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Build, Buy, or Fine-Tune

The Build vs Buy Matrix

8 min+70 XPStep 1/10

Three lanes, three trade-offs

  • Frontier APIs — rent the best models by the token. Fastest to market, zero ML headcount, costs that scale with usage. The catch: your margin lives on their price list, and your capability is everyone else's
  • Open-weight models — download Llama- or Mistral-class weights and run them yourself or via a host. You own the model and your data never leaves your walls — but you now own GPU ops, latency tuning, and the upgrade treadmill
  • Custom training — train or heavily fine-tune from scratch. Rational only when AI is the product, or your data enables something nobody can rent

The honest default for most products: start on APIs, move to open weights when volume or privacy math forces it, custom-train almost never.

insight

Ask 'is this capability my differentiation?' If AI is the product, owning the stack matters. If AI is a feature inside the product, renting is almost always correct.