Gender detection that shows its evidence
Send a first name, full name, email address or username. Get back a gender, a probability and the sample size behind it, including for the names many APIs leave unanswered.
Names that change by country
Female
Female
Female
Female
Female
Country-by-country figures for any name come from the /countries endpoint.
The labels come from public name lists we did not compile, and the test runs the same code as the API. We publish the writing systems we handle badly next to the ones we handle well.
In the NameGender 2026 benchmark of 4,610 labelled names from 25 countries, the API answered 92% of the names and 96% of those answers were correct, so 88% of all names were answered correctly.
Share of all test names in each writing system answered correctly. Unanswered names count as misses.
98% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
98% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
100% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
99% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
100% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
76% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
66% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
3% answered · Share of all test names in each writing system answered correctly. Unanswered names count as misses.
100% answered
100% answered
100% answered
99% answered
99% answered
99% answered
100% answered
94% answered
100% answered
100% answered
76% answered
66% answered
97% answered
95% answered
98% answered
100% answered
100% answered
94% answered
99% answered
98% answered
100% answered
3% answered
98% answered
100% answered
86% answered
One API, four input types, and bulk tools that handle files other services choke on.
One REST API for names, emails and usernames, the same JSON shape for all three, and a bulk endpoint for up to 100 values per request.
curl "https://namegender.com/api/v1/gender?name=Jean&country=FR" \
-H "Authorization: Bearer $NAMEGENDER_API_KEY"
{
"name": "Jean",
"gender": "male",
"probability": 100,
"sample_size": 1910805,
"country": "FR",
"confidence": "high",
"source": "db"
}Run a spreadsheet job: send an XLSX or CSV file, tell us which column holds the names, and your rows come back with gender, probability and sample size alongside. No code.
| first_name | country | gender | probability | based_on |
|---|---|---|---|---|
| Jean | FR | male | 100 | 1910805 |
| Robin | FR | male | 100 | 59650 |
| Andrea | ES | female | 97 | 113054 |
| Kim | US | female | 84 | 10916 |
Compound names and names with titles or initials are cleaned up before the lookup, so you can send the field as it is.
ayse.yilmaz84@example.com is read as Ayşe; role mailboxes such as info@ come back unknown.
camelCase, snake_case and trailing digits are split apart before the lookup.
Give us an XLSX or CSV file and get the same rows back with gender columns added. 200,000 rows take under a second of compute.
Andrea is male in Italy and female in Germany. Pass a country and we weigh it.
Every answer tells you where it came from and how large the sample was.
Buy 5,000 credits for €5.00, or 50,000,000 for €990.00. Whatever you do not use stays on your account: no monthly reset and no inactivity clause.
Every account also gets 100 free credits a day.
See all packages| Package | Credits | Price | Price per 1,000 names |
|---|---|---|---|
| 5K | 5,000 credits | €5.00 | €1.000 per 1,000 |
| 300K | 300,000 credits | €63.00 | €0.210 per 1,000 |
| 50M | 50,000,000 credits | €990.00 | €0.020 per 1,000 |
A gender API predicts the gender most often associated with a first name, using counted birth registrations and other name statistics. NameGender returns the gender together with the probability, the number of people the answer is based on, the country and the source, and it returns unknown when the evidence is too thin.
In the 2026 benchmark of 4,610 labelled names from 25 countries, NameGender answered 92% of the names and 96% of those answers were correct, so 88% of all names were answered correctly. Names missing from the dataset altogether are a different case: of 2,000 names removed from it for a separate test, 10% were answered, by closest spelling, and 93% of those answers were correct.
Yes. Turkish names use the Latin script, where 95% of test names were answered correctly. Arabic, Chinese and Korean names are matched directly or after transliteration: 87%, 86% and 92% of test names were answered correctly. Thai and Hebrew names are not supported yet.
Yes. Jean is recorded as male in France (100%) and as female in United States (95%). Pass a two-letter country code and the answer uses that country's data; without one you get the worldwide aggregate.
Yes. The email endpoint looks up the first name in the local part, so john.doe@example.com resolves as John, and the username endpoint strips digits and separators first. Role addresses such as admin@ or info@, placeholder handles such as user123, and an initial followed only by a surname, as in j.smith@, come back unknown rather than as a guess.
Purchased credits stay on your balance until you spend them. Packages start at €5.00 for 5,000 credits, the largest costs €0.020 per 1,000 names, and every account gets 100 free credits a day.
No. A name-based result is a statistical association, not a person's gender identity. Use it for aggregate work such as audience segmentation or survey weighting, keep unknown results visible, and do not use it for employment, medical, financial, insurance, legal or eligibility decisions.
Measured coverage and worked examples for each. Written in English only.
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