Run LLMs Locally on CPU Without a GPU: A Guide

Running large language models locally without a dedicated GPU is now feasible using CPU-only inference. This guide details how to set up Ollama and run models like Llama 3.2, Mistral, and Qwen on standard computer hardware. Performance is influenced by RAM, quantization precision, CPU instruction sets like AVX2, memory bandwidth, and thread count, with specific hardware recommendations provided for different model sizes. AI

IMPACT Enables broader access to local LLM experimentation and development on standard hardware, reducing reliance on expensive GPUs.

RANK_REASON The article provides a guide on how to use existing tools and techniques to run LLMs on consumer hardware, rather than announcing a new model or significant research breakthrough.

Read on dev.to — LLM tag →

• Apple Silicon
• gemma3
• Llama 3.1
• Llama 3.2
• Ollama
• phi4-mini
• Qwen
• qwen2.5

• infra
• product

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