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Ask HN: Who uses open LLMs and coding assistants locally? Share setup and laptop

326 points threeturn | 3 comments | 31 Oct 25 13:39 UTC | HN request time: 0.637s | source

Dear Hackers, I’m interested in your real-world workflows for using open-source LLMs and open-source coding assistants on your laptop (not just cloud/enterprise SaaS). Specifically:

Which model(s) are you running (e.g., Ollama, LM Studio, or others) and which open-source coding assistant/integration (for example, a VS Code plugin) you’re using?

What laptop hardware do you have (CPU, GPU/NPU, memory, whether discrete GPU or integrated, OS) and how it performs for your workflow?

What kinds of tasks you use it for (code completion, refactoring, debugging, code review) and how reliable it is (what works well / where it falls short).

I'm conducting my own investigation, which I will be happy to share as well when over.

Thanks! Andrea.

1. Greenpants ◴[01 Nov 25 07:39 UTC] No.45779881[source]▶
I got a personal Mac Studio M4 Max with 128GB RAM for a silent, relatively power-efficient yet powerful home server. It runs Ollama + Open WebUI with GPT-OSS 120b as well as GLM4.5-Air (default quantisations). I rarely ever use ChatGPT anymore. Love that all data stays at home. I connect remotely only via VPN (my phone enables this automatically via Tasker).

I'm 50% brainstorming ideas with it, asking critical questions and learning something new. The other half is actual development, where I describe very clearly what I know I'll need (usually in TODOs in comments) and it will write those snippets, which is my preferred way of AI-assistance. I stay in the driver seat; the model becomes the copilot. Human-in-the-loop and such. Worked really well for my website development, other personal projects and even professionally (my work laptop has its own Open WebUI account for separation).

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2. mark_l_watson ◴[01 Nov 25 11:41 UTC] No.45780903[source]▶
I like your method of adding TODOs in your code, then using a model - I am going to try that. I only have a 32G M2 Mac so I have to use Ollama Cloud to run some of the larger models but that said I am surprised by what I can do ‘all local’ and it really is magical running all on my own hardware, when I can.
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3. Greenpants ◴[01 Nov 25 18:51 UTC] No.45784261[source]▶
The TODOs really help me get my logic sorted out first in pseudocode. Glad to inspire someone else with it!

I've read that GPT-OSS:20b is still a very powerful model, I believe it fits in your Mac's RAM as well and could still be quite fast to output. For me personally, only the more complex questions require a better model than local ones. And then I'm often wondering if LLMs are the right tool to solve the complexity.