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Software tasks

How many tokens does writing a unit test suite take with AI?

Quick answer

A unit test suite for a module typically takes about 415,000 tokens to build with an AI coding agent (roughly 165,000–930,000 depending on complexity), about $1.30 at today's GPT-4o prices ($0.5250–$2.93). This is the build-time (developer) cost, not the cost of running the finished feature.

Writing a unit test suite is one of the more output-heavy AI tasks: the agent reads the module, generates many test cases, and iterates until they pass. Both input (the code under test) and output (the tests) are substantial.

Token & cost ranges

Cost uses GPT-4o at current prices. Verified 29 July 2026.

ScenarioInput tokensOutput tokensTotal tokensEst. cost
Low (simple)150,00015,000165,000$0.5250
Typical380,00035,000415,000$1.30
High (complex)850,00080,000930,000$2.93

Typical cost by model

The same typical token estimate priced across a few common coding models.

ModelTypical costRange (low–high)
GPT-4o$1.30$0.5250$2.93
GPT-4o mini$0.0780$0.0315$0.1755
Claude Sonnet 4.6$1.67$0.6750$3.75
Gemini 2.0 Flash$0.0520$0.0210$0.1170

How we estimate this

Writing tests means reading the module under test, generating cases, and iterating until they pass — output is higher than most tasks. 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

  • Covering a service class with unit tests
  • Adding edge-case tests to a utility
  • Backfilling tests before a refactor

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 unit test suite for a module take to build with AI?+

A unit test suite for a module typically takes about 415,000 tokens to build with an AI coding agent (roughly 165,000–930,000 depending on complexity), about $1.30 at today's GPT-4o prices ($0.5250–$2.93). 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?+

Writing tests means reading the module under test, generating cases, and iterating until they pass — output is higher than most tasks. 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.