Cloud APIs are pay-per-call: cheap to start, linear forever. Self-hosting an open model is a fixed cost: dear at low volume, then it crosses over — and your data never leaves. Plug in your numbers, find your crossover, then see how every bake-off compounds into a moat.
The break-even
Same task, same quality bar already cleared. The only question left is unit economics at your volume. Drag the volume; edit the assumptions to match your stack.
Illustrative. Real self-hosting economics swing hard on batching, request size and GPU choice — that's why the assumptions are editable. The honest takeaway isn't a number, it's the shape: cloud wins small, self-hosting wins at scale, and the crossover is exactly the conversation an enterprise buyer wants to have.
The moat
A cloud-only "cheapest model" router is a few days of engineering — it's already commoditising. The defensible asset is the one that needs data you have to earn: run real tasks, accumulate verdicts nobody else has, and train a model on that. Drag to watch it compound.
Each customer task = a labelled verdict: which models cleared the bar, at what cost. Cheap to run, and every run is a proprietary data point.
With enough verdicts, a small learned router predicts the cheapest model that'll clear the bar — no full bake-off needed. Trained on your data, not generic chat benchmarks.
Enough domain data and you can distil a small model fine-tuned to a customer's task — one they own and run on their own hardware. Data-sovereign, cheap at scale, and yours to license.
The simple tool is the on-ramp: it validates demand and generates the only thing that makes the proprietary model possible — the data. Validation feeds the moat.
Plug in your real volume and quality bar, and see the verdict for yourself.
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