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Comment by verdverm | Hacker News Reader

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.

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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.

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?

My read is that GP is eluding to people over estimating how much of a model they need for a task. Perhaps Claude can make more features work in autonomous mode more often, but what are the actual artifacts? What is the quality of the architecture?

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)

> 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.

Yes, this was the core of my point.

Sorry for being unclear. I mean that we humans have a tendency to believe we can detect nuances in the world when it is in fact just a case of internal bias. I simply question whether most people can actually detect whether they relly need the best model for their task. But of course, everyone believes that they themselves have this ability even if people in general do not.

There's also the factor of habituation, the best model is the one we're used to, and most familiar with its quirks. Using a model only for unreal work won't result in really knowing how to work with it.

True, good point.

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.

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

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