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Add the GenieX SDK to an Android Studio project so your app can pull weights from Hugging Face / Qualcomm AI Hub and run them on the Hexagon NPU, Adreno GPU, or CPU compute units — all in Kotlin.

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Try the sample app first

See GenieX running on Android before you write any code. The reference chat app — with model picker, resumable downloads, and VLM support — lives in qualcomm/ai-hub-apps. Clone it, open it in Android Studio, and hit Run ▶.

Get the GenieX Chat sample app

Build the reference chat app from source — follow the README to clone, build, and run it.
Pick a model from the dropdown and choose NPU, GPU, or CPU on load. Tap the image button for VLMs. Stay on Wi-Fi for the first download. No phone? See Testing without a physical device.

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Prerequisites

  • Android Studio Hedgehog (2023.1.1) or newer.
  • minSdk = 27 (Android 8.1) in your app module.
  • A phone running Snapdragon 8 Elite (SM8750) or Snapdragon 8 Elite Gen 5 (SM8850) — see Supported platforms.

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Add the SDK to your app

1

Enable Maven Central

In settings.gradle.kts (or your top-level build.gradle.kts for older projects):
dependencyResolutionManagement {
    repositories {
        google()
        mavenCentral()
    }
}
2

Add the dependency

In your app module’s build.gradle.kts:
dependencies {
    implementation("com.qualcomm.qti:geniex-android:0.3.1")
}
The artifact ships native arm64-v8a libraries — no NDK or CMake on your side.
3

Declare permissions

The SDK pulls weights at runtime. In AndroidManifest.xml:
<uses-permission android:name="android.permission.INTERNET" />
For VLMs that load images from the gallery, also declare READ_EXTERNAL_STORAGE (or scoped media permissions on Android 13+).
4

Sync Gradle

Click Sync Now in Android Studio.
Next, head to the Quickstart to download and run your first model.