About LocalRig
LocalRig helps you decide what hardware actually runs a given large language model — by VRAM, memory bandwidth, and real tokens per second — instead of by marketing FLOPS or whatever pays the most. The guides are constraint-first: they start from your model and budget, then name the specific card, Mac, or mini-PC that fits.
How the guides are built
Every guide is built from compiled public benches — Hugging Face and Unsloth cards, official GitHub, Ollama, llama.cpp issues, and named X posts with a reproducible config — plus first-party testing only when LocalRig already owns the hardware. Community figures are labeled community-cited and dated. First-party figures say so, with runtime version, quantization, and measurement date.
What LocalRig will and won't do
- Recommends the best-fit option, never the best-paying one. Picks are ranked by which constraint you're optimizing, not by commission. Used cards, non-affiliate parts, and "rent in the cloud instead" are surfaced when they're the honest answer.
- Never fabricates a number. If a benchmark wasn't run and no cited source exists, the guide says so rather than inventing a figure.
- Dates its data. Prices, availability, and performance figures carry a data date, because the used-GPU market moves with every new release.
- Tells you when a guide is the wrong guide. Every article has a "Who this is NOT for" section.
How LocalRig makes money
LocalRig earns affiliate commissions when readers buy through some of its links, at no extra cost to the reader. That revenue is what makes the testing and writing sustainable — but it never decides the recommendation. Full details are on the affiliate disclosure page, and the testing rules are on the methodology page.
Contact
Corrections and questions are welcome — if a number looks wrong or out of date, tell us and it gets checked. Reach the editor at [email protected].