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.
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.
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
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.
I suspect that's because they're working on projects that are several orders of magnitude more complex and demanding than a "todo app".
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.
Their point may also be (re: wine), that some devs have been conditioned to think a certain token vendor (vineyard) is of superb quality, while if given a blind test (tasting) of the agents on a real world task, they would not notice the difference.
For those of us who use open weights, the difference has narrowed dramatically this year. I've personally been mostly eyes-free developing an NES harness with mostly flash models, bringing in Kimi from time to time, and stepped in a couple times to reframe the approach or architecture. For those of us who (when we) stay in the loop, the difference is near-zero because the tasks we give them are more bite sized.
The difference I have observed is most closely tied to the complexity or context requirements. While I work in a multi-million LoC codebase without any issue for open weights or flash models, my NES project is only 20k lines. The challenging part is the core loop (which needs to blend the emulator FPS with the agent loop) and game state observation (needs to detect byte changes in emulator RAM). The ROM decoding itself has not been so bad, I have actually been quite impressed with the little open weight models on this front. After it extracted the maps, then pulled out even more details, it has written an A* implementation that requires moving between different modes of transportation. (Final Fantasy 1)
Yes, this was the core of my point.
GLM flash catches Claude errors and bad assumptions, all LLMs make mistakes
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.
Grownups pay for tokens or rent GPUs. Step up. AMD hardware rates are stupid-cheap if you're willing to do the legwork to step off of CUDA.
But you sound like the type who likes being monopolized.
And yes, I am taking full advantage of the scammy subscription scam, because it's the best value by far until the inevitable rugpull. Guess I'm not as smart as you and your "grownup" setup though.
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.
We have also gender neutral words (child, butter, ending with „o” in polish).
And you cannot really talk about anything without revealing its gender because all the adjectives and verbs are gendered. Using a gender neutral form for Astra or Opus would be very weird.
Out of all the project names „Claude” is the only project that you can kind of use any gender form with.
And our grammar has no distinction between animate vs inanimate. If I talk about agents in polish there is no difference in grammar between a human agent or a machine agent.
I wonder how it will affect a perception of ai long term. Also adoption is a bit easier - I can talk about my agent/assistant and not reveal my opinion about it being a machine or whether or not I personify it (which I don’t).
As a sidenote, people do not need to announce their pronouns here. The pronouns are usually obvious after the first sentence they speak usually. And gender neutral communication is very difficult unless you use plural.
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
This defined a huge set of possible work.
> I've spent around $100-$120k in api calls
Have multiple $200 subs and just use Codex as the intermediary, save yourself $90k-$110k