Developer cost model

Codex Cost Calculator

Codex costs depend on local task size, cloud task duration, code review depth and the model selected for the workflow.

No login. No AI API calls. Calculations run locally in your browser.

Last updated: 2026-05-24. Estimate only. This is not a billing statement.

Inputs

AI coding agent cost calculator

Model subscription fees, BYOK API usage, cache reads, cache writes and team workload in one local calculator.

Coding toolPricing modeModelWorkload preset

Tasks per dayAverage turns per taskInput tokens per turnOutput tokens per turnWorking days per monthTeam members

Cache read ratio35%Cache write ratio8%Subscription monthly fee$

Results

No login. No AI API calls. Calculations run locally in your browser.

OpenAI / GPT-5 / GPT-5 Codex. Last updated: 2026-05-24

Estimated monthly cost

$46.01

Estimated daily cost

$2.09

Cost per task

$0.42

Estimated yearly cost

$552.10

Token volume

Monthly input tokens

9.90M

Monthly output tokens

1.32M

Monthly cache read tokens

3.46M

Monthly cache write tokens

792.0K

Cost risk level

Medium

Main cost driver: subscription fee

Suggested ways to reduce cost

Keep task context bounded so input tokens do not grow silently.
Use explicit task boundaries before starting an agent run.
Prefer patch-oriented output over broad explanations.
Review high-cost sessions and reuse successful prompts.

TokenPatch

Want to measure cost per applied patch instead of raw token usage? Try TokenPatch.

TokenPatch TokenPatch GitHub

Workflow assumptions

Codex costs depend on local task size, cloud task duration, code review depth and the model selected for the workflow.

This page uses model price assumptions so teams can estimate monthly usage before adopting a coding agent process.

Local tasks can stay cheap when context is bounded and patches are small.

Cloud tasks and code review flows can add many turns before a final patch is accepted.

Model choice changes the economics more than most prompt tweaks.

TokenPatch

Want to measure cost per applied patch instead of raw token usage? Try TokenPatch.

TokenPatch TokenPatch GitHub

Pricing data

Model price assumptions

Pricing data is stored locally in the site configuration and should be treated as a planning estimate. Verify official provider pages before budgeting.

Provider	Model	Input / 1M	Output / 1M	Cache read / 1M	Cache write / 1M	Last updated	Source
Anthropic	Claude Sonnet 4.6 Estimate only. Claude Code plan limits, Max plan behavior and enterprise contracts can differ from API token pricing.	$3	$15	$0.3	$3.75	2026-05-24	Official
Anthropic	Claude Opus 4.6 Estimate only. Opus is usually the high-cost path for long-running agent sessions.	$5	$25	$0.5	$6.25	2026-05-24	Official
OpenAI	GPT-5 / GPT-5 Codex Estimate only. Codex plans, ChatGPT subscriptions and API billing are different billing surfaces.	$1.25	$10	$0.125	$0	2026-05-24	Official
OpenAI	GPT-5 mini / Codex mini Estimate only. Good for bounded coding tasks where cheaper iterations matter more than peak reasoning.	$0.25	$2	$0.025	$0	2026-05-24	Official
Google	Gemini Pro Uses Gemini Pro-class paid-tier pricing for prompts at or below 200k tokens. Long context pricing can be higher.	$2	$12	$0.2	$0	2026-05-24	Official
DeepSeek	DeepSeek Estimate only. Promotional rates and model naming can change; verify the pricing page before budgeting.	$0.14	$0.28	$0.0028	$0	2026-05-24	Official

FAQ

Is this an exact bill predictor?

No. It is an estimate for AI coding workflows. Provider billing, subscriptions, discounts and limits can vary.

Does the calculator call an AI API?

No. All calculations run locally in your browser and no login is required.

Why do coding agents use more tokens than chat?

They repeatedly consume repository context, command output, diffs, plans and review feedback across many turns.