We see it, but they dont have a competitor. OpenAI cant compete and they are the closest. I have both for work, and Opus 5.5 is in a league of it's own. I use opus for everything until it bitches, and I use openAI for whatever it bitches about just to get past it.
At this point, I would like to consider other options, but if I want to get work done, opus 5.5. Hell even sonnet 5.5 is better than anything OpenAI has to offer when it comes to coding.
which kind of works exactly?
there is a huge difference between open models/other models/opus5.5 performance on, say, enterprise CRUD vs one shotting games vs embedded development vs pure algorithmic complex stuff vs cybersecurity stuff.
In my case "real work" is enterprise programming, while side projects are gaming stuff, so I'm better served by chinese open models on real work and opus for non-real work.
In my experience GLM5.3-4 are perfectly en par with opus 5.5 on pure enterprise CRUDs (basically 95% of enterprise programming) while GLM seriously lacks on game development.
the other aspect of real work is cybersecurity to me, and Opus5.5 and other models are very limited by their own safety, I have digital twins of our infra and I want LLMs to actually write full exploits on it, opus and openai just refuse to do it, GLM more than once got it there and showed me how it chained everything to actually break in the system and I could go around and fix stuff at all levels.
I'm also dabbing in training LORAs for smaller open models to do data entry and little more (RAG and the likes of it), because that costs a lot of tokens when you pay for them and it makes sense for a company to flat out buy a server with a few H100/200 to do it when you look at the TCO, I've already hit safety limitations when using Opus5.5 to help me through this.
Anthropic has plenty of competitors. We don't need the best model for most tasks these days. Open weights are making huge inroads for a reason.
They do have competitors. They just dont have anyone with models equivalent to theirs. They win in the large context long thinking space by a lot.
I love local models, and I run 3.8 Flash Next on a dedicated machine. Alone with a number of image and video generation models. But if I'm doing REAL work, that isnt tinkering for fun on a side project, im using claude, because Qwen3.8 just cant handle large context project well without going off into left field.
Im SUPER jazzed for qwen4 with 1mil token context native support. I HOPE it a step up from 3.8 flash next. Ill be playing with all the qwen4 models the moment I can, but I dont see how someone working on large code bases doing REAL enterprise grade work is seriously using any local models in any capacity that comes remotely close to Opus 5.5+Claude
The size of a code base does not determine the size of the model you need. It's much more correlated with the complexity of the problem. I work in a monorepo with millions of lines, no issue; I have a side project with 20k lines, I had to step in and pull it out of non-progress - albeit by asking a single question
> But if I'm doing REAL work, that isnt tinkering for fun on a side project
Sorry, but this is either dilettante talk or an unhinged exaggeration - Qwen, DS, GLM and MM are perfectly fine for REAL work, unless you are an overly ambitious vibe coder, but then no model can save you. The Cl hand-holding may feel like something but it won't lead to the completion of real REAL work.
Things are changing so fast that it's easy to let just a little bit of time slip by and think that smaller models are still unreliable.
Honestly I feel like most people going "oh but I can't do this without Claude" are just suffering from FOMO. Especially since a lot of metrics are just subjective, you feel like you "have" to use the "best of the best glub shitto v5" model or else you won't be able to produce the best todo app.
> Honestly I feel like most people going "oh but I can't do this without Claude" […] or else you won't be able to produce the best todo app.
I suspect that's because they're working on projects that are several orders of magnitude more complex and demanding than a "todo app".
It is a very human trait to believe/feel "what I do is special so general rules do not apply". The bias is very strong.
The same way people have opinions on things like for example wines without actually being able to discern them in a blind test.
We humans want to think we can have strong, well founded opinions even when we cannot.
I'm confused about what point you're trying to make. Are you saying that there is no discernable difference in challenge between different software projects – say, between a stereotypical todo app and a physics simulation engine? Or are you saying that most people falsely believe they're working on the latter while really doing the former? Or something else?
Eh, we all say we don’t need the best model, but especially for more personalized request/Advice there is sort of a FOMO feeling, where you are afraid weaker models will miss something and directs you down a more inefficient path.
I haven't used them in 6+ months, you definitely do not need them, I see them make mistakes while reviewing PRs (we allow many models at work)
GLM flash catches Claude errors and bad assumptions, all LLMs make mistakes