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Home › Calculators › Build vs Buy AI
Free · No sign-up · 2026 prices

Should you build it or just buy it?

We benchmark your use case against 500+ AI builds. In 90 seconds you'll see the verdict, the 3-year TCO, and the 5 reasons we'd push back if you decided wrong.

500+ projects benchmarked 3-year TCO model Buy or build verdict
BUILD vs BUY · DECISION ENGINE Live estimate: —

What are you trying to build?

We've pre-loaded a factor weighting for each pattern. You can still override every value in the next steps.

Drives how we weigh time-to-value vs. long-term control.

Your data — and how sensitive it is

These two factors decide whether a vendor can even host the workload — and how unique your moat actually is.

Team, budget, runway

Your operational reality. We won't recommend Build if the staffing math doesn't survive year 1.

8 wk

Expected scale

Volume + token cost are the levers that determine whether vendor margins compound for or against you.

500,000
1200

Your decision

Weighted on 15 factors. Hover any card to see which inputs moved the needle most.

Recommendation
BUY
— confidence
◢ Decision report · v2.0

Run the calculator to see your verdict.

Pick options on each step — we'll model the math live.

    Buy Score · —/100
    $—
    3-yr TCO
    Time-to-value2–4 wk
    Marginal $/k inferences—
    Headcount0.5 FTE
    Build Score · —/100
    $—
    3-yr TCO
    Time-to-value3–6 mo
    Marginal $/k inferences—
    Headcount2 FTE

    3-year cost projection

    Buy Build
    Setup
    Year 1
    Year 2
    Year 3
    Cumulative

    Computing the verdict

    Crossing your inputs against 500+ benchmark projects.

    Scoring use-case fit —
    Modeling 3-year TCO —
    Weighting risk factors —
    Composing the verdict —
    Step 1 of 5 · Use case
    THE DECISION ENGINE

    What the engine actually weighs.

    Each factor moves the bias scale by a fixed amount. We've published the weights so you can challenge them. Calibration: 500+ live AI projects, 2024–2026.

    Factor Weight Why it matters
    Foundation-model fit ◢ BUY Generic LLM tasks are commoditised — don't reinvent GPT-class capability.
    Proprietary corpus ◢ BUILD Unique data is the only durable moat you can own.
    Time-to-market ◢ BUY Vendors ship in weeks; bespoke training in quarters.
    Inference volume ◢ BUILD Above ~50M calls/month, API margins flip against you.
    Latency ceiling ◢ BUILD Sub-300ms often requires co-located models, smaller weights.
    Regulatory residency ◢ BUILD Air-gapped, on-prem or sector audits constrain vendor choice.
    ML engineer density ◢ BUILD No team → no pager → no in-prod custom model.
    MLOps appetite ◢ BUILD Eval, drift monitoring, retraining — a full second product.
    Differentiation urgency ◢ BUILD If AI is the product — control weights, prompts, evals.
    Vendor lock-in tolerance ◢ BUILD Single-vendor pricing power → multi-year margin risk.
    Budget runway ◢ BUY Buy = opex, build = front-loaded capex + hiring.
    Eval maturity ◢ BUY Without strong evals, you can't tell if your model is worse.
    Multimodal requirements ◢ BUY Image + audio + text — foundation-model scale wins.
    Workflow orchestration ◢ BUILD Tool-calling, state, memory — the glue is always yours.
    Long-term unit economics ◢ BUILD At scale, fine-tuned small models are ~10× cheaper per call.
    THE NUMBERS

    Where the numbers come from.

    We refuse to ship a calculator without showing the math. These three sources back the cost and bias model.

    ◢ BENCHMARK

    a16z framework

    Build vs buy bias scoring derived from a16z's 2024 'AI build vs buy' framework, which audits 200+ enterprise projects.

    ◢ FIELD DATA

    CodeFormers field data

    TCO model calibrated on 500+ AI projects we shipped or audited 2024–2026. Hosted model prices reflect 2026 blended rates.

    ◢ RESEARCH

    Stanford HAI 2026 index

    Latency, fine-tune, and eval thresholds informed by the Stanford HAI 2026 AI Index report on production AI deployments.

    HONEST QUESTIONS

    Honest questions, honest answers.

    We don't gate this calculator behind a sign-up wall. Use it. Argue with it. Ship the right decision.

    No — in 2026, "build" almost always means fine-tuning or adapter-training a small open-weight model (Llama, Mistral, Qwen class) on your corpus, self-hosted, with your own eval suite. Training a frontier model from zero is a billion-dollar decision that sits outside this calculator entirely.
    Hosted foundation model (OpenAI, Anthropic, Azure AI, Gemini) + a thin orchestration layer + a vector store (Pinecone / pgvector) + an eval harness (Langfuse / Braintrust). Roughly 80% of our buy-leaning recommendations land on this shape.
    Because unit economics don't move linearly. Below ~2M monthly inferences, amortising fine-tune + infra + an MLE headcount over that volume is nearly always more expensive than pay-as-you-go. Above ~50M, the crossover flips. The slider reflects that curve.
    Yes — and that's the answer for ~40% of the projects we ship. Buy the foundation model, build the retrieval, evals and business logic. The calculator will still lean one direction so you can plan the dominant investment, but "hybrid" is the sensible default.
    Yes. We re-fit the pricing curves monthly against the current generation of frontier APIs and open-weight releases. The buy / build crossover has shifted roughly 3× toward "buy" since 2022 — this tool reflects the 2026 cost map.
    Only in your browser's localStorage, so you can come back and tweak. Nothing is sent to CodeFormers unless you explicitly click "Book a review" and fill the contact form.
    THE FREE-TOOL KIT

    The rest of the free-tool kit.

    Once you've made the build/buy call, here's what to model next.

    Project cost estimator

    Ballpark a web, mobile or AI build in 90 seconds. Scope, stack, timeline.

    →

    Tech stack finder

    Match your project shape to a proven stack — with known pitfalls and hiring cost.

    →

    AI search readiness

    Is your site cited by ChatGPT, Perplexity, Google AI Overviews? 40-point audit.

    →

    Tech debt calculator

    Quantify how much your codebase is quietly costing you in velocity.

    →
    YOU MODELED THE DECISION

    You modeled the decision. We'll ship the model.

    Bring the verdict to a 30-min review. We'll pressure-test it, lock in the architecture, and put a fixed-price scope on the table.

    Book the 30-min review →
    BUILDERS HUB //

    Buduj szybciej. Razem z founderami.

    Budujemy zamkniętą społeczność dla founderów i indie hackerów, którzy chcą zwalidowanych pomysłów, blueprintów architektury i wspólnego finansowania narzędzi — nie kolejnego martwego Slacka. Lista daje pierwszy dostęp, gwarantowaną cenę i bezpośredni kontakt z inżynierami, którzy to budują.