How to Run LLMs Locally in 2025: The Complete Guide

TL;DR: You can run powerful AI models on your own computer—no API costs, no data leaving your
machine. This guide covers Ollama, LM Studio, and other tools for local LLM hosting in 2025.

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Why Run LLMs Locally?

• Privacy: Your data never leaves your computer
• Cost: No per-token API charges
• Offline access: Works without internet
• Customization: Fine-tune models for your use case
• Speed: No network latency (depends on hardware)

Hardware Requirements

What you need depends on the model size:

Model Size	RAM	GPU VRAM	Example Models
7B parameters	8-16GB	6-8GB	Mistral 7B, Llama 3.2 7B
13B parameters	16-32GB	10-12GB	Llama 3.1 13B
34B+ parameters	32-64GB	24GB+	CodeLlama 34B, larger models
70B+ parameters	64GB+	48GB+ or multi-GPU	Llama 3.2 70B

For most users: A 7B model on a computer with 16GB RAM and an RTX 3060/4060 (8-12GB VRAM) works
well.

Ollama (Recommended for Beginners)

Ollama is the easiest way to run LLMs locally. It’s free, open-source, and works on Mac, Windows, and Linux.

Installation

# macOS/Linux
curl -fsSL https://ollama.com/install.sh | sh

# Windows - download from ollama.com

Running a Model

# Download and run Llama 3.2
ollama run llama3.2

# Or try Mistral
ollama run mistral

# For coding
ollama run codellama

Using with APIs

Ollama runs a local API server on port 11434:

curl http://localhost:11434/api/generate -d '{
  "model": "llama3.2",
  "prompt": "Why is the sky blue?"
}'

Popular Ollama Models

Model	Size	Best For
llama3.2:7b	4.7GB	General purpose
mistral	4.1GB	Fast, efficient tasks
codellama	3.8GB	Code generation
llama3.2:70b	40GB	Maximum quality
phi3	2.3GB	Lightweight, fast

LM Studio (Best GUI)

LM Studio provides a beautiful desktop app for running local models. No terminal required.

Features

• Point-and-click model downloads
• Chat interface like ChatGPT
• Model comparison side-by-side
• Local API server
• Runs on Mac, Windows, Linux

Getting Started

1. Download from lmstudio.ai
2. Search for a model (e.g., “Llama 3.2”)
3. Click Download
4. Start chatting

Best For

Non-developers who want a ChatGPT-like experience locally.

GPT4All

GPT4All is designed specifically for local, private AI. It includes:

• Desktop app (cross-platform)
• Curated model library
• LocalDocs feature (chat with your files)
• Privacy-focused design

Local Document Chat

GPT4All’s killer feature is LocalDocs—point it at a folder, and it can answer questions about your documents
without uploading them anywhere.

Text Generation Web UI (for Power Users)

Oobabooga’s Text Generation Web UI offers the most customization:

• Support for many model formats
• Fine-tuning capabilities
• Multiple inference backends
• Extensions ecosystem

Best for: Users who want maximum control and are comfortable with setup complexity.

Model Recommendations for 2025

Best General Purpose

Gpt-oss-120b – Meta’s latest models offer the best quality-to-size ratio.

Best for Coding

CodeLlama 34B or DeepSeek Coder – Purpose-built for code generation.

Best for Low-End Hardware

Gpt-oss-20b– Great performance in smaller packages.

Best for Long Context

Llama 3.2 with 128K context – Handles large documents well.

Performance Tips

1. Use quantized models: Q4 or Q5 quantization reduces size with minimal quality loss
2. GPU offloading: Put as many layers on GPU as VRAM allows
3. Batch requests: Increase throughput for multiple queries
4. Right-size your model: Don’t use 70B when 7B does the job

Integrations

Use with VS Code/Cursor

Point your code editor’s AI features at your local Ollama server for code completion without cloud APIs.

Use with Python

from langchain_community.llms import Ollama

llm = Ollama(model="llama3.2")
response = llm.invoke("Explain quantum computing")

Use with Open WebUI

Open WebUI provides a ChatGPT-like interface that connects to Ollama. Best for teams wanting a shared local AI
interface.

Comparison Summary

Tool	Best For	Difficulty
Ollama	Developers, CLI users	Easy
LM Studio	Non-technical users	Easiest
GPT4All	Document Q&A, privacy	Easy
Text Gen WebUI	Power users, customization	Medium

The Bottom Line

Running LLMs locally in 2025 is easier than ever. For most users:

1. Start with Ollama (if comfortable with terminal) or LM Studio (if you want a GUI)
2. Try Llama 3.2 7B – it’s the best balance of quality and resource requirements
3. Upgrade to larger models as needed

You don’t need to pay for API access to have AI on your machine. The local LLM ecosystem is mature, capable, and
free.