Best gender APIs in 2026: a testable shortlist

There is no best gender API for every dataset. The useful question is narrower: which service gives the best measurable result on your names, with an output and billing model your application can safely use?

This shortlist was checked against vendor documentation on September 8, 2026. Product details change, so follow the linked documentation before making a purchase.

The shortlist

Service	Useful when	Evidence returned	Inputs and workflow to test
NameGender	You need source visibility, non-Western scripts, bulk files, or credits that remain until used	Probability, `total_names`, confidence, source, country	First name, full name, email, username, bulk API, CSV/XLSX
Genderize.io	You want a compact API with a large counted corpus and may also use age or nationality services	Probability and count	First or full name, country hint, batches up to 100, spreadsheet and no-code workflows
Gender-API.com	You need first-name, full-name or email endpoints and detailed response metadata	Probability or accuracy, samples and normalized name, depending on API version	First name, full name, email, country, batch and CSV workflow
GenderAPI.io	You want both one-time credit and subscription choices with spreadsheet processing	Check the current response schema in its documentation	Name API plus Excel/CSV workflow

This table is deliberately not a ranking. A ranking without one shared input fixture rewards whichever vendor chose the examples.

What the official documentation confirms

Genderize's API reference documents a JSON result with gender, probability and count, an optional country_id, and batches of up to 100 names. Its documentation also says one API key can be used across Genderize, Agify and Nationalize. That combination is useful if gender is only one part of a demographic enrichment job.

Gender-API.com's current API documentation exposes dedicated handling for first names, full names and email addresses, as well as batch requests and country localisation. Check which API version you plan to use because response names and authentication differ between its simpler and current interfaces.

GenderAPI.io's pricing page currently shows both monthly subscriptions and one-time credit purchases. Its own FAQ says unused subscription allowance resets monthly while one-time credits do not expire. That distinction matters more than the headline price when your workload arrives quarterly rather than every day.

NameGender returns a probability, an evidence count and a source on each lookup. It also has separate full-name, email and username paths, a bulk endpoint, and managed CSV/XLSX processing. Purchased credits remain in the account until used. We are the vendor writing this page, so treat those statements as candidates for your test, not reasons to skip it.

Run one benchmark across every service

Take at least 200 labelled rows from the data you will actually process. Preserve the real mixture of countries, scripts, ambiguous names and messy inputs. Do not use a vendor's demonstration list and do not remove the rows that look difficult.

Send the same input and the same country hints to every provider. Record three separate measures:

Coverage: the share of submitted rows that received an answer
Accuracy when answered: the share of answers that matched the label
End-to-end accuracy: the share of all submitted rows that received a correct answer

The third number is coverage multiplied by accuracy when answered. It prevents an API from looking excellent simply because it declines every hard input. Report all three by country and writing system, not only as one global average.

Compare the output contract

A binary label is not enough for production. Check whether the response gives you a probability, a sample or evidence count, the country actually used, and a way to distinguish a direct database match from another method. Then submit deliberate nonsense and verify that the provider can say unknown.

Also test an ambiguous name such as Andrea with different country hints. If the result never changes, the country field may not be affecting the lookup in the way you expect. If it changes, inspect whether the evidence fields change with it.

Your database should allow a null result. Forcing every response into male or female turns absence of evidence into hidden data and makes later quality measurement impossible.

Price your real workload

Convert each plan into the cost of the workload you will actually run, not a generic cost per request. Include these questions:

Does the plan reset monthly, or do credits remain until used?
Is usage counted by API call, input name, file row, or unique lookup?
Does an unknown result consume quota?
Can you send batches, and what is the maximum batch size?
Is spreadsheet processing included or a separate product?
What happens above the limit: rejection, overage, or automatic upgrade?

A low monthly price can be expensive for a seasonal import. A higher one-time package can be cheaper when it removes twelve renewal cycles. The reverse can be true for a steady daily product.

Our recommendation

Choose two candidates whose workflow fits your system, then run the fixture before committing. If you need only a clean first-name call and already use adjacent demographic APIs, begin with Genderize. If you need richer full-name or email handling, include Gender-API.com. If your work is spreadsheet-heavy, test the file workflow rather than judging only the REST endpoint. Include NameGender when source visibility, managed bulk files, non-expiring purchased credits or our script coverage match your requirements.

The provider that wins on a generic English list may lose on your Turkish, Arabic, Indian or East Asian customers. Your fixture is the ranking that matters.