Cost Estimates

Before you commit to a large labeling run, you can ask Rapidata what a job is expected to cost. Every job definition and every running job exposes an estimated_cost property that returns a CostEstimate.

Getting an Estimate

You can read the estimate straight from a job definition, before assigning it to an audience — useful for checking the cost of a run before you launch it:

from rapidata import RapidataClient

client = RapidataClient()

job_definition = client.job.create_compare_job_definition(
    name="Example Image Prompt Alignment",
    instruction="Which image matches the description better?",
    datapoints=[
        ["https://assets.rapidata.ai/midjourney-5.2_37_3.jpg",
         "https://assets.rapidata.ai/flux-1-pro_37_0.jpg"]
    ],
    contexts=["A small blue book sitting on a large red book."],
)

estimate = job_definition.estimated_cost # (1)!
print(f"About {estimate.estimated_cost} for {estimate.required_responses} responses")

1. The estimate is priced shortly after the definition is created. Reading it right away blocks for a moment until it is ready, then returns.

The same property is available on a job once it is running:

job = audience.assign_job(job_definition)
print(job.estimated_cost.estimated_cost)

What the Estimate Contains

A CostEstimate has three fields:

Field	Description
estimated_cost	The estimated total cost of running the job to completion, in your account's billing currency.
datapoint_count	The number of datapoints the job will label.
required_responses	The total number of responses the job collects to complete.

Note

This is an estimate, not the final bill. It is based on a sample of the job's tasks scaled to the number of responses requested, so the amount you are actually charged can differ. Features like Early Stopping can also lower the final cost by collecting fewer responses than the maximum.

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