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Fake Mobile Device Info Generator

Used by developers, writers, and creators worldwide.

A fake mobile device info generator solves a real problem for developers who need diverse, realistic device metadata without capturing data from actual users. Each generated profile includes brand, model, operating system version, screen resolution, RAM, storage, and a synthetic device identifier — the same fields you'd find in a crash report or analytics payload. Paste the output straight into your test fixtures, seed scripts, or Postman collections. QA teams use it to populate device inventory tables and simulate varied user cohorts. Backend engineers use it to stress-test how their code handles Android fragmentation or iOS version spread. Choose Android, iOS, or a mixed batch using the platform selector, and set the count to generate up to a full staging dataset in one click.

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How to use

  1. Choose your options above
  2. Click Generate
  3. Copy your result

Detailed instructions

  1. Select your target platform from the dropdown: choose Android, iOS, or Mixed depending on which device profiles you need.
  2. Set the count field to the number of device profiles you want, up to your preferred batch size for seeding or testing.
  3. Click Generate to produce a batch of complete device metadata objects with models, OS versions, resolutions, and identifiers.
  4. Review the output list and copy individual records or the full batch into your test fixtures, database seed scripts, or analytics mock data.

Use Cases

  • •Seeding a Postgres staging database with 50+ diverse Android and iOS device profiles
  • •Testing crash report ingestion pipelines in Datadog or Sentry with realistic device metadata
  • •Validating device-specific feature flags across varied OS versions and RAM tiers in Firebase Remote Config
  • •Generating Cypress fixture files that cover real-world screen resolutions for responsive breakpoint tests
  • •Populating demo dashboards in Mixpanel or Amplitude with believable device distribution data

Tips

  • →Generate a Mixed batch of 20+ devices and filter by RAM tier to test how your app behaves on low-memory handsets versus flagships.
  • →When testing analytics dashboards, generate separate Android and iOS batches to simulate realistic platform split ratios like 70/30.
  • →Pair screen resolutions from the output with Chrome DevTools custom device presets to get accurate viewport rendering tests.
  • →For crash report testing, regenerate until you have profiles spanning at least three major OS versions per platform to catch version-specific bugs.
  • →Use the device identifiers as foreign keys in test databases to link fake sessions, events, and crash logs to consistent device records.
  • →If your feature flag system targets RAM thresholds, generate a large batch and filter profiles at the exact cutoff to find boundary condition bugs.

FAQ

what fields are included in a generated mobile device profile

Each profile includes brand, model name, OS and version, screen resolution, pixel density, RAM, internal storage, battery capacity, and a randomly generated device identifier. These match the fields you'd typically see in mobile analytics SDKs like Amplitude or Mixpanel and in crash reporters like Firebase Crashlytics.

can I use fake device IDs to test push notification routing

You can use them to test how your system stores, deduplicates, and routes token data, but not to send real pushes. APNs and FCM validate tokens against actual device registrations, so generated identifiers will be rejected at the delivery stage. Pair this tool with a real device or simulator for end-to-end push tests.

is it safe to commit generated device data to a public GitHub repo

Yes. All profiles are entirely synthetic — no real IMEIs, no real serial numbers, and no user linked to any identifier. There is no PII, so you can freely commit the output to public repositories, include it in documentation, or use it in destructive GDPR deletion tests without touching real user records.