Product team
You expect uneven demand. Write down likely peak traffic and the response time your application needs before choosing a deployment.
A traffic range gives you a basis for comparing capacity with usage.
How to evaluate baseten pricing for your workload
Baseten serves teams deploying AI models for inference. A useful cost estimate starts with the model, deployment configuration, and expected traffic—not a single headline price.
prerequisites
Before comparing costs, identify what you need to deploy and how people will use it. These starting points lead to different questions.
ML engineer
You have a model ready to serve. Record its size, hardware requirements, and expected requests before testing an inference workflow.
A defined workload makes deployment estimates easier to challenge.
Budget owner
You need to distinguish an introductory offer from an ongoing operating budget. Check current eligibility and terms directly.
A plan that does not depend on a temporary allowance is easier to maintain.
Security reviewer
You are assessing a production deployment. Include security and data-handling requirements when comparing deployment choices.
An approved architecture avoids a misleading estimate for an option your team cannot use.
one full run-through
Work through one representative deployment rather than applying a generic rate to every model.
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1
Define the workload
Suppose your team serves a text model behind an application. Note the model, average input and output size, expected requests, peak periods, and acceptable latency. Keep estimates separate from measured traffic.
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2
Choose a deployment candidate
Identify the hardware and capacity the model may require, then check the current Baseten documentation or sales information for the relevant configuration and billing terms. Do not substitute another provider’s rates.
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3
Estimate and test
Calculate a low, expected, and peak-use scenario using the applicable current rates. Test a representative workload, compare observed capacity with your assumptions, and revise the estimate before treating it as a budget.
options table
A cost comparison is only useful when the options are measured on the same workload. These common shortcuts leave important columns blank.
1
Single-price comparison
This guide cannot provide one reliable rate for every Baseten deployment. Model requirements, capacity, usage, and current commercial terms may differ.
What to do instead
Compare candidate configurations against the same traffic and latency assumptions, using current provider information.
2
Unverified monthly total
A request count alone cannot establish a monthly bill if the deployment needs available capacity between requests or has other applicable charges.
What to do instead
Record both usage and operating time, then confirm how the selected option is billed.
3
Introductory allowance as a baseline
A temporary offer, if available, does not establish the recurring cost of production use.
What to do instead
Build the ongoing estimate without an allowance and treat any eligible offer separately.
what fails
Switch perspectives to catch assumptions that can make an otherwise tidy estimate unreliable.
Engineering
A model name is not a deployment specification
Two deployments of the same model may have different capacity needs. A benchmark using short requests and steady traffic may not represent long outputs or sudden peaks.
- Test representative inputs and outputs.
- Measure latency and throughput under realistic load.
- Revisit the configuration if the model changes.
Finance
A forecast is not an invoice
An estimate can miss idle capacity, changes in traffic, or terms that apply to a particular arrangement. Separate confirmed billing details from assumptions in the budget.
- Keep low, expected, and peak scenarios.
- Date the rates used in the calculation.
- Review actual usage against the forecast.
Operations
Average demand can hide peak demand
A monthly average may look affordable while a short peak requires more capacity to meet the application’s latency target. Consider the service requirement alongside the projected spend.
- Identify busy periods.
- Set an acceptable response-time target.
- Test how the deployment behaves at peak load.
Make the estimate testable
Input assumptions
Step 1
Start with a workload record
Keep the model version, request shape, traffic forecast, and latency goal together. That record makes it possible to explain why a Baseten configuration was selected and what would trigger a new estimate.
Validation
Step 2
Compare the forecast with observation
After a representative test, replace guesses with measured throughput and operating patterns where possible. If the workload or deployment changes, update the calculation rather than carrying forward an old figure.
Take the next step
The destination offers a separate AI platform, not an official Baseten quote. Bring your model requirements and expected usage, and verify any current terms at the destination before making a commitment.
Explore an AI workload with real assumptions
- Define the workload first
- Check current terms directly
- Test before forecasting at scale
its own FAQ
The applicable pricing depends on the service and deployment arrangement you choose. Check Baseten’s current published information or contact its team for rates and billing terms relevant to your workload; this guide does not quote a current rate.
Do not assume one billing unit applies to every option. Confirm the unit, any minimums, and how operating time or usage is measured for the specific arrangement you are evaluating.
Start with the model and configuration, expected traffic, request size, peak demand, and latency target. Combine those assumptions with current applicable rates, then test whether the chosen capacity handles representative requests.
Traffic and operating time can differ from a forecast, and a different configuration may be needed to meet performance targets. Record the assumptions behind your estimate and compare them with measured usage and the actual billing terms.