Sunk Cost – How long until a local LLM rig pays for itself?
Pick a Mac mini, Mac Studio, DGX Spark or Strix Halo box, see which open models fit and how fast they run, and how much usage it takes to break even against paying an API. It is willing to say: it doesn
Sunk Cost – How long until a local LLM rig pays for itself? launched on September 15, 2026 with 47 votes, #684 of 8,094 launches that month and more than 95% of that year's launches.
In plain words
Sunk Cost helps users determine whether buying local hardware to run open-source language models is financially worthwhile compared to paying for API access. It lets users select specific machines like Mac mini, Mac Studio, or DGX Spark, see which models fit, measure their speed, and calculate the usage threshold needed to break even. The tool provides measured benchmarks where available and estimates where data is unavailable, giving users a practical way to evaluate the cost-benefit of local versus cloud-based LLM usage.
written from the facts on this page · September 2026
From the sources
If you buy a machine to run local models, how long until it pays for itself, and what can it actually do? Where nothing has been measured, local speed is estimated as memory bandwidth ÷ bytes read per token × , and labelled as such. API speed only affects the time comparison. Capability ratings and the frontier comparison are a judgement call informed by public benchmarks, coarse on purpose. If one looks wrong, tell usfrom sunkcost.ai
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