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AI Translation Cost per Task Calculator

The AI Translation Cost per Task Calculator estimates the direct and allocated cost of translating one text job with an AI workflow. It combines source and generated token charges, compute or platform expense, quality-review labor, and a share of monthly fixed costs. The result is useful when comparing models, setting internal chargeback rates, or checking whether a quoted price leaves enough margin.

A task can represent one document, message batch, product description set, or any other repeatable translation unit. Because providers price tokens and infrastructure differently, the calculator keeps each cost component visible instead of treating translation as a single opaque rate. It is an operational estimate rather than a vendor invoice; actual billing can vary with tokenization, retries, caching, minimum charges, and human-review requirements.

Translation cost inputs

tokens
tokens
USD
USD
USD
min
USD/hr
USD
tasks
Result
—
estimated cost per translation task
Token cost—
Human review cost—
Allocated fixed cost—
Monthly total at entered volume—

1. Step 1
Define one task as a consistent translation unit, such as one document or one batch.

2. Step 2
Enter the expected source and translated token counts for that unit.

3. Step 3
Add the provider prices per one million input and output tokens.

4. Step 4
Include platform expense and the minutes of human review required after generation.

5. Step 5
Enter monthly fixed costs and expected task volume so overhead can be allocated per task.

6. Step 6
Review the total and its component breakdown; use the same assumptions when comparing alternatives.

Cost per task = input token cost + output token cost + other compute cost + review labor cost + allocated fixed cost. Input token cost = input tokens × input rate ÷ 1,000,000. Review labor cost = review minutes ÷ 60 × hourly labor cost. Allocated fixed cost = monthly fixed costs ÷ monthly tasks.

What the result means

The main result is the estimated fully loaded operating cost for one translation task under the entered volume and review assumptions.

Taxes, retry traffic, discounts, caching, and minimum vendor charges are not included unless you add them to other compute or fixed costs.

Given: 1,800 input tokens, 2,000 output tokens, rates of $0.50 and $1.50 per million tokens, $0.02 platform cost, 3 review minutes at $30/hour, and $100 fixed cost across 5,000 tasks.

Calculation: Token cost = 1,800 × 0.50 ÷ 1,000,000 + 2,000 × 1.50 ÷ 1,000,000 = $0.0039. Review cost = 3 ÷ 60 × 30 = $1.50. Fixed allocation = 100 ÷ 5,000 = $0.02. Total = 0.0039 + 0.02 + 1.50 + 0.02 = $1.5439.

Result: The estimated cost is $1.54 per task. Human review is the dominant cost in this example.

Should input and output tokens include system prompts?

Yes. Include every billable token attributable to the task, including repeated instructions or context that the provider bills.

How should retries be handled?

Use average token counts that already include normal retries, or add a retry allowance to the token and platform inputs.

Why does monthly volume change the result?

Fixed costs are spread across the entered number of tasks. Lower volume assigns more overhead to each task.

Can I use this for human-only translation?

The structure can approximate it by setting token and compute costs to zero and entering the full human time in review minutes.

Is cost per task the same as customer price?

No. A selling price may also include profit margin, support, taxes, risk, and commercial overhead not entered here.