What is Local Models? Definition & Meaning

Local models are AI language models that run entirely on your own hardware — your laptop, desktop, or server — rather than through cloud APIs. They offer privacy, offline access, and zero API costs, though they require capable hardware and typically perform below the largest cloud models.

Local models put AI directly on your machine. No API keys, no internet required, no data leaving your computer.

Why Run Models Locally?

Cloud APIs	Local Models
Best quality models	Good but smaller models
Pay per token	Free after download
Requires internet	Works offline
Data sent to servers	Data stays on your machine
No hardware requirements	Needs capable GPU/CPU

Getting Started

Tools for Running Local Models

Tool	Platform	Notes
Ollama	Mac, Linux, Windows	Simplest to start with
LM Studio	Mac, Windows	Visual interface
llama.cpp	All	Maximum performance

Quick Start with Ollama

ollama pull llama3
ollama run llama3

That's it. You're running AI locally.

Hardware Requirements

Model Size	RAM Needed	GPU Recommended
7B parameters	8GB+	Optional
13B parameters	16GB+	Recommended
70B parameters	64GB+	Required

When to Use Local vs Cloud

Use local models when:

Privacy is critical (sensitive code, private data)
You want zero ongoing costs
You're experimenting frequently
Internet is unreliable

Use cloud APIs when:

You need the best quality output
Complex reasoning tasks
Production applications
You want the latest model capabilities

Local Models for Vibe Coding

Local models work well for quick prototyping, learning, and tasks where privacy matters. For serious development work, cloud models still lead in quality — but the gap is closing rapidly.

Local Models

Example