Back to Home
    Published: Dec 31, 2025Last updated: Feb 11, 2026

    Cross-Platform App Development
    One Codebase, Multiple Platforms

    Cross-platform development lets you build iOS and Android apps from a single codebase. This technical guide examines the frameworks, trade-offs, and best practices for multi-platform mobile development.

    React NativeFlutterTechnical ComparisonDecision Framework

    Understanding Cross-Platform Development

    Cross-platform mobile development refers to creating applications that run on multiple operating systems (primarily iOS and Android) from a shared codebase. This contrasts with native development, where separate codebases are maintained for each platform.

    The primary frameworks in this space are React Native (JavaScript, maintained by Meta) and Flutter (Dart, maintained by Google). Both compile to native code rather than running in a webview, achieving performance closer to native applications than older hybrid approaches.

    The business case for cross-platform is compelling: maintain one codebase instead of two, ship features simultaneously on both platforms, and reduce the expertise required on your team. However, cross-platform involves trade-offs that make it inappropriate for certain projects.

    Fastshot generates React Native code, chosen for its mature ecosystem, large community, JavaScript familiarity, and excellent balance between performance and development experience.

    Framework Comparison

    Technical comparison of leading cross-platform frameworks.

    FeatureReact NativeFlutterKotlin Multiplatform
    LanguageJavaScript/TypeScriptDartKotlin
    RenderingNative componentsCustom renderingNative components
    Hot ReloadYesYesLimited
    Bundle SizeMediumLargerSmallest
    Platform LookNative feelCustom (Material/Cupertino)Native feel
    Learning CurveLow (if JS experience)MediumHigher
    EcosystemLargestGrowingDeveloping
    Major UsersInstagram, Walmart, DiscordGoogle Pay, BMWNetflix, VMware

    When to Choose Cross-Platform

    Simultaneous Platform Launch

    If you need to launch on iOS and Android at the same time, cross-platform dramatically simplifies coordination and ensures feature parity.

    Limited Development Resources

    Small teams benefit from maintaining one codebase rather than two. Cross-platform lets a smaller team cover both platforms effectively.

    Rapid Iteration Requirements

    When you need to test hypotheses quickly, fixing bugs once and deploying everywhere accelerates your feedback loop.

    Standard UI Patterns

    Apps using common UI patterns (lists, forms, navigation, cards) work excellently in cross-platform frameworks. The standard components are highly optimized.

    Budget Constraints

    Maintaining two native codebases costs roughly twice as much as one cross-platform codebase over time. The savings compound as your app grows.

    When Native Makes More Sense

    Cross-platform is not always the right choice. Consider native development when: your app requires heavy use of platform-specific APIs (AR, advanced camera features, HealthKit/Health Connect), performance is absolutely critical (high-performance games, real-time video processing), you have dedicated iOS and Android teams who prefer platform expertise, or your app design intentionally differs significantly between platforms. The decision should be based on your specific requirements, not general preferences. Many successful apps use a hybrid approach—cross-platform for most screens with native modules for platform-specific features.

    Cross-Platform FAQ

    Build Cross-Platform with AI

    Fastshot generates React Native code that runs on both iOS and Android. Describe once, deploy everywhere.

    About the Author

    Elvira Dzhuraeva is an expert in AI mobile app development and React Native. A former Senior Product Manager at Google specializing in AI/ML and Generative AI, she is the Founder of Fastshot (YC-backed) and a founding contributor to Kubeflow.

    AI Mobile App DevelopmentReact NativeAI Developer ToolsVibecodingAI/ML Ops