PRIVATE · PRACTICAL · LOCAL
Run AI locally,
on your computer.
Evidence-based setup instructions, model-selection criteria, and realistic hardware guidance—without the hype.
$ ollama run gemma3:4b
pulling manifest ··· done
loading model locally ··· done
› Where is my document sent?
This conversation is processed on this computer.
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FIRSTNO CLOUD REQUIRED
Local AI for Beginners: Where Should You Start?
A practical introduction to local AI, from choosing a runtime and model to testing quality on your own computer.
Read guide →What can my computer run?
We use the lowest of the three components as a conservative estimate.
Chat, translation, and summaries
Limiting components: CPU · RAM · GPU
A planning estimate; actual speed and compatibility depend on the model and runtime.
See the full tier guide →GUIDE LIBRARY
Browse all guides
Find exactly what you need, from setup to hardware.
Local AI for Beginners: Where Should You Start?
A practical introduction to local AI, from choosing a runtime and model to testing quality on your own computer.
Install Ollama and Run Your First Local Model
Install Ollama on macOS, Windows, or Linux, run a model, verify GPU loading, and troubleshoot common failures.
How Much RAM and VRAM Do Local LLMs Need?
Estimate model-weight memory, understand context overhead, and choose a realistic model size for your hardware.
Local AI Privacy and Security Checklist
Map document paths, logs, backups, cloud features, model files, and network exposure before using sensitive data.
LM Studio Setup: Run Your First Local LLM
Check requirements, find a GGUF model, choose quantization, load it into memory, and verify offline operation.
Build Your First Local AI App with the Ollama API
Call localhost, manage chat messages, choose streaming, request structured JSON, and handle failures safely.
Local RAG: Search Your Documents with a Local LLM
Understand extraction, chunking, embeddings, retrieval, grounded answers, evaluation, and deletion in a local RAG pipeline.
GGUF Quantization: Q4 vs Q5 for Local LLMs
Learn what GGUF stores, how quantization trades memory for precision, and how to compare Q4 and Q5 on your hardware.
How to Evaluate a Local LLM for Your Real Work
Build a fixed prompt set, repeat tests, score quality and operations separately, and define a rational model-switching threshold.
Mac vs NVIDIA PC for Local AI
Compare unified memory, dedicated VRAM, CUDA and Metal ecosystems, mobility, upgrades, and real workload fit.
Run Local AI on an Old Laptop
Check CPU features, RAM, storage, heat, and a small model before replacing an older computer.
Connect Open WebUI to Ollama
Run Open WebUI with Docker, connect it to local Ollama, and understand ports, accounts, and persistent data.
Install llama.cpp and Run a GGUF Model
Choose an official installation path, run a licensed GGUF in the CLI, then start a local compatible server.
How to Compare Local LLMs for Korean
Evaluate Korean comprehension, summaries, register, evidence, and consistency with a fixed task set.
Context Length and KV Cache Explained
Understand how long context affects memory and latency, then set only what the task needs.
Summarize PDFs with Local AI
Extract clean text, preserve page evidence, summarize in stages, verify claims, and delete every derived copy.
Local Speech-to-Text with Whisper
Install ffmpeg and Whisper, transcribe a short public recording, and review names, numbers, and sensitive artifacts.
Secure a Local AI API
Keep localhost as the default and add authentication, TLS, network policy, limits, and monitoring before remote access.
Benchmark Local LLM Speed Correctly
Separate loading, time to first token, and generation throughput under repeatable conditions.
Used PC and GPU Buying Checklist for Local AI
Verify VRAM, compatibility, power, cooling, condition, and a real model run before buying used hardware.
Category images: Unsplash
ZERO TO LOCAL
Start in about
30 minutes.
- 01
Check your computer
Use memory and GPU capacity to choose a realistic model size.
- 02
Install one runtime
Begin with Ollama or LM Studio instead of combining multiple tools.
- 03
Start small
Use a 3B–8B quantized model to establish a reliable baseline.
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We document what is reproducible, not merely fast.
Every guide includes its verification scope, update date, and primary sources.