This article is a good summary of local models. Unlike the way they are hyped sometimes, as fantastic tools for coding and agentic local work. The reality is that they are rather limited, would not do well on a long or complex task, and are prone to fall into loops, forget their tasks, etc. Not mentioned in the article is that they are also rather expensive - not just for the hardware cost, but also electricity. Thes…
Local Qwen isn't a worse Opus, it's a different tool
71–80 of 271 posts
Re: Local Qwen isn't a worse Opus, it's a different tool
#72If you play with these models long enough, you realize there is more to them than just "model X is smarter than model Y" or "model Y is cheaper than model Z". They are different tools and the prompting technique is different. It is very much like playing an instrument. With Claude, you sometimes want to under-specify or phrase things more indirectly to give a color to the implementation or elicit something creative.…
Re: Local Qwen isn't a worse Opus, it's a different tool
#73Would be interesting to use local models for: - tool calling - code base exploration - anonymizing / abstracting your request Such that your local AI communicates to frontier model like an expensive consultant giving high level advice. I think due to the lower latency of a local model that this could be faster.
In every way, the cloud products from the big two seem optimised for speed and speed of initial response even.
I don’t think most people are running local models for speed. More for control, privacy, interest, bloody-mindedness and general principle.
Re: Local Qwen isn't a worse Opus, it's a different tool
#74If you play with these models long enough, you realize there is more to them than just "model X is smarter than model Y" or "model Y is cheaper than model Z". They are different tools and the prompting technique is different. It is very much like playing an instrument. With Claude, you sometimes want to under-specify or phrase things more indirectly to give a color to the implementation or elicit something creative.…
> It is very much like playing an instrument. Or it is more like playing a slot machine and you imagine the rest.
Re: Local Qwen isn't a worse Opus, it's a different tool
#75If you play with these models long enough, you realize there is more to them than just "model X is smarter than model Y" or "model Y is cheaper than model Z". They are different tools and the prompting technique is different. It is very much like playing an instrument. With Claude, you sometimes want to under-specify or phrase things more indirectly to give a color to the implementation or elicit something creative.…
totally true. one key for claude is to not smell like an evaluator, its good at knowing when its being tested and will behave defensively and avoid doing work. i avoid this basin by typing unreasonably excited about the thing i want done. like way over the top. it's harder to keep that up than it sounds.
Re: Local Qwen isn't a worse Opus, it's a different tool
#76If you play with these models long enough, you realize there is more to them than just "model X is smarter than model Y" or "model Y is cheaper than model Z". They are different tools and the prompting technique is different. It is very much like playing an instrument. With Claude, you sometimes want to under-specify or phrase things more indirectly to give a color to the implementation or elicit something creative.…
Re: Local Qwen isn't a worse Opus, it's a different tool
#77Earlier quoted context omitted.
The parsing thing, or the willingness to instantly drop into janky unsanitized string manipulations, or to constantly push back against work on infra projects because some random package on GitHub has 200 stars so it’s totally the safer approach, is driving me insane. On one hand I’m glad Anthropic is only just now starting to get into infrastructure because it means there’s opportunity there, but it’d be great for t…
I feel like this is really due to the harness. Gemini CLI at work has the same issue: it'll prefer hacking your workstation over just asking you how to proceed. I think the harnesses are setup to have a bias to action otherwise the LLM would just stop all the time when doing trivial task but it also mean they'll keep going when the "obvious" path is to just prompt the user.
I often tell it to stop asking me and just keep going until it accomplishes X task; unfortunately it tends to assume I want something that only just barely works, in the sense that it means it's time to stop once its there, which is I don't think a harness by itself could easily address (ultimately the model itself needs to determine the stopping points unless I literally specify by hand hidden evaluation criteria).
That's why think it's at least partially a training issue where the model gets rewarded for "solving" the problem within a certain amount of context/time without access to grounded knowledge (eg looking up the actual spec for a format) nor adversarially/rigorously evaluated against a reviewer capable of finding all the edge cases/shortcuts preventing something from being a properly generalized solution. I don't want it to ask me for guidance when it's working on a well-specified problem, I want it to either find the right parser and use it, or to completely implement one against the spec, rather than write some half-assed string inserter that eg only works on the specific select statements my examples use right now. My understanding is that the Mythos/Fable models were better trained for this but from my brief foray into using Fable for work I wasn't that impressed. For me they need to get better at agentic search and self-eval still
Re: Local Qwen isn't a worse Opus, it's a different tool
#78Would be interesting to use local models for: - tool calling - code base exploration - anonymizing / abstracting your request Such that your local AI communicates to frontier model like an expensive consultant giving high level advice. I think due to the lower latency of a local model that this could be faster.
Re: Local Qwen isn't a worse Opus, it's a different tool
#79If you play with these models long enough, you realize there is more to them than just "model X is smarter than model Y" or "model Y is cheaper than model Z". They are different tools and the prompting technique is different. It is very much like playing an instrument. With Claude, you sometimes want to under-specify or phrase things more indirectly to give a color to the implementation or elicit something creative.…
It's hard to decide when to use the best tool for a job you are aware of to ensure throughput and when to spend time experimenting with a new tool to learn what it's good at.
Re: Local Qwen isn't a worse Opus, it's a different tool
#80If you play with these models long enough, you realize there is more to them than just "model X is smarter than model Y" or "model Y is cheaper than model Z". They are different tools and the prompting technique is different. It is very much like playing an instrument. With Claude, you sometimes want to under-specify or phrase things more indirectly to give a color to the implementation or elicit something creative.…
This is the problem.
I would love to have a product sheet showing what each models strengths an weaknesses are, so that I can have a clear decision tree of "if this kind of work, use model X", or "model Y should be used in ways Z". But they all look the same from the outside and the only way to figure out which might be marginally better at what is to do extensive, time consuming, and perhaps expensive testing.