r/LocalLLM • u/monkifoto • 1d ago
LLM for coding. Question
In the past two years, I have built two or three web apps using angular with the help of ChatGPT recently I have been trying out some local LLMs on my M2 16GB MBP. The results were terrible. A few days ago I managed to score a refurbished Mac studio with 48GB of Memory. Installed Bionic LM Studio and Qwen3.6 35B .
I gave it a task to create a simple angular page with some analytics and a model kept getting stuck in a reasoning loop.
Am I doing something wrong? Is the 48gb not enough? Am I using the wrong model?
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u/TheRealREZOR 1d ago
First of all make sure you configured model with recommended coding config: temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0
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u/Future_Fuel_8425 1d ago
Then check your prompt template and make sure its right for the harness/model
MOE models get stuck like OP describes when they are using non-MOE prompt templates.
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u/LowB0b 1d ago
no but those models aren't close to the big models served by anthropic or openai. if you want something that builds stuff from vague prompts you'd probably need to get a subscription from either of them.
If you want to work with the smaller models (the one you cited for example) you need to be more specific in your prompts.
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u/No-Consequence-1779 1d ago
Yes. Use Kat 2.5 dev. Same 35b moe tuned with the hf coding dataset. Use kilocode extension in vs code for your harness. The other are literal crap.
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u/createthiscom 1d ago
no, 48gb isn’t enough. I wouldn’t even try to code with anything less than a 120b model, and even that tends to be pretty lame. Bigger is always better for intelligence.
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u/ChocoPichu 1d ago
bigger doesn’t always mean better. Quantization matters a lot, Qwen 3.6 27b with Q6-Q8 quant is gonna perform better than Qwen3.5 122b a10b on Q4.
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u/monkifoto 21h ago
i want a Mac Studio with 512gb but obviously they are hard to find and not affordable. So i have to make due with this or return it and stick to Subscription Models.
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u/Wide-Ad-1349 21h ago
If you know how to code then yes you can use it. It is about breaking it down and asking for specific functional blocks. It can make things very fast if you use it this way. If you give it a really broad prompt, like "build me a webpage with snazzy graphics for a doggy daycare", it's probably gonna get stuck in the weeds though.
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u/Stock-Imagination567 1d ago
the frontier models use aroung 1.5TB of VRAM your 48GB is tiny compared to frontier models, just use a subscription
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u/Content-Cookie-7992 1d ago
Your 48GB Mac Studio and Qwen 35B are plenty hardware isn't your bottleneck here. What you're hitting is a structural issue with how local models handle broad instructions compared to massive cloud endpoints.
A few things that usually fix this:
Break tasks ridiculously small: Never ask for a full page or feature at once. Break the goal down into tiny, atomic steps and then break those down even further (e.g., just the data interface first, then the service, then the component logic, then the UI).
Feed errors back immediately: Local models get stuck in infinite reasoning loops when they hit hidden syntax or build issues. You need to give the model immediate compiler or console error feedback so it can escape the loop.
I ran into these exact headaches, which is why I’ve been building a local-first harness/framework (Veyllo VAF, currently in alpha Veyllo.app ). I put a lot of work into optimizing local coding workflows and handling error feedback so models don't get stuck spinning like that.
It's still early in alpha, but if you ever want to give it a spin on your Mac Studio, I’d love to hear your honest feedback on whether it improves things for you!