How many tokens does an MVP feature take to build with AI?
A mvp feature typically takes about 3,680,000 tokens to build with an AI coding agent (roughly 1,580,000–8,400,000 depending on complexity), about $10.55 at today's GPT-4o prices ($4.55–$24.00). This is the build-time (developer) cost, not the cost of running the finished feature.
An MVP feature is a complete vertical slice you could ship: UI, API, data and tests, built over several sessions. It's the level at which model choice and prompt caching start to matter for the total bill.
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) | 1,500,000 | 80,000 | 1,580,000 | $4.55 |
| Typical | 3,500,000 | 180,000 | 3,680,000 | $10.55 |
| High (complex) | 8,000,000 | 400,000 | 8,400,000 | $24.00 |
Typical cost by model
The same typical token estimate priced across a few common coding models.
| Model | Typical cost | Range (low–high) |
|---|---|---|
| GPT-4o | $10.55 | $4.55 – $24.00 |
| GPT-4o mini | $0.6330 | $0.2730 – $1.44 |
| Claude Sonnet 4.6 | $13.20 | $5.70 – $30.00 |
| Gemini 2.0 Flash | $0.4220 | $0.1820 – $0.9600 |
How we estimate this
An MVP feature is a vertical slice — UI, API, data and tests — built over several sessions with real iteration and integration. 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 shareable-links feature end to end
- A commenting system with moderation
- A basic dashboard with live 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 mvp feature take to build with AI?+
A mvp feature typically takes about 3,680,000 tokens to build with an AI coding agent (roughly 1,580,000–8,400,000 depending on complexity), about $10.55 at today's GPT-4o prices ($4.55–$24.00). 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?+
An MVP feature is a vertical slice — UI, API, data and tests — built over several sessions with real iteration and integration. 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.