"This particular [80B] model is what I’m using with 128GB of RAM". The author then goes on to breezily suggest you try the 4B model instead of you only have 8GB of RAM. With no discussion of exactly what a hit in quality you'll be taking doing that.
A guide to local coding models
11–20 of 363 posts
Re: A guide to local coding models
#12I'm curious what the mental calculus was that a $5k laptop would competitively benchmark against SOTA models for the next 5 years was.
Somewhat comically, the author seems to have made it about 2 days. Out of 1,825. I think the real story is the folly of fixating your eyes on shiny new hardware and searching for justifications. I'm too ashamed to admit how many times I've done that dance...
Local models are purely for fun, hobby, and extreme privacy paranoia. If you really want privacy beyond a ToS guarantee, just lease a server (I know they can still be spying on that, but it's a threshold.)
Re: A guide to local coding models
#13This story talks about MLX and Ollama but doesn't mention LM Studio - https://lmstudio.ai/ LM Studio can run both MLX and GGUF models but does so from an Ollama style (but more full-featured) macOS GUI. They also have a very actively maintained model catalog at https://lmstudio.ai/models
Makes me think it's a sponsored post.
Re: A guide to local coding models
#14> I realized I looked at this more from the angle of a hobbiest paying for these coding tools. Someone doing little side projects—not someone in a production setting. I did this because I see a lot of people signing up for $100/mo or $200/mo coding subscriptions for personal projects when they likely don’t need to. Are people really doing that? If that's you, know that you can get a LONG way on the $20/month plans fr…
And as a hobbyist the time to sign up for the $20/month plan is after you've spent $20 on tokens at least a couple times. YMMV based on the kinds of side projects you do, but it's definitely been cheaper for me in the long run to pay by token, and the flexibility it offers is great.
I spent $240 in one week through the API and realized the $20/month was a no-brainer.
Re: A guide to local coding models
#15> I realized I looked at this more from the angle of a hobbiest paying for these coding tools. Someone doing little side projects—not someone in a production setting. I did this because I see a lot of people signing up for $100/mo or $200/mo coding subscriptions for personal projects when they likely don’t need to. Are people really doing that? If that's you, know that you can get a LONG way on the $20/month plans fr…
I'm convinced the $20 gpt plus plan is the best plan right now. You can use Codex with gpt5.2. I've been very impressed with this.
(I also have the same MBP the author has and have used Aider with Qwen locally.)
Re: A guide to local coding models
#16This story talks about MLX and Ollama but doesn't mention LM Studio - https://lmstudio.ai/ LM Studio can run both MLX and GGUF models but does so from an Ollama style (but more full-featured) macOS GUI. They also have a very actively maintained model catalog at https://lmstudio.ai/models
LMStudio is so much better than Ollama it's silly it's not more popular.
LMStudio is not open source though, ollama is
but people should use llama.cpp instead
Re: A guide to local coding models
#17I'm curious what the mental calculus was that a $5k laptop would competitively benchmark against SOTA models for the next 5 years was. Somewhat comically, the author seems to have made it about 2 days. Out of 1,825. I think the real story is the folly of fixating your eyes on shiny new hardware and searching for justifications. I'm too ashamed to admit how many times I've done that dance... Local models are purely fo…
I agree with everything you said, and yet I cannot help but respect a person who wants to do it himself. It reminds me of the hacker culture of the 80s and 90s.
Re: A guide to local coding models
#18This story talks about MLX and Ollama but doesn't mention LM Studio - https://lmstudio.ai/ LM Studio can run both MLX and GGUF models but does so from an Ollama style (but more full-featured) macOS GUI. They also have a very actively maintained model catalog at https://lmstudio.ai/models
Makes me think it's a sponsored post.
LMStudio? No, it's the easiest way to run am LLM locally that I've seen to the point where I've stopped looking at other alternatives.
It's cross-platform (Win/Mac/Linux), detects the most appropriate GPU in your system and tells you whether the model you want to download will run within it's RAM footprint.
It lets you set up a local server that you can access through API calls as if you were remotely connected to an online service.
Re: A guide to local coding models
#19I appreciate the author's modesty but the flip-flopping was a little confusing. If I'm not mistaken, the conclusion is that by "self-hosting" you save money in all cases, but you cripple performance in scenarios where you need to squeeze out the kind of quality that requires hardware that's impractical to cobble together at home or within a laptop. I am still toying with the notion of assembling an LLM tower with a f…
If you ever do it, please make a guide! I've been toying with the same notion myself
If you want to do it cheap, get a desktop motherboard with two PCIe slots and two GPUs.
Cheap tier is dual 3060 12G. Runs 24B Q6 and 32B Q4 at 16 tok/sec. The limitation is VRAM for large context. 1000 lines of code is ~20k tokens. 32k tokens is is ~10G VRAM.
Expensive tier is dual 3090 or 4090 or 5090. You'd be able to run 32B Q8 with large context, or a 70B Q6.
For software, llama.cpp and llama-swap. GGUF models from HuggingFace. It just works.
If you need more than that, you're into enterprise hardware with 4+ PCIe slots which costs as much as a car and the power consumption of a small country. You're better to just pay for Claude Code.
Re: A guide to local coding models
#20Earlier quoted context omitted.
Makes me think it's a sponsored post.
LMStudio? No, it's the easiest way to run am LLM locally that I've seen to the point where I've stopped looking at other alternatives. It's cross-platform (Win/Mac/Linux), detects the most appropriate GPU in your system and tells you whether the model you want to download will run within it's RAM footprint. It lets you set up a local server that you can access through API calls as if you were remotely connected to an…
FWIW, Ollama already does most of this:
- Cross-platform
- Sets up a local API server
The tradeoff is a somewhat higher learning curve, since you need to manually browse the model library and choose the model/quantization that best fit your workflow and hardware. OTOH, it's also open-source unlike LMStudio which is proprietary.