How many tokens does a proof of concept take to build with AI?
A proof of concept / prototype typically takes about 798,000 tokens to build with an AI coding agent (roughly 320,000–1,810,000 depending on complexity), about $2.36 at today's GPT-4o prices ($0.9500–$5.35). This is the build-time (developer) cost, not the cost of running the finished feature.
A proof of concept trades polish for speed: enough working code to demo an idea or de-risk an approach, with minimal tests. Token usage lands between a single feature and an MVP, depending on how much you throw away.
Token & cost ranges
Cost uses GPT-4o at current prices. Verified 29 July 2026.
| Scenario | Input tokens | Output tokens | Total tokens | Est. cost |
|---|---|---|---|---|
| Low (simple) | 300,000 | 20,000 | 320,000 | $0.9500 |
| Typical | 750,000 | 48,000 | 798,000 | $2.36 |
| High (complex) | 1,700,000 | 110,000 | 1,810,000 | $5.35 |
Typical cost by model
The same typical token estimate priced across a few common coding models.
| Model | Typical cost | Range (low–high) |
|---|---|---|
| GPT-4o | $2.36 | $0.9500 – $5.35 |
| GPT-4o mini | $0.1413 | $0.0570 – $0.3210 |
| Claude Sonnet 4.6 | $2.97 | $1.20 – $6.75 |
| Gemini 2.0 Flash | $0.0942 | $0.0380 – $0.2140 |
How we estimate this
A POC prioritizes speed over polish — the agent generates a working slice with minimal tests and some throwaway iteration. Input tokens dominate because an agent re-sends file context on every turn; output is the generated code, diffs and tests. Treat these as planning ranges, not a quote — your real usage depends on codebase size, model, prompt caching and how many iterations it takes.
Examples of this size
- A demo of one core idea
- A spike to de-risk a technical approach
- A clickable prototype wired to fake data
Estimate it with your own model
Plug in your model, complexity and prompt-caching to get a tailored range.
Frequently asked questions
How many tokens does a proof of concept / prototype take to build with AI?+
A proof of concept / prototype typically takes about 798,000 tokens to build with an AI coding agent (roughly 320,000–1,810,000 depending on complexity), about $2.36 at today's GPT-4o prices ($0.9500–$5.35). This is the build-time (developer) cost, not the cost of running the finished feature.
Is this the cost to build it or to run it?+
This is the build-time (developer) cost — the tokens an AI coding agent burns while implementing the work. Running the finished feature is a separate, usually much smaller per-request cost.
Why is the range so wide?+
A POC prioritizes speed over polish — the agent generates a working slice with minimal tests and some throwaway iteration. Input tokens dominate because an agent re-sends file context on every turn; output is the generated code, diffs and tests. Treat these as planning ranges, not a quote — your real usage depends on codebase size, model, prompt caching and how many iterations it takes.
How can I lower the cost?+
Split large work into smaller pieces, enable prompt caching so re-sent context is billed at the cheaper cache-read rate, and use a cheaper model for routine steps. Try your own model in the Cost to build X estimator.