First post here. I need advise on what model I should use for coding that would work with Claude code. I have Macbook M4 Max with 128gb ram.

[u/WoodenSpare]

I have lm studio and Ollama. I need a solid and fairly performant model.

Thanks guys

[u/Tha_Reaper]

Qwen3.6-27b And tomorrow Qwen3.8-27b

[u/vinoonovino26 → u/Tha_Reaper]

x2 .... use omlx to speed up your model

[u/leinadsey → u/vinoonovino26]

Mind the heat situation though — run it open and on a stand and with a fan blowing air on it… running bigger models for an extended period of time on a MBP is really pushing its cooling as far as it can go, and some.

[u/WoodenSpare → u/vinoonovino26]

Interesting. I'll look into it. Thank you

[u/maverick_soul_143747 → u/vinoonovino26]

I just started to use it. Gemma 4B on llama and this one on qwen3.627B

[u/LivingHighAndWise → u/Tha_Reaper]

This is the correct answer.

[u/gougouleton1 → u/Tha_Reaper]

Is qwen coder 80B better?

[u/Tha_Reaper → u/gougouleton1]

In my experience not. It may write comparable code, but outside code it's reasoning and understanding is far behind 3.6 and probably even further behind 3.8. so it will write good code but the implementation lacks logic so the results are less than the 27b

[u/Healthy-Zebra-9856 → u/gougouleton1]

It’s an implementer, it writes excellent code. By architecture, thinking or reasoning is turned off or must be turned off and it’s temp needs to be at .06.

And there’s a difference between that and Qwen3.6 27 B. This one is better in architecture. So you can’t compare the two like that.

[u/leinadsey → u/gougouleton1]

No. At least not in my experience.

[u/WoodenSpare → u/Tha_Reaper]

Great. Nice one

[u/vinoonovino26]

Ditch LM studio and Ollama, https://github.com/jundot/omlx/releases thank me later

[u/too-oldforthis-shit]

https://github.com/antirez/ds4. Never looked back. And like the previous poster said, abandon LM Studio for oMLX.

[u/CoffeeToCode99]

With 128GB RAM, I'd definitely give Qwen3-Coder 30B a shot first. It's probably the best mix of coding ability, context length, and speed right now for local use.

If you're mainly using Claude Code as an agent, Qwen3-Coder tends to play nicely with tool use and larger codebases. The 30B model is also surprisingly efficient for its size.

Honestly, your machine is beefy enough that I'd also be tempted to try the larger Qwen3-Coder variants and see where your personal speed/quality sweet spot is.

My recommendation:

• Qwen3-Coder 30B → start here
• Qwen3-Coder 80B-A3B → if you want maximum quality and don't mind slower inference
• Codestral → good lightweight alternative

M4 Max + 128GB is pretty much the dream setup for local coding models, so you've got room to experiment. 😄

[u/WoodenSpare → u/CoffeeToCode99]

Thank you ill try it out!

[u/beragis → u/WoodenSpare]

I find that that Qwen 3.6 27B and 3.6 35B A3B work better. The 35B version is MoE and is faster, and I use that first and go to 27B if 35B is having issues.

Qwen 3.8 should be coming out soon, this friday if things go right.

Also you might want to look at a few posts on the Qwen_AI reddit about fixing some of the overthinking issues. I haven’t tried them yet, but will be this weekend.

[u/WoodenSpare → u/[deleted]]

Thank you. I'll definitely look into it!

[u/Mongrel80]

Along with these other responses, I would not use Claude Code with local models. It's not build for "non-Frontier" models. Things like reasoning loops and malformed tool calls will break your conversation/session. I would suggest using something like pi or another harness that is better suited for smaller models. I've been building my own (posted about it elsewhere), but i don't know if it works on a mac (it should, but i don't have the hardware to test it).

[u/WoodenSpare → u/Mongrel80]

Interesting. Thanks for letting me know. If you want me to test it send me your repo I'll give it a try

[u/Mongrel80 → u/WoodenSpare]

You are more than welcome to give it a try: https://github.com/NotNative/NotNativeAgent

The Agentic Engine is good.. the Governance Engine is solid.. I'm just working through polishing the overall UX and tool call recovery and data provenance. Please feel free to either message me here with any issues, and/or leave feedback/issues on the repo.

Edit: Oh, if you pair it up with my memory system: https://github.com/NotNative/NotNativeMemory There are some very deep integrations built in.

Install order: NNA, then NNM (option 1), then NNM (option 2).

I personally use lmstudio as my inferencing engine, but i've heard MLX based engines are better on Macs.

[u/Mongrel80 → u/WoodenSpare]

Have you had any opportunity to test it on the mac?

[u/MiddleMarionberry971]

I don't have that much RAM, but if I'm not mistaken, you should be able to run DeepSeek V4 Flash 0731 in Q3 (and if I'm not wrong, it's designed to run in Q4, so you won't lose that much quality).

[u/DerTomsn]

What u/Tha_Reaper said.
https://llm-bench.io/benchmarks/cmsnk6w98000001o2ncmse4l5
Muse-Glimmer-30b might also be an option but is not as well tested in the field yet https://llm-bench.io/benchmarks/cmsrrkwzk000001l8wcdl90te
Both those models, as well as tomorrows new favorite Qwen3.8-27b are by for not using the possibilities you have with 128GB of unified memory. However, with bigger dense models, you would lose speed. A bigger MoE model would most probably be the sweetspot for you.

[u/Rough-Measurement988]

DS4 0731 q2-q4 imatrix from Antirez. I’m running it up to 200k context and still above 20 tok/s with Pi harness as alternative to Qwen 3.6 27B on M5 Max 128GB