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330 points threeturn | 1 comments | | HN request time: 0.207s | 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 ◴[] 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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jckahn ◴[] No.45775069[source]
I don't ever want to be dependent on a cloud service to be productive, and I don't want to have to pay money to experiment with code.

Paying money for probabilistically generated tokens is effectively gambling. I don't like to gamble.

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nprateem ◴[] No.45775725[source]
Where did you get your free GPU from?
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1. serf ◴[] No.45778239[source]
GPUs can do other things. Cloud service LLM providers cannot.