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

326 points threeturn | 1 comments | 31 Oct 25 13:39 UTC | HN request time: 0.21s | 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.

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scosman ◴[31 Oct 25 17:15 UTC] No.45774360[source]▶
What are folks motivation for using local coding models? Is it privacy and there's no cloud host you trust?

I love local models for some use cases. However for coding there is a big gap between the quality of models you can run at home and those you can't (at least on hardware I can afford) like GLM 4.6, Sonnet 4.5, Codex 5, Qwen Coder 408.

What makes local coding models compelling?

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1. zargon ◴[31 Oct 25 21:29 UTC] No.45776913[source]▶
Another reason along with the others is that the output quality of the top commercial models varies wildly with time. They start strong and then deteriorate. The providers keep changing the model and/or its configuration without changing the name. With a local open weights model, you can learn each model's strengths and it can't be taken away with an update.