Knowledge base · OpenSourcesAI

Everything you need to build with local AI.

Seven topic areas — from basic concepts to advanced workflows. Jump to the right section using the links below, or start with the orientation if you're new to local AI.

New to local AI? Start the 15-minute orientation →

Jump to topic

Not sure where to start?

Use the Start Here page for a guided orientation.

The Start Here page walks you through the key concepts, hardware check, and first tools in order — no searching required.

Go to Start Here Check hardware fit Browse guides

Quick-access tools

Start with a tool, not a doc

These interactive tools get you to an answer faster than reading a guide.

LLM Compatibility CheckerMatch GPU VRAM to model sizesOpen →Model Builder WizardAnswer 5 questions, get a model shortlistOpen →AI PlaygroundTest prompts in the browser before downloading modelsOpen →

Reference index

Browse by topic

Start here

Local AI Foundations

Core concepts every local AI builder needs before choosing tools, models, or hardware. Covers what local LLMs are, how inference works, and what the key terms mean.

What is a local LLM?Guide What is VRAM and how much do you need?Guide Open-weight vs open-source AIGuide Start here: beginner orientationOverview

Hardware

Hardware & VRAM Planning

How to match model size to GPU memory, quantization tiers, KV cache overhead, CPU offload, and Apple Silicon unified memory considerations.

What is VRAM for local AI?Guide Local LLM compatibility checkerTool Model builder wizardTool Set up local LLMs on WindowsGuide

Models

Models & Quantization

Open-weight model families, quantization formats (GGUF, Q4, Q8, FP16), parameter counts, context windows, and how to choose the right model for your hardware and task.

Browse all model familiesHub How to test open-weight coding modelsGuide Choose a model for coding, RAG, agentsGuide Frontier model comparisonOverview

Tools & runtimes

Tools & Runtimes

Local LLM runners (Ollama, LM Studio, Jan), web interfaces (Open WebUI), inference servers (vLLM, GPUStack), and how to connect them into a working workflow.

Browse all AI toolsHub Ollama tool profileTool LM Studio tool profileTool Open WebUI tool profileTool

RAG & data

RAG & Private Data

Retrieval-augmented generation architecture, embedding models, vector databases, chunking strategies, and how to build a private document search workflow locally.

Build a local RAG stack (Ollama + Qdrant)Guide Choose a vector database for RAGGuide Browse RAG toolsBest-of Qdrant tool profileTool

Agents & MCP

Model Context Protocol architecture, MCP servers and clients, agent tool use, security boundaries, and how to extend AI agents with reusable external connections.

What is MCP for AI agents?Guide MCP security best practicesGuide MCP integrations hubHub Browse MCP integrationsHub

Coding & IDE

Coding Assistants & IDE Workflows

AI coding assistants, IDE integrations, local vs hosted models for code, code review agents, and how to set up Continue, Cline, Cursor, or Windsurf with a local backend.

Best open-source AI coding assistantsBest-of Cursor vs Windsurf vs ClineCompare Continue tool profileTool Cline tool profileTool