Who This Is For
Beginner to intermediate.
Think of it like buying a vehicle for the driving you actually do. A daily commuter doesn't need a truck's towing capacity, and you're not towing a boat with a compact hatchback either.
What You'll Build
A realistic model size and hardware target chosen for your actual use case.
Prerequisites
- None, this is a planning guide to read before buying anything
What Determines Local AI Performance
- Model parameter count
- Quantization level
- Context length
- System RAM
- GPU VRAM
- GPU memory bandwidth
- CPU capability
- Storage speed
CPU-Only vs. GPU-Accelerated
CPU-only inference works for small models but is noticeably slower; a consumer GPU with enough VRAM changes the experience dramatically for anything beyond small models.
Suggested Tiers
- An existing laptop or desktop, fine for small models and basic chat/summarization
- Mini PC with 16–32GB RAM, comfortable for mid-size models on CPU
- Apple Silicon system, strong unified-memory performance for its power draw
- Consumer NVIDIA GPU system, best price-to-performance for serious local inference
- Dedicated AI workstation, only worth it once local AI is a core part of your workflow
What to Realistically Expect
- Small models: fine for basic chat and summarization
- Larger models: needed for coding and complex reasoning tasks
- Larger context windows always mean more memory usage, regardless of model size
Benchmark What Actually Matters
- Tokens per second
- Time to first token
- RAM/VRAM usage under load
- Usable context size before things slow down
Honest "Don't Buy This for Local AI" Examples
Very old laptops with 8GB RAM and no discrete GPU, and any system without enough RAM to even load a mid-size model, will produce a frustrating experience regardless of CPU clock speed.
Security & Backup Notes
Troubleshooting
Lab Finish Line
You've selected a realistic model size and hardware target for your actual use case.