5 are a step-change above what we had before. On the open-weights side, GLM 5.3, DeepSeek 4.1 v1017, Qwen3.8-Flash-Next are all significantly more capable in basically any task you can give them.

You can now have a model work on a task non-stop for a day or more. This was unthinkable 12 months ago, and unstable 6 months ago.

If you are searching for evidence of capability, just look at the amount of projects, blog posts and videos on game remixes, hardware reverse engineering, new compilers and runtimes that has started coming out in the last 6 months. Slop? Sure, but this kind of slop didn't exist at this level 6 or 12 months ago.

And yet we have to contrast that with reports like this of model capability falling:

https://news.ycombinator.com/item?id=50422069

It's really very hard to pin down progress in this domain, companies are definitely targetting benchmarks.

One bit of evidence I would look at is the maths results this last year which have been impressive, that was a huge expensive brute force effort, but it is still good progress.

i am wondering in what potential world would average user or even business user require for model to work on a task for more than a couple of hours? Is assumption that models on average are used to build nextt SpaceX or something?

Are you certain this is a model improvement and not improvements to agents?

For me personally? yes absoluttly.

Opus 5 vs. 5.5 is a clear stepup.

Problem is, you need to do a diverse set of experiments to recognize it. Blender support got relevant better,t he amount of corrections got less etc.

It does very much vary with the domain though. I haven't personally noticed much improvement, they're still useful but unreliable, in my view the idea of agents, harnesses etc has been a distraction and functions to cover up the lack of progress in the underlying models.

But everyone has a different view of this, it'll be interesting to see how it plays out.

In some YT talk it was explained quite well: AI is not just progressing in one field, its progressing in a lot of fields in parallel.

Before Opus 5.0, anything with 3d was not doable at all. Starting with Opus 5, it can build you cloth simulators and more.

Yes, but what's interesting here is that everything didn't get better. The original "interesting" for transformers was that a translation AI turned out to also be good at generating novel prose. But if we now need to focus to train new capabilities into the models and those don't yield better behavior everywhere then we're no longer in the "free lunch" period of LLMs.

I think we will need a timeframe of at least a year to see if we reached any plateu.

But I do expect a combination of fast progress to continue alone due to the fact that hardware will catch up and will be faster.

And when we reached a real bottleneck, the next thing will be to put the frontier model on a chip and advancing world models and other architectures.

We are still 'just' steamrolling LLMs.

I took a six month break from AI coding after leaving my startup and just restarted this week. I feel like Opus 5.5 is a step function improvement from 4.5 or 5, which I built a large codebase with.

Opus 5.5 is capable of completing very long running tasks and managing many threads of work with subagents without getting confused in a way that simply wasn't possible before.