Run AI on Your Hardware
The definitive guide to deploying AI locally. From your first local chatbot to enterprise-scale deployment — we cover every tool, model, and technique.
Why Run AI Locally?
Complete Privacy
Your data never leaves your machine. No API calls, no telemetry, no cloud processing. Essential for healthcare, legal, and enterprise.
Zero API Costs
No per-token pricing. Run unlimited queries after the one-time hardware investment. Break even in weeks at scale.
No Latency
No network round-trips. Local inference starts immediately. Critical for real-time applications and interactive workflows.
Works Offline
No internet required. Your AI works on planes, in air-gapped environments, and during outages.
Full Customization
Fine-tune models on your data. Choose any model, quantization, and configuration. No vendor restrictions.
Data Sovereignty
Meet GDPR, HIPAA, and SOC2 requirements by keeping data processing entirely within your infrastructure.
Explore the Local AI Ecosystem
We cover every major tool in the local AI space — not just our own. From inference engines to fine-tuning frameworks, find the right tool for your needs.
Inference Engines
Run AI models on your hardware
Desktop Apps
Chat with AI on your computer
Web Interfaces
Self-hosted ChatGPT alternatives
Developer Frameworks
Build apps with local AI
Mobile AI
On-device AI for phones
Fine-Tuning
Train your own models
Start Deploying
Step-by-step guides for every platform, use case, and skill level.
What Is a Local LLM?
The complete beginner's guide to running AI on your own hardware.
BeginnerYour First Local AI in 5 Minutes
Install Ollama and start chatting with an AI model in under 5 minutes.
IntermediateChoose the Right Local LLM
A decision framework for picking the best model for your hardware and use case.
IntermediateBuild a Local RAG Chatbot
Chat with your documents privately using embeddings, vector search, and local models.
IntermediateLocal AI Code Assistant
Set up a free, private Copilot alternative with Continue + Ollama.
AdvancedEnterprise Local AI Deployment
Deploy LLMs for your organization with compliance, security, and scale.
Built by Cognisoc
Open-source tools we build and maintain for the local AI ecosystem.
Mullama
Local LLM inference engine with bindings for Python, Node.js, Go, Rust, PHP, and C/C++. Ollama-compatible CLI with embedded mode.
Learn more → Mobile AILlamafu
Flutter plugin for on-device AI on Android and iOS. Text generation, chat, vision, function calling, and structured JSON output.
Learn more → EducationalZigLLM
Learn transformer internals from first principles. 18 model architectures implemented in Zig with 285+ tests.
Learn more →Frequently Asked Questions
What is a local LLM?
A local LLM (Large Language Model) is an AI model that runs entirely on your own hardware — your desktop, laptop, phone, or server — instead of sending data to cloud services like OpenAI or Google. This gives you complete privacy, zero API costs, and offline availability.
Can I run AI locally without a GPU?
Yes. Tools like Ollama and llama.cpp support CPU-only inference. Smaller models (1B-7B parameters) with quantization (Q4_K_M) run well on modern CPUs with 8-16GB RAM. A GPU dramatically improves speed but is not required to get started.
What hardware do I need to run a local LLM?
For small models (7B), you need 8GB RAM or 6GB VRAM. For medium models (13B-30B), 16-32GB RAM or 12-24GB VRAM. For large models (70B+), 64GB+ RAM or 48GB+ VRAM. Apple Silicon Macs with unified memory are excellent for local AI thanks to shared CPU/GPU memory.
What is the easiest way to run an LLM locally?
Install Ollama (one command on Mac/Linux, installer on Windows), then run "ollama run llama3.2" in your terminal. You will be chatting with a local AI in under 5 minutes. For a graphical interface, try LM Studio or Open WebUI.
Is local AI as good as ChatGPT?
For many tasks, yes. Models like Llama 3.2 70B, DeepSeek-R1, and Mistral Large rival GPT-4 on coding, reasoning, and creative writing. Smaller models (7B-13B) are great for chat, RAG, and specific tasks. The gap continues to narrow with each model release.
Is my data private when using local AI?
Completely. When you run a model locally, your data never leaves your machine. There are no API calls, no telemetry, and no cloud processing. This makes local AI ideal for sensitive documents, healthcare, legal, and enterprise use cases.