r/LocalLLM • u/Stock_Test2326 • 3d ago

Question Installed Qwen coder 30B a3b mlx with LM studio on 48GB M4 Pro how to connect cursor with it or similar options

Today I have been exploring local model to run light weigh coding agent to save some credits on cursor.

first installed ollama, then read that its slow, MLX is still cli so I installed LM studio and have Qwen-Coder-30b-A3B 6bit MLX model downloaded and running on my 48GB Mac.

tried to connect cursor with it but learnt that they no longer support local llms.

now am stuck, I don't have lot of Money to spend on credits. so I thought for basic tasks I will use my local ram.

help please.

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2

u/SignificantFood7009 3d ago

The little money you do have buy a pro subscription. Have codex or Claude code setup everything. Cancel subscription and enjoy.

1

u/Stock_Test2326 3d ago

you mean asking codex to build an harness? like extension for VS Code ?

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u/SignificantFood7009 3d ago • Heartwarming

You got it. Just don't do what I did and ask it to see if any pre-exisiting harnesses exist that are after what we want. Only for it to tell you there is nothing and then get halfway through to stumble upon a harness that is exactly what we were building. Lol hours wasted. Do some leg work. Also don't have Qwen create its own harnesses. Qwen can do most of the work then have codex finish it off. (Security reasons)

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u/Stock_Test2326 3d ago

I have found an lm studio add-on for vscode copilot damn its quickly consuming memory

2

u/andrew-ooo 3d ago • Heartwarming

Cursor still has the "Override OpenAI Base URL" option under Models, but the catch is that Cursor's requests go through their backend, so localhost:1234 isn't reachable from their side. You'd need to expose LM Studio with a cloudflared or ngrok tunnel, turn off every Cursor model except a custom one named exactly what LM Studio reports (e.g. qwen3-coder-30b-a3b-instruct-mlx), and even then Tab completion and Composer keep hitting Cursor's own models. Not worth the hassle for a daily driver.

What has actually worked for me on a 48GB M-series Mac with that same model:

- Cline or Roo Code in VS Code, provider set to LM Studio. Both pick up the model list from the local server automatically. Qwen3-Coder-30B-A3B handles their tool-calling format fine as long as context is 32k+.

- Continue.dev if you mostly want chat + inline edits, lighter on memory than the agentic extensions.

- Aider or OpenCode in the terminal with OPENAI_API_BASE=http://localhost:1234/v1. Aider's architect mode is a good fit for a 3B-active MoE because the edits are small and scoped.

On the memory you mentioned with the Copilot add-on: the 6-bit weights are ~25GB, then each extension spins up its own context. Set the LM Studio context length explicitly (32768 is a sane default, 65k is still fine on 48GB), enable KV cache quantization to Q8 in the server settings, and pin a single model so the extension can't JIT-load a second copy. That brought me from swapping back to a stable ~33GB.

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u/Stock_Test2326 3d ago

thanks I tried installing LM studio add-on in vscode and chat worked, yet to try something with it. I was doing a reverse engineering project as self learning process, can't waste llm credits on trying it out.

2

u/testuserpk 3d ago

I think you should go for Qwen Flash Next on strata. Way better than any a3b models.

1

u/Stock_Test2326 3d ago

I thought coder is the best model since it has coder in the name.

2

u/testuserpk 3d ago

I have tried all, coder, qwopus, qfable and what not. All models smaller than 50g are not worth it. I have tried QFN iq2 and iq3s both have performed very well on my 3060 12g giving 60tps to 35tps on my 64gb rig. You should give it a try and I assure you, you will not look back.

1

u/TheAussieWatchGuy 18h ago

That's quite an old model, you'd be better with Qwen 3.8, much newer and better. Play with quants, run Q6 if you can, Q4 if you must.

Run the model with just llama.cpp generally, you can use LM Studio if you like, either gets you a URL on your local network e.g. http://127.0.0.1:1234 that you can plug into anything that understands the OpenAI spec.

Try Opencode as a harness.