How to Choose a Local LLM for Your Hardware (Without Guessing)
This story is from 2026-10-12. It is preserved in the archive; the latest stories are on the live feed.
Running a language model on your own machine has obvious appeal: your data stays local, there's no per-token bill and you can work offline. But the choice usually starts in the wrong place, with a parameter count or a leaderboard. A model that excels at code completion may be a poor choice for summ…
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- 2026-10-12 10:32 · DEV Community — Machine Learning
How to Choose a Local LLM for Your Hardware (Without Guessing)