B
Aider logoAiderNo GPU, just RAM and patience

Run an LLM on a Cheap CPU-Only Box

setuproll@setuproll
78.0Overall score

Squeezes a usable open model onto a machine with no GPU by leaning on llama.cpp, aggressive quantization, and a small but sharp model. For homelab tinkerers and old-laptop owners who want local AI without buying hardware.

78.0Score
1.3kVotes
5Components

Install this build

Export
terminal
llama-server -hf bartowski/gemma-3-12b-it-GGUF:Q4_K_M -c 8192

Components

Model

  • Gemma 3 12B
  • Mistral Small 3.1 24B
  • Qwen3 8B

Stack

  • llama.cpp
  • llama-server built-in web UI

Hardware

  • 32GB system RAM
  • Modern multi-core CPU, AVX2

Quantization

  • Q4_K_M GGUF
  • Q3_K_M if RAM is tight

How it works

  • Build llama.cpp or grab a prebuilt binary
  • Download a GGUF quant from Hugging Face
  • Start llama-server with thread count matched to your cores
  • Open the built-in UI at localhost:8080, expect a few tokens per second

Summary

Squeezes a usable open model onto a machine with no GPU by leaning on llama.cpp, aggressive quantization, and a small but sharp model. For homelab tinkerers and old-laptop owners who want local AI without buying hardware.

78.0 score 1.3k votes

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