# GenderAPI.io vs Namsor

> Compare GenderAPI.io V2 and Namsor for name-based gender inference: request shapes, country context, batch limits, confidence signals and migration decisions.

Canonical HTML: https://www.genderapi.io/genderapi-io-vs-namsor

Last reviewed: 2026-09-26

## About this comparison

Published by GenderAPI.io, one of the providers discussed. This is a dated review of public documentation, not an independent performance test or an endorsement by another provider. We did not run competitor prediction requests. Undocumented in a reviewed reference does not mean unavailable. Recheck the linked contract and pricing before integrating.

## What changes between these APIs?

Namsor documents separate name and country-aware gender routes, including structured first/last names and full names. GenderAPI.io V2 uses type and value across name, email and username workflows. This page compares gender integration only, not Namsor’s broader name-analysis products.

| Decision point | GenderAPI.io V2 | Namsor | Sources |
| --- | --- | --- | --- |
| Name inputs | Names, email addresses and usernames use type and value on /api/v2/gender. | firstName with optional lastName, or an unsplit name on full-name routes. firstName explicitly accepts nicknames. | [GenderAPI.io V2 request parameters](https://www.genderapi.io/docs/v2/request-parameters); [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/) |
| Authentication | Authorization: Bearer with a GenderAPI.io key. Query keys are available for simple GET examples; prefer headers in applications. | X-API-KEY header with a Namsor credential. | [GenderAPI.io V2 authentication](https://www.genderapi.io/docs/v2/authentication); [Namsor API documentation introduction](https://namsor.app/api-documentation/introduction/) |
| Country and batch | Up to 50 keyed items or 10 IP-trial items. Each item can have its own type, country and options. Optional country on each item. | genderBatch / genderFullBatch and Geo variants with countryIso2; up to 100 names. | [GenderAPI.io V2 batch guide](https://www.genderapi.io/docs/v2/batch); [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/) |
| Confidence signals | data.confidence is 0–1 or null. confidence_kind distinguishes stored-count frequency from an AI score; sample_count is null for AI. | likelyGender, probabilityCalibrated (0–1), unnormalized score and genderScale (−1 male to +1 female). | [GenderAPI.io V2 responses](https://www.genderapi.io/docs/v2/responses); [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/) |
| Unknown handling | data.result_status: unknown; data.gender and data.confidence are JSON null. Inspect data.reason. | The reviewed gender enum lists female and male. A general JSON-null unknown contract is not established by these references. | [GenderAPI.io V2 responses](https://www.genderapi.io/docs/v2/responses); [Namsor API enumerators](https://namsor.app/api-enumerators/) |
| AI routing | Explicit off, fallback or always. Singles default to fallback; batches default to off. Optional forceToGenderize uses the dataset first, then nickname-aware AI. | The reviewed gender request tables do not document an equivalent off/fallback/always switch. | [GenderAPI.io V2 AI options](https://www.genderapi.io/docs/v2/ai-options); [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/) |
| Usage accounting | Ordinary successful lookups cost 1 credit, even unknowns and fallback AI. Always-AI costs 2. forceToGenderize costs 1 for a resolved dataset result or 2 when AI runs. | Pricing lists 1 credit per standard gender operation; costs vary for other features and plan overages. | [GenderAPI.io V2 credits and usage](https://www.genderapi.io/docs/v2/credits-and-usage); [Namsor prices and feature credit costs](https://namsor.app/prices/) |

## Before you switch an integration

For a GenderAPI.io integration, change X-API-KEY to Authorization: Bearer and use a GenderAPI.io credential. Map the name intentionally into type: name and value; map countryIso2 to country. Replace personalNames with items and split batches to the V2 limit. Keep per-item IDs and handle item-level errors.

Do not transform Namsor score or genderScale into GenderAPI.io confidence. Even probabilityCalibrated and a 0–1 GenderAPI.io score should not share an acceptance threshold without evaluation. Record unknowns separately from an application decision to abstain on a low score.

Sources: [Namsor API documentation introduction](https://namsor.app/api-documentation/introduction/); [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/); [GenderAPI.io V2 authentication](https://www.genderapi.io/docs/v2/authentication); [GenderAPI.io V2 request parameters](https://www.genderapi.io/docs/v2/request-parameters); [GenderAPI.io V2 responses](https://www.genderapi.io/docs/v2/responses); [GenderAPI.io V2 batch guide](https://www.genderapi.io/docs/v2/batch)

- [V2 request fields](https://www.genderapi.io/docs/v2/request-parameters)
- [V2 response fields](https://www.genderapi.io/docs/v2/responses)
- [Batch processing and item errors](https://www.genderapi.io/docs/v2/batch)

## Evaluate the workflow you will deploy

Choose a representative sample you are permitted to process and keep the original inputs, preprocessing and country context fixed. Evaluate name, email and username workflows separately. Record provider, endpoint, date, configuration and whether AI was used.

Measure coverage (answered / eligible), accuracy among answered results (correct / answered), and correct results across all eligible inputs (correct / eligible). Report unknowns, errors, costs and latency separately. A threshold should be selected on validation data and then checked on a held-out sample.

GenderAPI.io does not publish an independent reference-labelled accuracy benchmark here. Database counts, contract tests and one provider's published study cannot establish which service will work best on your data. An inferred association does not establish a person's gender identity.

Sources: [GenderAPI.io accuracy methodology](https://www.genderapi.io/accuracy-methodology)

- [Our methodology and current evidence limits](https://www.genderapi.io/accuracy-methodology)
- [Dated database profile](https://www.genderapi.io/data-provenance)

## Does Namsor support nicknames?

Yes. Its firstName documentation explicitly includes nicknames. That input support does not establish that its behavior is identical to GenderAPI.io forceToGenderize, which can infer an alias association without returning a real name.

Sources: [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/); [GenderAPI.io V2 AI options](https://www.genderapi.io/docs/v2/ai-options)

## Is a low score the same as a failed request?

No. Keep transport errors, an unknown API result and an application confidence threshold separate. Inspect each provider’s documented fields and evaluate your own abstention policy.

Sources: [GenderAPI.io V2 responses](https://www.genderapi.io/docs/v2/responses); [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/)

## Sources and review date

- [GenderAPI.io V2 request parameters](https://www.genderapi.io/docs/v2/request-parameters): Reviewed 2026-09-26
- [GenderAPI.io V2 authentication](https://www.genderapi.io/docs/v2/authentication): Reviewed 2026-09-26
- [GenderAPI.io V2 responses](https://www.genderapi.io/docs/v2/responses): Reviewed 2026-09-26
- [GenderAPI.io V2 AI options](https://www.genderapi.io/docs/v2/ai-options): Reviewed 2026-09-26
- [GenderAPI.io V2 batch guide](https://www.genderapi.io/docs/v2/batch): Reviewed 2026-09-26
- [GenderAPI.io V2 credits and usage](https://www.genderapi.io/docs/v2/credits-and-usage): Reviewed 2026-09-26
- [GenderAPI.io accuracy methodology](https://www.genderapi.io/accuracy-methodology): Reviewed 2026-09-26
- [GenderAPI.io pricing](https://www.genderapi.io/price): Reviewed 2026-09-26
- [Namsor API enumerators](https://namsor.app/api-enumerators/): Reviewed 2026-09-26
- [Namsor Gender API: Predict gender from first or full names](https://namsor.app/api-documentation/gender-api/): Reviewed 2026-09-26
- [Namsor API documentation introduction](https://namsor.app/api-documentation/introduction/): Reviewed 2026-09-26
- [Namsor prices and feature credit costs](https://namsor.app/prices/): Reviewed 2026-09-26