About Local AI Rigs
Local AI Rigs exists for one reason: to help you buy the right hardware for running AI locally, without wasting money on the wrong GPU or settling for performance that frustrates you within a week.
What We Cover
We're laser-focused on local AI hardware — GPUs, mini PCs, build guides, and the software that makes them useful. We don't cover gaming GPUs unless they're also great for AI. We don't cover smart home gadgets or retro handhelds. We cover the hardware you need to run LLMs, generate images, create AI videos, and build AI servers on your own infrastructure.
Who Runs Local AI Rigs
Local AI Rigs is written and maintained by Max — 20+ years in IT and operations, building custom PCs since 2000, and running open models like Gemma, Qwen, and Mistral on his own hardware: discrete GPUs alongside an Apple Mac Studio M2 (32GB) and a Mac Mini M4. The hardware judgments here come from that first-hand experience, not reworded spec sheets. Read more about Max.
Our Methodology
Every product recommendation goes through a fixed research protocol before it is published. We verify that the exact product is live and in stock, confirm the current price context, cross-check the specs that matter for local AI — VRAM, memory type, power draw, and software support — against at least two sources, and check whether a newer model has replaced the current pick. Every recommendation also names at least one buyer who should skip it. We pull live product data and current images directly from the retailer listing rather than reusing stale manufacturer copy.
Planning Estimates vs Measured Data
We are explicit about what kind of number you are reading. VRAM figures, electricity costs, and model-fit verdicts in our tools are planning estimates derived from transparent math — parameter count, bytes per parameter, quantization, and context overhead — and we label them as such. We never publish invented tokens-per-second figures or fabricated benchmark numbers. Where we cite throughput, it references community-validated data (LM Studio Community, r/LocalLLaMA, llama.cpp benchmarks) or our own runs, and we say which.
Freshness
Hardware pricing and model availability move fast, so a recommendation is only as good as its last check. We re-verify our core money pages on a recurring cadence, refresh the answer and pricing context when the market shifts, and update the "Updated" date on a page only when the content has meaningfully improved. When a product is discontinued or superseded, we say so rather than leaving a dead recommendation in place.
Affiliate Disclosure
We participate in the Amazon Associates program and may earn small commissions from qualifying purchases made through our links. This never affects our recommendations — we recommend the hardware we'd actually buy and use. Our goal is trust, not quick commissions.
How to Reach Us
Questions, feedback, or corrections? We read everything and we update pages when readers catch something we missed. If a price, spec, or compatibility note looks wrong, tell us — accuracy is the whole point of the site.