Running LLMsOn Your Own Computer
Local LLMs let you run AI models on your own hardware — no cloud, no API costs, no data leaving your machine. With tools like Ollama and open-source models like Llama 3, you can have ChatGPT-like AI running entirely offline.
Why Run LLMs Locally?
The benefits of keeping AI on your own hardware
Privacy
Your data never leaves your machine. No API calls, no servers, no data collection.
Free (After Hardware)
No API costs. Run unlimited queries once you have the model.
Offline Access
Works without internet. Use AI on planes, in remote areas, or air-gapped networks.
Full Control
No rate limits, no content filters you don't want, no API changes breaking your app.
Low Latency
No network round-trip. Responses start immediately.
Customization
Fine-tune, modify prompts, combine with local tools. Complete flexibility.
The Tradeoffs
Hardware Requirements
Good models need good GPUs. A 7B model needs 8GB+ VRAM.
Quality Gap
Local models are great but not GPT-4/Claude level. Expect 70-90% of cloud quality.
Setup Complexity
More technical than calling an API. But tools like Ollama make it much easier.
Updates
You manage model updates yourself. Cloud APIs update automatically.
Bottom line: Local LLMs are amazing for privacy, cost, and control. But if you need GPT-4-level quality or don't have a good GPU, cloud APIs are still the way to go.
Tools for Running Local LLMs
From beginner-friendly to power-user options
Ollama
Easy All-in-One
The easiest way to run LLMs locally. One-line install, simple CLI.
Command
ollama run llama3
Best for: Beginners, quick setup
LM Studio
GUI Application
Beautiful desktop app for Mac/Windows/Linux. Browse and chat with models visually.
Command
Download from website
Best for: Non-technical users
llama.cpp
Core Engine
The C++ engine that powers most local LLM tools. Maximum performance.
Command
./main -m model.gguf
Best for: Performance, custom builds
GPT4All
Desktop + Chat
Desktop app with built-in models. Focus on privacy and ease of use.
Command
Download from website
Best for: Privacy-focused users
Popular Open-Source Models
The best models you can run locally
Llama 3 8B
Meta's latest. Great all-around model.
Needs: 8GB VRAM
Mistral 7B
Efficient and fast. Great for coding.
Needs: 6GB VRAM
Phi-3 Mini
Microsoft's small model. Surprisingly capable.
Needs: 4GB VRAM
Llama 3 70B
The big one. Closest to cloud quality.
Needs: 48GB+ VRAM
Hardware Requirements
What you need to run different model sizes
Budget Laptop
Integrated / No GPU • 16GB RAM
Gaming PC
RTX 3060/4060 (8GB) • 32GB RAM
Workstation
RTX 3090/4090 (24GB) • 64GB RAM
Pro Setup
Multiple 4090s / A100 • 128GB+ RAM
Quickstart with Ollama
From zero to AI in 2 minutes
Install Ollama
One-line install on Mac/Linux.
Command
curl -fsSL https://ollama.ai/install.sh | sh
Pull a Model
Download Llama 3 (about 4GB).
Command
ollama pull llama3
Start Chatting
Interactive chat in your terminal.
Command
ollama run llama3
Use the API
OpenAI-compatible API on localhost:11434
Command
curl localhost:11434/api/generate -d '{"model":"llama3","prompt":"Hello"}'Best Use Cases
Where local LLMs really shine
Private Document Q&A
Ask questions about sensitive documents without sending them to the cloud.
Example: Legal docs, medical records, financial data
Offline Coding Assistant
Code completion and help without internet.
Example: Air-gapped development, travel coding
Local Development/Testing
Test AI integrations without API costs.
Example: Prototyping, CI/CD testing
Privacy-First Apps
Build applications where user data never leaves their device.
Example: Personal assistants, journaling apps