What Is a Local LLM? Local AI Explained for Beginners
Learn what a local LLM is, how it differs from cloud AI, what hardware you need, and how to start with Ollama or LM Studio on your own computer.
Local LLM setup guides
Run your first local language model on Mac, Windows, or Linux. Start with the basics, check your RAM and GPU memory, then follow the Ollama or LM Studio installation guide. Add document chat or a browser interface after the model is working.
The core path
Start with the guide for your next step.
Check your hardware, choose an app, and get a model answering. Review privacy settings before adding sensitive documents.
01What is a local LLM? Start with the basics02What local LLM can my computer run?03Ollama vs LM Studio04Local LLM RAM and VRAM requirements05Best local AI setup for Mac06Best local AI setup for Windows07How to install Ollama08How to install LM Studio09How to use Open WebUI with Ollama10How to chat with PDFs locally11Local AI privacy
Get a first local model working
Start with one app, one model that fits, and one successful response.
How to Install Ollama on Mac, Windows, and Linux
Install Ollama on Mac, Windows, or Linux, run your first local AI model, verify that it works, and avoid common storage, PATH, and first-run mistakes.
Download and Install LM Studio: Your First Local AI Model
Download and install LM Studio on Mac, Windows, or Linux. Check hardware requirements, download a model that fits, start a chat, and fix common setup problems.
How to Install Open WebUI With Ollama
Set up Open WebUI with Ollama using Docker or Python, connect your local models, and fix common connection and missing-model errors.
How to Use Model Context Protocol (MCP) with Local LLMs: LM Studio & Ollama Tutorial
Connect local LLMs to local files, databases, and APIs using the Model Context Protocol (MCP). Learn how to set up MCP in LM Studio and Ollama.
Choose hardware and models
Work from memory, GPU, task, and model size rather than parameter-count hype.
How to Install Ollama on Mac, Windows, and Linux
Install Ollama on Mac, Windows, or Linux, run your first local AI model, verify that it works, and avoid common storage, PATH, and first-run mistakes.
Download and Install LM Studio: Your First Local AI Model
Download and install LM Studio on Mac, Windows, or Linux. Check hardware requirements, download a model that fits, start a chat, and fix common setup problems.
Local LLM RAM and VRAM Requirements
Understand how model weights, quantization, context, RAM, dedicated VRAM, and Apple unified memory determine which local LLMs are practical.
The Complete Guide to Local AI Coding: Setting Up Cline, Continue.dev, and Aider with Local Models
Connect Continue, Cline, and Aider to Ollama or LM Studio. Check model fit, context, edit quality, and network settings before using local coding assistants.
How to Use Model Context Protocol (MCP) with Local LLMs: LM Studio & Ollama Tutorial
Connect local LLMs to local files, databases, and APIs using the Model Context Protocol (MCP). Learn how to set up MCP in LM Studio and Ollama.
Choose a Local AI Model for Coding
Choose a local coding model by memory and task, try Qwen2.5-Coder or a small Qwen3 model, and check generated code before connecting an agent.
Choose a Local AI Model for Writing
Use a local model for rewriting, outlines and drafting. Compare models with the same text, preserve facts and tone, and check memory and offline limits.
Run Local AI with 6GB of VRAM
Start local AI on a 6GB graphics card with a small quantized model. Check GPU use, context memory and offloading before trying a larger download.
Work with documents and private material
Check how an app reads, searches, and stores your files, and whether anything leaves your computer.
Chat With PDFs Locally
Chat with PDFs locally using LM Studio, Open WebUI, or AnythingLLM. Set up document retrieval, check privacy settings, and fix inaccurate answers.
Move Local AI Models to Another Drive
Free space by moving Ollama or LM Studio model downloads. Copy the correct folders, change the model directory, and confirm a model works before deleting originals.
Build a more advanced workflow
Connect a working model to a browser workspace, coding assistant, or another app.
How to Install Open WebUI With Ollama
Set up Open WebUI with Ollama using Docker or Python, connect your local models, and fix common connection and missing-model errors.
The Complete Guide to Local AI Coding: Setting Up Cline, Continue.dev, and Aider with Local Models
Connect Continue, Cline, and Aider to Ollama or LM Studio. Check model fit, context, edit quality, and network settings before using local coding assistants.
Choose a Local AI Model for Coding
Choose a local coding model by memory and task, try Qwen2.5-Coder or a small Qwen3 model, and check generated code before connecting an agent.
More practical guides
More help with models, setup, and everyday tasks.
Local AI Glossary
Plain-English definitions for local AI terms, including local LLMs, model size, quantization, context length, VRAM, unified memory, embeddings, and RAG.
What Local LLM Can My Computer Run?
Enter your hardware, understand the memory that matters, and choose a local model size that leaves enough headroom for context and normal work.
How to Run DeepSeek-R1 Locally
Choose the exact DeepSeek-R1 distilled model, check its memory requirements, and run it in Ollama or LM Studio with practical reasoning and licensing limits.
Run Local AI on Linux
Install Ollama on Linux, download a small local model, check the service and GPU, and fix common first-run failures without adding Docker.
Use Local AI Offline
Prepare a local model for offline chat, writing, coding, or documents. Check downloads, local providers and a fresh offline restart before travelling.
Does Local AI Have Unlimited Tokens?
Local models can avoid a hosted per-token charge, but context, response limits, memory, time and app licensing still matter. Learn which limit you are seeing.