Comment by nicce
12 hours ago
They keep doing anti-competitive things over and over again, and the end users seems to refuse to see it. They do whatever they can to get vendor-lock in.
12 hours ago
They keep doing anti-competitive things over and over again, and the end users seems to refuse to see it. They do whatever they can to get vendor-lock in.
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
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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.
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Oh, I see it. But there is nothing that competes with Opus 5.5 for 90+% of the work I do, so I use Opus 5.5 for that 90%.
Mr. T pities the fool who has not tried Kimi K3.
You mean 3.1 Pro now, I assume? K3 is nice, but more expensive than an Claude subscription on a token-for-token basis (until the US frontier rugpull eventually comes), and not as good for my needs unless I'm trying to do "naughty" things, like reverse engineering.
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What kind of work you do? I'm doing Linux kernel work in my free time, arguably one of the most complex coding task you can do, and the open source models are sufficient
There is nothing comparable. I will take Opus5.5 (or even 5.0) over Astra for almost any workload. OpenAI's models are just too misaligned to work well outside their benchmarks, or a strict environment with very clearly defined goals and constraints.
And I've spent around $100-$120k in api calls this year (total, both providers). Terra is awesome (price-performance) on noncreative things, but I don't allow it to write anything besides one-off scripts. Astra is decent for adversarial review, but only when you watch closely for her to not derail project into directions that are away from goal but safe to build, and Sol I honestly don't know where I'd use.
Her? Are we really giving them pronouns now?
sure.
would you rather treat your AIs like people, or would you rather find yourself down the line treating a person like an AI, but without really noticing it? because you are what you practice
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