Cheatsheet 05 — Open-Source vs Commercial Models

The build-vs-buy of models. Full: Phase 5.01, Phase 6.

The tradeoff at a glance

DimensionCommercial API (OpenAI/Anthropic/Google)Open-weight self-hosted (Llama/Qwen/Mistral)
Quality ceilingUsually highest (frontier)Strong, narrowing gap
Speed to startInstant (API key)Slow (infra/ops)
Cost at low volumeCheap (pay per token)Expensive (idle GPU)
Cost at high volumeExpensive (per-token adds up)Cheaper (past break-even)
Data control / privacyData leaves your boundary (DPA/ZDR matters)Full control (data never leaves)
Residency / air-gapLimited (provider regions)Full (run anywhere, on-prem)
CustomizationLimited (their fine-tune API)Full (LoRA/full FT, your stack)
Ops burdenNone (managed)High (you run GPUs)
Model choiceTheir catalogAny open model
Vendor lock-inYesNo

Choose commercial when…

  • You're early / need speed; low or spiky volume.
  • You want the frontier quality ceiling.
  • You don't have GPU/ops capacity.
  • Data-use terms (no-train tier + DPA/ZDR) satisfy your privacy needs (Phase 14.02).

Choose open-weight self-hosted when…

  • Data residency / privacy / air-gap is required (healthcare, defense, finance) (Phase 14.07).
  • High, steady volume → past the self-hosting break-even (Phase 15.05).
  • You need deep customization (fine-tune the weights, Phase 13).
  • You want no vendor lock-in / full cost control.

Hybrid (common in production)

  • Commercial for hard/rare requests, self-hosted for the cheap bulk (route, cheatsheet 13).
  • Commercial now, migrate hot paths to self-hosted as volume grows.
  • Open-weight for sensitive tenants (on-prem/VPC), commercial SaaS for the rest.

License gotchas 🚩

  • "Open weights" ≠ "open source" ≠ "free for commercial use" — read the license (some restrict commercial use, competing-model training, or scale).
  • Llama community license, Apache-2.0, MIT, custom RAIL — each differs. Verify before shipping.

Interview line

"Commercial for speed and the quality ceiling at low/spiky volume; open-weight self-hosted for residency, deep customization, and cost at high steady volume. Most production stacks are hybrid — route the cheap bulk to a self-hosted model and the hard tail to a frontier API."


Next: 06 — Quantization · Full: Phase 5.01