Ask HN: What does your local LLM setup looks like? | Hacker News Reader

Ask HN: What does your local LLM setup looks like?

6 pointsthe-mitr7 comments

What models and hardware you are using? For what purpose? What were the challenges? Any tricks that helped you in doing this?

This might help new users like me setup theirs.

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RTX 5090, just because it dual boots as a gaming rig. I have a llama server usually with `gemma4:31b` or `qwen3.6:27b` that powers my own automation / orchestration harness.

If I can go back in time, I would probably buy a more AI dedicated machine but I also don't regret finally being able to play Cyberpunk in 4k with great FPS and overkill mods.

I bought a pretty powerful desktop computer for gaming in late 2025. It came with an RTX 5080, which I started using to run some local LLMs and run some experiments (most recently, I was trying to get agents to get better at playing Zork I).

I've mostly enjoyed having WSL to leverage Linux dev tools, but it seems like it's still adding overhead that prevents me from taking advantage of the GPU in full, so I'll likely get another drive and install Linux.

I tried Qwen, Llama, Mistral and Gemma. Gemma 4 was pretty impressive.

I used Gemma 4 on a budget PC to work with an AI that thinks in a new way. Since I am testing how far it can be controlled and developed through simple conversation rather than heavy-duty tasks, I dedicated all the low-end PCs to Gemma. I am satisfied with the test results.

V100 32G SXM2 adapted to PCIE. Running llamacpp with Q4KM Qwen 3.6 27B or Gemma 4 31B. I use them when I feel of privacy is important or I just want to mess around.

I have a Mac mini (the square one, idk the model) with M3 chip.

Runs pretty well with Ollama on the Qwen models. It seems like Qwen has done a great job with speed.

Claude.MD and other MD context files with guardrails and enforcement?

Are you offering something in this space?

Thanks for the reply. No, just trying to setup something locally for myself.

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