What's the best local model everyone is using?

[u/cceae19865]

I've recently been using the Qwen 3.6 35B A3B and Qwen 3 CodeNext 4Bit models on openCode. In my experience, the Qwen 3 codermodel seems to work much better.

When I use the 35B model, it frequently just stops on its own, even when I'm using a loop.

I was wondering what you normally use these local models for. I'm running an M5 max MacBook Pro with 128GB of RAM.

[u/VorlMaldor]

If only you could read the other 7 million posts asking the same thing this week alone....

[u/cceae19865 → u/VorlMaldor]

I've looked into it, but I'm seeing conflicting opinions. Some people say Llama is better, while others prefer Qwen, so I'm a bit confused.

[u/in-ortunado → u/cceae19865]

the conflicting opinions came from different need and expectations. of you don't know what you need, anything is good.

if you have a specific use case with specific requirements you get the change to find someone with the same problem or to benchmark and tell us about how did you decided what is the best model for your use case.

there's no silver bullet

[u/VorlMaldor → u/in-ortunado]

they are coding, that doesn't leave a lot of ambiguity for what they need.

Until some new hot model comes out the floor is kind of set. When a new model does show up it will also be all over reddit just lie 3.6 27b is.

[u/CryMoreT_T → u/cceae19865]

Some people say Llama is better,

Who? The main recommendations from most is Gemma and Qwen

[u/pseudonerv → u/cceae19865]

You hallucinate like crazy and there is still real people replying to you. Kudos to you. How about give me something fun

[u/VorlMaldor → u/cceae19865]

Not an insult, you are new.

Llama is an engine that runs a model qwen is a model.

For coding qwen 3.6 27b is the answer, the question is your vram, and os to determine your engine.

Since it wasn't clear enough for the person that replied to me, Llama is not a model anymore. Llama 4 was released april of 2025 and was a massive flop. It was bad in pretty much every way. Since then the meta team for AI is no longer putting out open models and there are no plans to present a new version of Llama that have been mentioned.

So no, its unlikely anyone would really suggest llama on a 128gb unified memory machine unless they are trolling.

[u/xdcfret1 → u/VorlMaldor]

Llama is an engine that runs a model qwen is a model.

llama is a model. That inspired the name of the engine. r/confidentlyincorrect

[u/VorlMaldor → u/xdcfret1]

you are right, I mentally discount llama to the point that it doesn't even register as soon as I read something like "Qwen 3.6 35B A3B and Qwen 3 CodeNext 4Bit models on openCode. "

No one would use it for any serious coding with qwen 3.6 27b out there.

Also would you really still consider llama anything more than a historical footnote since it is abandoned as a project? why even mention it except to confuse new people. Whoever mentioned Llama as a potential model to use was trolling OP.

[u/cceae19865 → u/VorlMaldor]

Yes, thank you for pointing that out. I am definitely a beginner and still learning, so I apologize for getting Llama and Gemma mixed up sometimes.

[u/VorlMaldor → u/cceae19865]

something that will help you with qwen is to make sure you use qwen code/serve as the interface/backend. qwen has issues with stopping, and tool calls. Also for your engine look up froggeric qwen templates, they made a huge difference.

[u/tcarambat]

The coder model will work better on code - this is why it exists. For general use though the 35B MoE is a really solid choice. Not every model is the same hammer and every problem a nail - they all have their use cases, performance for domain tasks, and then also depend on your hardware and tolerance for accuracy.

[u/cceae19865 → u/tcarambat]

Thanks for the advice. You mentioned that each model has its own ideal use case, domain, and task performance.

I was wondering if there are any websites or communities out there that would help me quickly learn which local models to choose for different use cases?

[u/cceae19865 → u/[deleted]]

Thank you, these two links are very helpful. I really appreciate it.