Android Developers Blog

Expanded billing choice and lower fees on Google Play

2026-06-24T07:00:00.000-07:00

Posted by Paul Feng, Vice President, Google Play Eng, Product, UX

At Google Play, we are committed to delivering the best possible experience to users, while ensuring developers have the tools and adaptability to succeed. Guided by this commitment, earlier this year we announced updates to our business model introducing more billing flexibility, lower fees, and new programs to help your business thrive.

With some of these changes rolling out soon, the breakdown below outlines what is coming, where to find more information, key dates, and how to get started.

More billing flexibility

Google Play’s billing system safely, efficiently, and intuitively handles the complexities of taxes, compliance, and subscriptions across 195+ markets with 300+ local payment methods. However, we understand there are situations where your business needs more flexibility, and that's why we're offering you more options in how you handle digital commerce.

Building from existing programs, the new billing choice program is available to all developers globally who provide digital services or content to users within the United Kingdom and the European Economic Area, alongside programs in the United States. Following this initial phase, we will continue expanding availability to additional markets. You will find the global release schedule at the bottom of this post.

Through these programs, developers can offer an alternative billing system or link users to their own website for purchases, alongside Google Play’s billing. You may also design your own choice screen in accordance with our UX guidelines, as an alternative to Google Play’s default version.

Please find all the details in the program page here.

Lower, separate fees

To enable this new level of flexibility, we're separating our service fee from the billing fee. This starts on June 30, 2026, beginning with the United States, European Economic Area, and United Kingdom.

Regardless of whether you use Google Play's billing system, alternative billing, or external web links, the service fee starts at 10% on your first $1M (USD) in annual earnings. This 10% service fee also applies to all auto-renewing subscriptions. For all other transactions, the rates in the table below applies:

For other transactions, the service fee will be determined by whether the transacting user's install is new or existing relative to the regional rollout date:

New installs: A transaction from a user whose first-time install or first update of the app from Google Play occurred on or after the date that the new fee structure launched in their region.
Existing installs: A transaction from a user whose first-time install or first update of the app from Google Play occurred before the date that the new fee structure launches in their market.

For transactions that use Google Play’s billing system, an additional billing fee applies. In the United States, United Kingdom, and the European Economic Area, the billing fee is set at 5%. We'll announce billing fee details for other markets soon. For transactions processed via alternative billing or external web links, the billing fee does not apply.

Review this Help Center article to understand how these rates apply to your business.

Games Level Up and Apps Experience program guidelines

We are also excited to announce even more opportunities for partners who deliver exceptional user experiences across the Android ecosystem: the revamped Games Level Up and the new Apps Experience program. Detailed guidelines are now available on the respective program websites.

Apps and games that meet all requirements are eligible for a new program rate card with reduced rates. See the table below for details:

Visit the Games Level Up and Apps Experience program websites, review the guidelines, and start preparing your games and apps ahead of September 30, 2026, when the program rate cards officially become available.

Global release schedule

Evolving our business model requires technical infrastructure and alignment with local regulations, so these updates will roll out on a staggered timeline. To help you plan, here is the previously announced release schedule for each update across all markets:

Here is a quick recap of the resources available to help you get started:

Review the billing choice program;
Learn more about Google Play's lower service fees;
Explore detailed guidelines on the Games Level Up and Apps Experience program websites.

We look forward to building the next generation of Google Play experiences together.

Android developer verification: Building a safer ecosystem together

2026-06-18T07:00:00.000-07:00

Posted by Matthew Forsythe, Director Product Management, Android App Safety

Last year, we introduced Android developer verification to strengthen ecosystem security and stop malicious actors from hiding behind anonymity to release harmful apps. Millions of apps have been registered since the verification launched in March, covering nearly all installs on Google Play and a large majority of installs from outside of Google Play. We appreciate the feedback and partnership from industry leaders, developers, and Android communities that helped us design this experience and drive strong adoption.

Initial launch across seven stores and four countries

These new developer verification protections will take effect on September 30, 2026, starting with users in Brazil, Indonesia, Singapore, and Thailand.

This rollout is an industry-wide effort to create a safer ecosystem. We will begin by verifying app installations from the following stores:

Google (Google Play)
Honor (HONOR App Market)
OPlus (OPPO App Market)
Samsung (Galaxy Store)
Transsion (Palm Store)
vivo (V-Appstore)
Xiaomi (GetApps)

Following this initial phase with our partners, we will expand these protections globally for all apps on certified Android devices in 2027.

Automate your workflow with new APIs

To further streamline app registration, we are launching a suite of developer-requested APIs to help you register apps in bulk or directly through your continuous integration and deployment (CI/CD) pipelines. The Android Developer ID Status API will let you check if a package name has already been registered, and the Android Developer Console API will let you register and manage package names directly within your development environment. Both APIs also support OAuth delegation, allowing third-party platforms, like Android app stores, to perform these operations natively on your behalf.

We'll launch these APIs over the next few months.

What’s next

June 2026: Starting this month, we are rolling out a new system service that will be automatically installed on most Android devices. This service will be used later this year to verify developer registration.
July 2026: We’ll launch the Android Developer ID Status API globally and begin early access for the Android Developer Console API. Early access also starts for limited distribution accounts on Android Developer Console. This new type of Android developer account is designed for students, hobbyists, and learners and lets you share your apps to up to 20 devices without a government-issued ID or a fee.
August 2026: Limited distribution accounts and the new Android Developer Console API will launch globally. We’ll also launch an advanced flow for installing apps from unverified developers, which includes security checkpoints to resist coercion scams, while allowing power users to maintain the ability to sideload apps from unverified developers.
September 30, 2026: App registration becomes required for participating stores in Brazil, Indonesia, Singapore, and Thailand. Unregistered apps can be sideloaded with Android Debug Bridge (adb) or advanced flow.
2027 and beyond: After incorporating the feedback from our partners, users, and developer community, we’ll expand the Android verification requirement globally.

Get started with Android developer verification

If you distribute apps in Brazil, Indonesia, Singapore, or Thailand via the stores listed above, please ensure your verification is complete by the September deadline.

Google Play developers: Most Play developers are already verified, and over 99% of their apps have been registered. Go to your Play Console Home page to see your app’s verification status, and register apps you want to continue distributing that weren't automatically registered.
Developers who distribute only outside of Google Play: Sign up for the Android Developer Console today to register your apps.

Students and hobbyists: Sign up here for early access to limited distribution accounts to help us refine the feature with your feedback.

Thank you for helping us build a safer Android ecosystem. Stay tuned for more updates as we approach September and the 2027 global rollout.

Building a Mixed-Reality Tour Guide with Android XR, the Geospatial API, and Gemini

2026-06-17T10:00:00.000-07:00

Posted by Coco Fatus, UX Designer, Alon Hetzroni, UX Engineer, Azin Mehrnoosh, Product Manager Android XR

At this year's Google I/O, we announced an update for spatial experiences: the Geospatial API is now available as a preview in ARCore for Jetpack XR. By bringing Google's Visual Positioning System (VPS) to Android XR, Android XR enables anchoring digital content to the physical world with sub-meter accuracy and precise orientation in supported areas.* To explore what the Geospatial API could unlock, our team built a demo: the XR Geospatial Tour.

Imagine walking into a new city, putting on a pair of wired XR glasses (like the upcoming XREAL Project Aura), and instantly having a knowledgeable, local guide showing you around. You don't need to stare down at a 2D map—instead, 3D models gently guide your path, and an intelligent voice tells you about the historical landmarks right in front of you. We combined the Geospatial APIs, Gemini API using Firebase AI Logic, Google Maps Grounding, and Jetpack XR SDK to create a hands-free, immersive walking tour experience.

*Disclaimer: Video and Tour Guide application are for demonstration purposes only. Some sequences have been shortened. Any hardware depicted may be under development; final product details may differ.

Let’s walk through the implementation details and show how we tied these APIs together to build a world-scale spatial experience.

1. Pinpointing the User with ARCore Geospatial API (VPS)

Enhance your navigation experience on XR by combining the power of GPS with the precision of VPS. The accuracy and precise orientation that comes with VPS allows 3D waypoints to align with the physical world.

This is why the Geospatial API on Android XR can help you build custom experiences. By using advanced computer vision, VPS tries to provide a GeospatialPose (including latitude, longitude, and heading) that is more accurate than GPS.

Here's how we retrieve the user's Geospatial pose by mapping the device's orientation to a Geospatial coordinate:

// Retrieve the current geospatial pose from the ARCore session
val result = geospatial.createGeospatialPoseFromPose(arDevice.state.value.devicePose)
if (result is CreateGeospatialPoseFromPoseSuccess) {
    val pose = result.pose
    Log.d("VPS", "Accurate Location: ${pose.latitude}, ${pose.longitude}")
}

Because the entire experience relies on this accuracy, we monitor the horizontalAccuracy and orientationYawAccuracy until they meet our thresholds. If the user is indoors or in an unrecognized area, we prompt them to "walk to an outdoor public space and look around".

2. Crafting the Itinerary with Gemini API & Google Maps Grounding

Once we have a location, we use the Gemini API using Firebase AI Logic to prompt the Gemini model to act as a local tour guide. We pass the user's coordinates to the model and ask it to output a structured JSON response containing nearby walking tours:

   val configForTools = ToolConfig(
      functionCallingConfig = null,
      retrievalConfig = retrievalConfig {
        latLng = FirebaseLatLng(pose.latitude, pose.longitude)
        languageCode = "en"
      }
    )
    val responseJsonSchema = Schema.obj(
      mapOf(
        "locationIntro" to Schema.string(),
        "tours" to Schema.array(
          Schema.obj(
            mapOf(
              "title" to Schema.string(),
              "description" to Schema.string(),
              "stops" to Schema.array(
                Schema.obj(
                  mapOf(
                    "name" to Schema.string(),
                    "detailedName" to Schema.string(),
                    "description" to Schema.string()
                  )
                )
              )
            )
          )
        )
      )
    )
    val model = Firebase.ai(backend = GenerativeBackend.googleAI()).generativeModel(
      modelName = "gemini-3.5-flash",
      tools = listOf(Tool.googleMaps()),
      generationConfig = generationConfig {
        responseMimeType = "application/json"
        responseSchema = responseJsonSchema
      }
    )
   val result = model.generateContent("The user is at latitude ${pose.latitude} and longitude ${pose.longitude}. Generate exactly 3 diverse tours near this location (e.g., historical, food, nature). All tour ideas should be walking distance only.")

Large Language Models are great at generating rich descriptions, but they can sometimes hallucinate exact latitude/longitude coordinates. To solve this, we used Google Maps Grounding to ground the AI.

3. A Voice to Guide You: Gemini 2.5 TTS

To make the tour guide feel truly present, we implemented dynamic voiceovers.

Using the gemini-2.5-flash-tts model, we can configure our model generation config to natively return audio data instead of just text! Here’s how you can request the ResponseModality.AUDIO:

val ttsModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-2.5-flash-tts",
        generationConfig = generationConfig {
            // Instruct the model to return Audio
            responseModalities = listOf(ResponseModality.AUDIO)
        }
    )
val response = ttsModel.generateContent("Say in a neutral but positive voice:\n$prompt")
// Extract the raw audio bytes from the response
val audioBytes = response.candidates.firstOrNull()?.content?.parts
    ?.filterIsInstance<InlineDataPart>()
    ?.firstOrNull { it.mimeType.contains("audio") }?.inlineData

4. Bringing it to Life in 3D with Jetpack XR

The final piece of the puzzle is rendering this data in the user's field of view. The Jetpack XR SDK makes it intuitive to transition from a 2D Android UI to spatial computing.

We used Jetpack Compose for XR to build spatial components. To represent points of interest along the tour, we built a Composable called InfoSphere, which contains a GltfModel of a 3D orb that floats in space and can be interacted with to reveal information.

Using Jetpack XR SDK, we can place 3D models alongside the Compose UI using SpatialBox and SceneCoreEntity. We also used InteractableComponent to respond to user taps.

@Composable
fun InfoSphere(
    content: InfoBubbleContent,
    session: Session,
    sphereModel: GltfModel,
    isSelected: Boolean,
    onClick: () -> Unit
) {
    // SpatialBox lets us arrange 3D components and SpatialPanels together
    SpatialBox(
        SubspaceModifier
            .offset(x = 2.dp, y = 1.dp, z = (-3).dp) // Positioned in 3D space
    ) {
        // Smoothly animate the visibility of our 2D Compose UI Panel
        AnimatedSpatialVisibility(visible = isSelected) {
            SpatialPanel {
                InfoBubble(content) // Regular 2D Compose UI
            }
        }
        // Render our interactive 3D sphere
        SceneCoreEntity(
            factory = {
                GltfModelEntity.create(session, sphereModel).also { entity ->
                    // Make the 3D model respond to user taps
                    entity.addComponent(InteractableComponent.create(session) { inputEvent ->
                        if (inputEvent.action == InputEvent.Action.UP) {
                            onClick()
                        }
                    })
                }
            }
        )
    }
}

By combining AnimatedSpatialVisibility for traditional Compose UI surfaces with SceneCoreEntity 3D elements, we're able to seamlessly blend data into the physical world.

Explore what’s possible with Android XR today

Building the XR Geospatial Tour app showed us that the barrier to entry for world-scale spatial experiences is lower than ever for Android developers. With the Geospatial API now available in preview on Android XR, your apps can seamlessly understand the physical world around them. By combining Compose for XR’s APIs with the high-precision location data of VPS and the generative capabilities of Gemini, we can create experiences that understand both where the user is and what they are looking at.

To help you get hands-on with Android XR, we are thrilled to open applications for the Android XR Developer Catalyst Program, which includes XREAL Project Aura. Starting today, you can apply to get access to an XREAL Project Aura devkit or our display glasses devkit over the coming months!

Android 17 is here

2026-06-16T06:00:00.000-07:00

Posted by Matthew McCullough, VP of Product Management, Android Developer

Today we're releasing Android 17 and making it available on most supported Pixel devices. Look for new devices running Android 17 in the coming months.

Android 17 marks the start of our transition to an intelligence system, putting your apps at the center. It's shifting to an adaptive-first development standard by introducing mandatory large-screen resizability, all while delivering next-generation privacy, security, media, camera, and performance. We'll cover all that in this post, as well as how we're bringing together next generation tools, libraries, and agent skills to help your apps embrace the opportunity.

Throughout the past year, from our Canary channel to our Beta releases, we’ve collaborated with you in the developer community to build a platform you and your users can trust. To that end, this moment marks the availability of the source code at the Android Open Source Project (AOSP). This allows you to examine the source code for a deeper understanding of how Android works.

Let's dive deeper into Android 17.

An intelligence system

With deep integration between hardware, software and AI, we’re transforming Android from an operating system to an intelligence system. It's about delivering new helpful experiences that anticipate user needs, and it brings more opportunities for engagement with your apps. To that end, Android 17 expands the capabilities of AppFunctions, a platform API with a corresponding Jetpack library. It allows you to contribute your app's unique capabilities as orchestratable "tools" for Android MCP, the on-device equivalent of the Model Context Protocol. AI agents and assistants (like Google Gemini) can discover and execute AppFunctions to perform workflows on behalf of the user with direct access to the app's local state.

The Jetpack library, currently in alpha, makes adding AppFunctions as easy as annotating a class and adding KDoc comments.

/**
 * A note app's [AppFunction]s.
 */
class NoteFunctions(
    private val noteRepository: NoteRepository
) {
    /**
     * Adds a new note to the app.
     *
     * @param appFunctionContext The execution context.
     * @param title The title of the note.
     * @param content The note's content.
     */
    @AppFunction(isDescribedByKDoc = true)
    suspend fun createNote(
        appFunctionContext: AppFunctionContext,
        title: String,
        content: String
    ): Note {
        return noteRepository.createNote(title, content)
    }
}

We’ve also launched an AppFunctions agent skill that analyzes your app’s key workflows, automatically generates the required Kotlin code, optimizes your KDocs for LLM tool-calling, and provides ADB commands for testing and debugging.

The Gemini integration is currently in a private preview with trusted testers, but you can begin preparing your apps now. In addition to ADB commands to execute your AppFunctions, we've provided a test agent app that includes an interface to discover and execute your app functions and simulate an AI agent integration. Join our integration early access program at goo.gle/eap-af for a chance to be among the first apps to deploy AppFunctions to production.

Adaptive-first

Your users no longer rely on a single form factor; they transition between phones, foldables, tablets, laptops, automotive displays, and immersive XR environments. Now, with over 580 million large screen devices in the hands of users and the forthcoming launch of Googlebooks, the next generation of ChromeOS built on the Android stack, adaptive is no longer just a technical goal. It’s a massive opportunity to reach highly engaged users, which is one of the reasons we're shifting to an adaptive-first development standard.

No resizability/orientation restrictions on large screens

To ensure apps deliver a premium experience across all form factors, including mobile devices running in desktop mode on connected displays, Android 17 (API level 37) removes the developer opt-out for orientation and resizability restrictions on large screen devices (sw > 600 dp) for apps targeting API level 37. The system will ignore legacy manifest attributes and runtime APIs, including screenOrientation, setRequestedOrientation(), resizeableActivity=false, and aspect ratio constraints (minAspectRatio/maxAspectRatio). Games (based on app category in Google Play) remain exempt. Your app must be ready to adapt to any window size, respect the user's preferred device posture, and support free-form windowing natively.

Next-gen multitasking: App Bubbles, Bubble Bar, and desktop interactive PiP

Android 17 introduces powerful new windowing capabilities that redefine how users multitask, demanding even greater layout flexibility from your apps:

App Bubbles: Moving beyond the messaging bubbles API, users can now transform any app into a floating bubble by long-pressing its icon on the launcher. This feature is available across phones, foldables, and tablets, enabling lightweight multitasking for any workflow.
The Bubble Bar: On large screens (tablets and foldables), the system taskbar now includes a dedicated Bubble Bar to organize, transition between, and dock these floating app bubbles.
Desktop interactive PiP: In desktop environments, Android 17 introduces interactive Picture-in-Picture (PiP). Unlike traditional PiP windows which are read-only, these pinned windows remain fully interactive while staying always-on-top of other application windows.

App Bubbles and Bubble Bar in action

Activity recreation updates

To prevent disruptive state loss and stutter, Android 17 updates the default behavior for Activity recreation. The system will no longer restart activities by default for typical configuration changes that do not require a full UI redraw (including CONFIG_KEYBOARD, CONFIG_KEYBOARD_HIDDEN, CONFIG_NAVIGATION, CONFIG_TOUCHSCREEN, and CONFIG_COLOR_MODE).
Instead, running activities will receive these updates via onConfigurationChanged(), enabling smooth transitions. If your application explicitly relies on a full restart to reload resources for these changes, you must now explicitly opt-in using the new android:recreateOnConfigChanges manifest attribute.

Continue On

Android 17 adds Continue On to help users seamlessly transition a task between Android devices. The user sees a suggestion for the most recently opened app from their mobile device in their tablet taskbar, providing a one-tap affordance to launch the app and deep-link where they left off. Continue on can support app-to-web transitions, including falling back to using the web if the app isn't installed.

Handoff Suggestion on a Tablet

class MyHandoffActivity : Activity() {

    ...

  override fun onCreate(savedInstanceState: Bundle?) {
    super.onCreate(savedInstanceState)
    // Do stuff
    ...
    // Enable handoff
    setHandoffEnabled(true, null)
  }

  // Override and implement onHandoffActivityDataRequested
  override fun onHandoffActivityDataRequested(handoffRequestInfo: HandoffActivityDataRequestInfo) : HandoffActivityData {
    // Create and return handoff data
  }
}

Go adaptive-first with Jetpack Compose

To help you adapt your apps to meet the new Android 17 requirements, we've launched the Jetpack Compose adaptive skill. This AI-powered developer workflow helps you implement the best adaptive practices:

Adaptive navigation: Automatically transition between bottom navigation bars on mobile and edge-anchored navigation rails on large screens using NavigationSuiteScaffold from the Material 3 Adaptive library.
Multi-pane layouts: Implement list-detail and supporting pane layouts natively using Navigation 3 Scenes (ListDetailSceneStrategy and SupportingPaneSceneStrategy) instead of fragile fragment transactions.
FlexBox & Grid APIs: Utilize Compose 1.11's dynamic layout components to easily adjust row and column spans on the fly, ensuring your content always fills the space beautifully.
Advanced non-touch input: Leverage Compose 1.11's enhanced trackpad and mouse support, including native focus rings and new APIs (like TrackpadInjectionScope and performTrackpadInput) to easily test and deliver a true "laptop-class" experience on Googlebooks and Desktop Mode.
Dynamic window states: Leverage Compose's reactive state model to seamlessly adapt your UI when the app transitions from full screen to a floating App Bubble or an interactive Desktop PiP window, ensuring a premium experience even at minimal dimensions.

Android is Compose-first

Compose offers the easiest way to build adaptive apps, and that's just one of the many reasons we believe that all Android UI should be built with Compose. To that end, Android development is now Compose-first. All new Android APIs, libraries, tools, and developer guidance will be built exclusively for Jetpack Compose. Legacy View components (in the android.widget package) and View-based Jetpack libraries (like Fragments, RecyclerView, and ViewPager) are now in maintenance mode. They will receive only critical bug fixes, and no new features.

TIP
Ready to migrate? Use our AI-driven XML to Compose Migration Skill to automatically analyze your legacy View layouts and convert them into highly-adaptive Compose code.

Performance & efficiency

App performance means a smooth user interface, fast app start times, and efficient multitasking; Android 17 has impactful improvements in all of these areas.

App memory limits

Memory usage is one of the silent foundations of overall performance. When a foreground app or service grows unchecked, memory management spikes CPU and battery utilization and eventually leads to the termination of other well-behaved cached apps and background jobs, ultimately forcing slower cold starts and impaired multitasking.

Starting in Android 17, the system will enforce strict app memory limits based on a device's total RAM, abruptly terminating offending processes. New things to help you navigate these tighter requirements:

R8 Optimizer: The R8 optimizer significantly reduces your app's bytecode memory footprint by shrinking classes, methods, and fields into shorter names, and stripping out unused code and resources. Use R8 in full mode along with the new R8 configuration analyzer to make sure your app is getting the most from R8.

The R8 Configuration Analyzer

LeakCanary in Android Studio Panda: The profiler now features native LeakCanary integration as a dedicated task, fully integrated with your IDE and source code.
ApplicationExitInfo: If your app is terminated by these limits, getDescription() from ApplicationExitInfo will return "MemoryLimiter:AnonSwap".
On-Device Anomaly Detection: Part of ProfilingManager, you can leverage trigger-based profiling using TRIGGER_TYPE_ANOMALY to automatically capture heap dumps when the memory limit is reached.

val profilingManager = applicationContext
   .getSystemService(ProfilingManager::class.java)

val triggers = ArrayList<ProfilingTrigger>().apply {
  add(ProfilingTrigger.Builder(
    ProfilingTrigger.TRIGGER_TYPE_ANOMALY).build())
}
profilingManager.addProfilingTriggers(triggers)

And, we're working to surface more in-field memory metrics to you within Google Play Console.

Generational garbage collection

Android 17 introduces more frequent, less resource-intensive young-generation collections to ART's Concurrent Mark-Compact garbage collector (GC). By separating short-lived objects from stable, long-lived ones, the system runs frequent, lightweight "young-generation" sweeps rather than expensive full-heap scans, drastically reducing CPU usage, power drain, and UI stutter. Our testing has shown significant improvements in GC interference with application threads and a reduction in the maximum memory resident set size (RSS). ART improvements are also available to over a billion devices running Android 12 (API level 31) and higher through Google Play System updates.

Lock-Free MessageQueue

For apps targeting SDK 37 or higher, the core android.os.MessageQueue now implements a lock-free architecture, significantly reducing missed frames, improving app startup time, and radically improving the performance of busy queues in multithreaded scenarios. Note: This can break apps that use reflection on private MessageQueue fields and methods. The peekWhen and poll APIs have been added to TestLooperManager for instrumentation testing without relying on MessageQueue internals.

Static final fields now truly final

Starting from Android 17, apps targeting SDK 37 or higher won’t be able to modify “static final” fields, allowing the runtime to apply performance optimizations more aggressively. An attempt to do so via reflection (or deep reflection) will lead to an IllegalAccessException being thrown. Modifying them via JNI’s SetStatic<Type>Field methods family will immediately crash the application.

Custom notification view restrictions

To reduce memory usage we are further restricting the size of custom notification views. This update closes a loophole that allows apps to bypass existing limits using URIs. This behavior is gated by the target SDK version and takes effect for apps targeting API 37 and higher.

Privacy & Security

Maintaining user trust is at the heart of the Android ecosystem. Android 17 introduces robust features that protect sensitive data while simplifying user experiences.

Privacy-preserving choices

Historically, apps required broad, permanent permissions to access information like contacts, precise location and media files. Android 17 continues the shift toward privacy-preserving choices that grant temporary, session-based access only to the data the user explicitly selects:

System-Level Contact Picker: Utilizing ACTION_PICK_CONTACTS, apps can request temporary access only to specific fields (e.g., email or phone number) chosen by the user, eliminating the need for the broad READ_CONTACTS permission. It also fully supports work/personal profile separation.
Customizable Photo Picker aspect ratio: UsingPhotoPickerUiCustomizationParams, you can customize the system photo picker to show thumbnails in portrait mode. This is perfect for apps that always display photos and videos in portrait such as video based social media apps.
System-rendered Location Button: A new system-rendered location button that you can embed in your app grants precise location access for the current session only.
EyeDropper API: A new system-level API, ACTION_OPEN_EYE_DROPPER, allows your app to create a system-powered eyedropper enabling the user to select color from any pixel on the display. This provides a secure, privacy-preserving color-picking experience that eliminates the need for broad, sensitive screen capture or media projection permissions.

val eyeDropperLauncher = registerForActivityResult(ActivityResultContracts.StartActivityForResult()) { result ->
   if (result.resultCode == Activity.RESULT_OK) {
       val color = result.data?.getIntExtra(Intent.EXTRA_COLOR, Color.BLACK)
       // Use the picked color in your app
   }
}
fun launchColorPicker() {
   val intent = Intent(Intent.ACTION_OPEN_EYE_DROPPER)
   eyeDropperLauncher.launch(intent)
}

Picking a color from anywhere on the screen with the system EyeDropper

Local network access

Apps targeting Android 17 now either require the ACCESS_LOCAL_NETWORK runtime permission or the use of system-mediated, privacy-preserving device pickers for local network communication, such as talking to smart home devices or casting receivers. Because ACCESS_LOCAL_NETWORK falls under the existing NEARBY_DEVICES permission group, users who have already granted other NEARBY_DEVICES permissions will not be prompted again.

SMS OTP protection

Android 17 expands SMS one-time-password (OTP) protection by delaying access to SMS messages for three hours:

WebOTP Format: Delayed for all apps that are not the intended recipient (domain mismatch).
Standard SMS OTP: Delayed for all apps targeting SDK 37+.
Exemptions: Default SMS, assistant, and connected companion apps are exempt. Apps are strongly encouraged to migrate to the SMS Retriever or SMS User Consent APIs.

Post-Quantum Cryptography (PQC)

Android 17 is ready for the next generation of cryptographic security:

Keystore Integration: Supported devices can generate ML-DSA (Module-Lattice-Based Digital Signature Algorithm) keys in secure hardware to produce quantum-safe signatures, exposed via standard JCA APIs.
Hybrid APK Signing: Introducing the v3.2 APK Signature Scheme, which combines classical signatures with ML-DSA signatures to secure app delivery.

Safer native dynamic code loading

If your app targets SDK 37 or higher, the Safer Dynamic Code Loading (DCL) protection introduced in Android 14 for DEX and JAR files now extends to native libraries. All native files loaded using System.load must be marked as read-only. Otherwise, the system throws UnsatisfiedLinkError

Smarter password protection for physical inputs

With Android 17, we're making it safer to enter passwords, PINs, and other secrets when using a physical keyboard by no longer showing the last typed character by default.

Users can still easily customize these display settings to match their preferences (availability may vary by device manufacturer).

These enhanced privacy protections are automatically supported byAndroid's built-in SDK components and will be supported in Compose 1.12 for SecureTextFields.

Smarter password protection for physical inputs

Media and camera features that empower creators and delight users

Android 17 introduces new creator features that give access to pro-quality cameras and media, all while improving the experience for consumers.

Eclipsa Video: HDR video standard built upon the SMPTE ST 2094-50 specification that introduces new metadata to help devices adapt content for their display headroom and ambient light conditions, as well as improve the simultaneous display of standard and HDR content.
RAW14 image format: New support for the RAW14 image format provides a way for your professional camera app to capture the highest level of detail and color depth from compatible camera sensors.
Vendor-defined camera extensions: Vendor-defined extensions enable hardware partners to define and implement custom camera extension modes, providing access to the best and latest camera features.
Extended HE-AAC software encoder: A new system-provided Extended HE-AAC software encoder, supports both low and high bitrates using unified speech and audio coding, providing significantly better audio quality for voice messages in low-bandwidth conditions, including support for loudness metadata.
Versatile Video Coding (H.266): Enables OEMs to add codec support by defining the video/vvc MIME type in MediaFormat, adding new VVC profiles in MediaCodecInfo, and integrating support into MediaExtractor.
Camera device type: New APIs that query the underlying device type to identify if a camera is built-in hardware, an external USB webcam, or a virtual camera.
Constant Quality for Video Recording: SetVideoEncodingQuality in MediaRecorder configures a constant quality (CQ) mode for video encoders to ensure uniform visual fidelity across the entire video.

Better support for hearing aids

Bluetooth LE Audio hearing aid support: Android now includes a specific device category for Bluetooth Low Energy (BLE) Audio hearing aids with the new AudioDeviceInfo.TYPE_BLE_HEARING_AID constant, so your app can distinguish hearing aids from regular headsets to provide a tailored experience for users with assistive listening devices.
Granular audio routing for hearing aids: Android 17 allows users to independently manage where specific system sounds are played. They can choose to route notifications, ringtones, and alarms to connected hearing aids or the device's built-in speaker, helping to avoid unwanted in-ear interruptions while maintaining a Bluetooth connection for hearing aid management apps.

CameraX and Media3

CameraX and Media3 have been updated for Android 17. They are there to do the heavy lifting, smoothing the rough edges of media development and simplifying building reliable camera capture, smooth media playback, and creative and complex editing experiences.

We've released an agent skill that can migrate legacy Android camera implementations (Camera1 or raw Camera2 APIs) to CameraX.

Note: You'll need to update your CameraX version to either 1.5.2 or 1.6.0+ to avoid a crash related to an added dynamic range mode on Android 17 devices.

Get your apps, libraries, tools, and game engines ready!

If you develop an Android SDK, library, tool, or game engine, it's critical to prepare any necessary updates now to prevent your downstream app and game developers from being blocked by compatibility issues and allow them to target the latest SDK features. Please let your downstream developers know if updates are needed to fully support Android 17.

Testing involves installing your production app or a test app making use of your library or engine using Google Play or other means onto a device or emulator running Android 17 Beta 4. Work through all your app's flows and look for functional or UI issues. Each release of Android contains platform changes that improve privacy, security, and overall user experience; review the app impacting behavior changes for apps running on and targeting Android 17 to focus your testing, including the following:

Resizability on large screens: Once you target Android 17 (SDK 37), you can no longer opt out of maintaining orientation, resizability and aspect ratio constraints on large screens.
Dynamic code loading: If your app targets SDK 37 or higher, the Safer Dynamic Code Loading (DCL) protection introduced in Android 14 for DEX and JAR files now extends to native libraries. All native files loaded using System.load() must be marked as read-only. Otherwise, the system throws UnsatisfiedLinkError.
Enable CT by default: Certificate transparency (CT) is enabled by default. (On Android 16, CT is available but apps had to opt in.)
Local network protections: Apps targeting SDK 37 or higher have local network access blocked by default. Switch to using privacy preserving pickers if possible, and use the new ACCESS_LOCAL_NETWORKpermission for broad, persistent access.

Background audio hardening: Starting in Android 17, the audio framework enforces restrictions on background audio interactions including audio playback, audio focus requests, and volume change APIs. Based on your feedback, we’ve made some changes since beta 2, including targetSDK gating while-in-use FGS enforcement and exempting alarm audio. Full details available in the updated guidance.
NPU access declaration: Apps targeting Android 17 that need to directly access the NPU must declare FEATURE_NEURAL_PROCESSING_UNIT in their manifest to avoid being blocked from accessing the NPU. This includes apps that use the LiteRT NPU delegate, vendor-specific SDKs, as well as the deprecated NNAPI.

Get started with Android 17

Your Pixel device should get Android 17 shortly if you haven't already been on the Android Beta. If you don’t have a Pixel device, you can use the 64-bit system images with the Android Emulator in Android Studio. If you are currently on Android 17 Beta 4.1 and have not yet taken an Android 17 QPR1 beta, you can opt out of the program and you will then be offered the release version of Android 17 over the air.

Getting the Android 17 beta on partner devices

Android 17 is available in beta on handset, tablet, and foldable form factors from partners including Honor, iQOO, Lenovo, OnePlus, OPPO, Realme, Sharp, vivo, and Xiaomi.

For the best development experience with Android 17, we recommend that you use the latest Canary build of Android Studio Quail. Once you’re set up, here are some of the things you should do:

Test your current app for compatibility, learn whether your app is affected by changes in Android 17, and install your app onto a device or Android Emulator running Android 17 and extensively test it.

Thank you again to everyone who participated in our Android developer preview and beta program. We're looking forward to seeing how your apps take advantage of the updates in Android 17, and have plans to bring you updates in a fast-paced release cadence going forward.

For complete information on Android 17 please visit the Android 17 developer site.

What’s New in Android XR: Tooling, Engine Support, and Ecosystem Updates

2026-06-15T06:00:00.000-07:00

Posted by Stevan Silva, Group Product Manager, and Vinny DaSilva, Developer Relations Engineer, Android XR

From augmented overlays to fully immersive environments, the Android XR ecosystem is expanding rapidly, with the Samsung Galaxy XR already available today. Alongside the latest updates from Google I/O and this week's Augmented World Expo (AWE), we are rolling out new tooling, broader engine support, and ecosystem resources to help you build and scale experiences for Android XR.

To get a quick look at what’s new, check out our video recap!

Ready to dive deeper? Let’s jump into the major updates that will streamline your XR development workflow.

Build, Prototype, and Iterate with Developer Preview 4

Developer Preview 4 of the Android XR SDK delivers the APIs and tools you need to design and build right from your laptop. This update includes the specific libraries required to target both immersive and augmented experiences. Check out the video below for a comprehensive breakdown of the latest in Android XR:

To test all of these interactions without needing physical hardware, you can emulate and iterate on your code entirely within Android Studio. Check out our tooling deep dive to see how you can use XR emulator today:

Extending your mobile apps for intelligent eyewear

Building for audio and display glasses doesn't mean starting from scratch. With the Jetpack Projected library, you can take your existing mobile app to create a complementary augmented experience. The new release includes a Device Availability API that hooks into standard Android Lifecycle states, allowing your app to natively adapt its behavior based on whether the glasses are being worn.

To accelerate your development journey, use Android CLI and the display glasses skill to extend your mobile app into an augmented experience. The skill is packed with specialized knowledge of Jetpack Compose Glimmer, enabling it to build your UI using our recommended design patterns.

We’ve also updated Jetpack Compose Glimmer to optimize text legibility on optical see-through displays and provide touchpad-optimized navigation components.

See how it looks in action: Developers at NAVER Papago are already exploring how to seamlessly bring their mobile experience directly to display glasses.

To learn how to leverage these tools, watch this session on extending mobile apps for AI glasses:

Building global, location-based immersive experiences

For developers focused on immersive experiences, Developer Preview 4 brings modern, Kotlin-first architectural upgrades across our core perception libraries. We have also introduced an early preview of the Geospatial API for wired XR glasses. By combining ARCore for Jetpack XR with Google's Visual Positioning System (VPS), you can anchor digital content to high-precision real-world locations.

Leverage the Platforms You Know with Expanded Engine Support

We want you to build using the ecosystems and workflows you already know best. To make it easier to bring your existing XR experiences over to Android XR, we are thrilled to introduce official support for Unreal Engine and Godot alongside our existing Unity's support for wired XR glasses.

With this expansion, we are introducing the Android XR Engine Hub, a desktop tool for Windows that shortens iteration cycles by bringing real-time testing directly into your engines viewport. Catch the full breakdown of our engine updates here:

Apply Today for the Android XR Developer Catalyst Program

In addition to providing the platform, we want to fuel your innovation directly through ecosystem resources. The Android XR Developer Catalyst Program is designed to support developers with access to pre-release hardware, including display glasses, and wired XR glasses.

Accepted developers will receive resources, support forums, and launch guidance to prepare their apps for Google Play. Applications are open right now, so don't wait to submit your project ideas.

Start Building!

The ecosystem is growing rapidly, and the tools are ready for you to explore. Samsung Galaxy XR is available now, and you can dive in today with Developer Preview 4 of the Android XR SDK. If you don’t have hardware yet, check out the tools and to get started with the XR Emulator in Android Studio.

For a complete look at all of our technical sessions, browse the full Android XR Playlist on YouTube to see what else is possible. We can’t wait to see what you build!

Top 3 updates for Android developer productivity

2026-06-09T06:00:00.000-07:00

Posted by Simona Milanovic, Developer Relations Engineer

Every year, Google I/O brings new announcements and resources across ecosystems and products, including Android development. As development shifts toward AI and agent-assisted tooling, we’ve expanded our offerings to better support you, however you decide to build for Android.

To help you stay up to date, here is a summary of the top 3 announcements for Android Developer Productivity at I/O.

1. Android CLI is now stable

Android CLI is now stable at version 1.0, with more capabilities and integrations.

The latest version of Android CLI introduces many new features, like programmatic version lookup and support for Journeys, and bridging capability to allow agents to integrate directly with Android Studio, via the studio command.

Running Android Studio alongside the agent and Android CLI enables more efficient navigation in your project, more precise output, and access to Android Studio’s unique tooling, such as performance profilers, Compose Previews, and Android Device Streaming.

Android CLI now integrates seamlessly with Android Studio

Additionally, Google Antigravity now officially supports Android development, with the Android resources bundle, which includes the Android CLI and skills.

You can either install the bundle during onboarding after installation, or later from the Settings > Customizations > Build With Google Plugins menu. This provides Antigravity with all the powerful tools and knowledge of Android CLI to enable it to perform core tasks—from creating projects to deploying your app on a new virtual device—much more easily and efficiently.

Google Antigravity now offers the Android resources bundle

Android CLI is now available through more package managers: like npm and homebrew. For more information, check out the Android CLI blog post and official documentation.

2. Android skills keep growing

To help models gain expertise for specific development patterns that follow our best practices, we are continuing to expand our repository of Android skills, available through Android CLI and GitHub.

Android skills ground LLMs in specialized workflows and domain knowledge, for the most common and more complex user journeys they might struggle with. We’ve shipped a fresh new batch of skills, with now more than 17 skills for areas such as:

Adaptive UI
Display Glasses and Jetpack Compose Glimmer for XR
Migration to CameraX
Perfetto SQL and Trace Analysis
Jetpack Compose Styles API
AppFunctions
Verified email retrieval with Android Credential Manager
Engage SDK integration
Testing setup
Wear OS Jetpack Compose Material3

Android skills keep growing

You can browse skills and install using the Android CLI commands:

android skills list
android skills add –skill=<skill-name>

For more information, check out the official documentation.

3. Android Bench adds new models

Earlier this year, we launched Android Bench - our leaderboard for testing LLMs on real-world Android development challenges and tasks, with the goal of accelerating model improvements, so you have more helpful options for AI assistance.

Latest results from Android Bench leaderboard

You asked us to evaluate open models. So, at I/O, we added more commonly used ones, including our local model Gemma 4, to the leaderboard. We also added the latest models including Gemini 3.5 Flash.

We are also working on increasing the difficulty of challenges we’re giving LLMs, including creating long running tasks, to continue encouraging improvements. These tasks will be coming soon to Android Bench. Check out the Android Bench leaderboard to see the latest results.

Android development anywhere

By expanding our AI-assisted Android development offerings to Antigravity, through Android CLI and Android skills, and solidifying with the pro capabilities and production grade polish of Android Studio, we’re supporting Android developers wherever they choose to build.

Have fun bringing your ideas to life faster and easier than ever before - we’re excited to see what you build in this new era of agentic development.

Check out the full Developer productivity at Google I/O 2026 YouTube playlist for more information.

Datadog delivers millions of in-depth performance insights with ProfilingManager

2026-06-08T06:00:00.000-07:00

Posted by Alice Yuan, Developer Relations Engineer at Google, Arti Arutiunov, Product Manager at Datadog and Nikita Ogorodnikov, Staff Software Engineer at Datadog

Performance regressions are notoriously hard to reproduce, making regressions a massive bottleneck for mobile developers. Although signals like ANR rates indicate what issues occur in production, pinpointing the specific line of code that resulted in the performance issue has historically necessitated exhaustive manual reproduction or speculative trial-and-error experimentation.

Datadog collaborated with Google to mitigate this frustration by integrating the ProfilingManager API (available on Android 15+ devices) into its Real User Monitoring (RUM) and Continuous Profiling platforms. This integration transforms the debugging workflow, allowing developers to move beyond surface-level symptoms to being able to detect the why behind a performance bottleneck.

By leveraging this system-level API, Datadog now processes millions of production profiles weekly across the globe according to Datadog internal data of June 2026. It provides engineering teams with a new level of visibility into real-world performance, all while maintaining a low runtime overhead for production-scale performance monitoring.

The impact of ProfilingManager

ProfilingManager is a system service introduced in Android 15 that enables apps to programmatically collect performance data such as call stack samples, field traces and memory heap dumps directly from production environments. This capability shifts the engineering paradigm from reactive manual reproduction to proactive field analysis.

For example, a Google communications app used field traces to investigate why its cold start times were slower on newer, more powerful hardware. By diving into the field-collected traces and comparing traces across different device types, the engineer discovered a hidden scheduling issue: a background text-to-speech service was unnecessarily being prewarmed during app startup. The traces revealed that this background process was monopolizing the device's highest-performing big CPU core, forcing the app's main thread to sleep while the prewarm occurred.

Solving the Android code-level visibility challenge

Prior to the implementation of ProfilingManager, Datadog’s Real User Monitoring (RUM) focused on high-level application health and session-level telemetry to assess the user journey. Engineering teams could monitor Android performance signals like time to initial display, ANR rates, CPU load, and frozen frames. These insights extended to granular interactions, such as network latency, touch events, and main thread hangs. However, while this data effectively highlighted which performance bottlenecks were surfacing in the field, it provided no clear path to identifying the root cause of these failures.

To address this, Datadog needed a profiling engine capable of capturing Android traces directly from devices in production with minimal performance impact. After evaluating alternative approaches, such as writing their own trace processor using Android Debug APIs, the team selected ProfilingManager because it is the most performant solution of the profiling options they evaluated and offloads the sampling decisions overhead to the OS.

ProfilingManager supports a wide range of collection methods, including CPU traces, call stack sampling, memory analysis through Java heap dumps and native heap profiles. It enables developers to profile production builds, upload trace files to external storage, and review them in the Perfetto trace analyzer UI. As a SaaS provider, Datadog uploads, visualizes, and analyzes these profiles collected via its SDK, providing a unified view of application health.

By centralizing high-fidelity telemetry within a unified observability API, ProfilingManager empowers Datadog and its clients to proactively monitor, investigate, and remediate complex Android performance regressions through key technical advantages:

Granular session diagnostics: ProfilingManager enhances debuggability by delivering direct OS-level trace data, overcoming the visibility and alignment challenges typical of custom logging with system services. To dive deeper, developers can download these traces from Datadog to investigate further in visualization tools like the Perfetto UI.
Automated telemetry triggers: By leveraging native system events to initiate trace recordings at key optimization points, Datadog reduces the need to build custom collection logic. While the initial rollout focuses on the APP_FULLY_DRAWN signal, there are already plans to expand this observability to include ANR, OOM, and COLD_START triggers.
Proactive trace snapshots: By interfacing directly with the system-level Perfetto service (traced), ProfilingManager utilizes a proactive background recording model designed to capture unpredictable issues. This ensures that developers receive a precise visualization of the events leading up to a performance anomaly, offering a level of insight that exceeds what is possible through manual instrumentation.
Bottleneck detection at scale: Datadog is able to synthesize telemetry from across Datadog’s global customer base to uncover regressions that only emerge under unique hardware configurations and variable network environments.
System-enforced resource stability: The API leverages sampling trace collection to ensure performance and user experience impacts remain unnoticeable.
On-device data controls: ProfilingManager filters out irrelevant information from other processes on-device before the profile is delivered to the app. This minimizes file sizes and ensures that only data relevant to the app's processes is provided.

Processing millions of weekly profiles to optimize real-world apps

An example of Datadog's time to initial display measurement with
stack sampling powered by ProfilingManager

Integrating a system-level profiling API into a global monitoring SDK required solving infrastructure challenges. Because ProfilingManager generates highly detailed performance traces, the Datadog engineering team had to build a pipeline capable of parsing and analyzing these profiles on the server side at scale. Beyond profile collection, Datadog also emphasizes the importance of balancing sampling frequency with collecting enough data to generate meaningful insights about your application. Datadog relies on ProfilingManager’s built-in rate limiting as a critical stability safeguard, preventing excessive telemetry requests from overburdening user devices.

The team has been profiling Datadog's own native Android application and a number of early adopters’ applications for months, gathering millions of profiles to ensure a fast, error-free launch experience and to refine their performance-detection algorithms. Today, the production integration seamlessly scales across a variety of Android devices.

Conclusion

By integrating Android’s ProfilingManager API, Datadog successfully closed the visibility gap between backend systems and mobile client applications for their customers. By processing millions of profiles weekly with negligible device overhead, Datadog equips Android developers with the code-level insights necessary to diagnose complex performance bugs instantly, helping developers build smoother applications and improve their app’s performance signals in the Play Store. To adopt the ProfilingManager API directly into your performance observability framework, check out our documentation.

In the future, Datadog aims to make Android profiling data a first-class input for coding agents to autonomously resolve performance bottlenecks, closing the feedback loop between detection and remediation. Datadog is working toward making Android profiling broadly accessible to developers.

To get started using the Datadog real user monitoring feature powered by ProfilingManager, visit Datadog Mobile Real User Monitoring.

Prioritizing Memory Efficiency: Essential Steps for Android 17

2026-06-02T12:00:00.000-07:00

Posted by Alice Yuan, Developer Relations Engineer, Ajesh Pai, Developer Relations Engineer, and Fung Lam, Developer Relations Engineer

While app performance is often equated with a smooth UI and fast start times, memory serves as the silent foundation upon which these visible metrics are built. It's no secret that we're seeing a shift where device memory is more important than ever. Not only have we made strides in Android memory optimizations with Android 17, we're providing the tooling and API support to help you stay ahead of stricter memory requirements later this year.

To ensure device stability, starting in Android 17, the system will begin enforcing app memory limits based on the device's total RAM. If an app exceeds those limits, Android will kill the process with no associated stack trace.

Beyond these forced terminations, unoptimized memory usage inevitably degrades the user experience. When the app approaches heap memory limits, it triggers frequent garbage collection—leading to noticeable UI stutters. Furthermore, when a device runs out of available memory, the system scrambles to reclaim pages, causing CPU strain, UI latency, and battery drain. If the memory shortage is too severe, it can cause Low Memory Killer (LMK) events that abruptly terminate background processes and force apps to have slow cold starts and lose user state.

To build highly performant apps and avoid these forced terminations, we recommend that you adopt the following memory optimization strategies:

Maximize bytecode optimization with R8
Optimize image loading
Detect and fix memory leaks with Android Studio
Trim memory when app leaves visible state
Advanced memory observability with ProfilingManager

A condensed version of this blog post is also available in video format, go check it out!

Understanding Android 17 app memory limits

App memory limits are being introduced in Android 17 to prevent "one bad actor" from destroying the multitasking experience and stability of the user’s entire device.

Here is a breakdown of the reasons driving this architectural change:

Preventing cascading kills: When an app becomes bloated or leaks memory while holding a privileged state (e.g. it’s running a Foreground Service), it is initially shielded from the system's Low Memory Killer (LMK). As this single app grows unchecked and hoards RAM, the LMK is forced to compensate by killing off dozens of smaller, well-behaved cached apps and background jobs to reclaim space for the memory hog.
Preserving multitasking and user state: When the system is forced to purge cached apps to accommodate a single leaking process, the multitasking experience is severely degraded. Users returning to prior cached applications encounter sluggish cold starts instead of near-instant warm resumes. This inefficiency generates more CPU strain and accelerates battery depletion. It can also destroy the user’s context in recently used apps, such as scroll positions, navigation stacks, and in-game progress.

To determine if your app session was impacted by these constraints in the field, you can call getDescription() within ApplicationExitInfo. If the system applied a limit, the exit reason is reported as REASON_OTHER and the description string will contain "MemoryLimiter:AnonSwap". You can also leverage trigger-based profiling using TRIGGER_TYPE_ANOMALY to automatically capture heap dumps when the memory limit is reached. Furthermore, Android is actively working to surface more in-field memory metrics to developers within the Google Play Console.

We have also expanded our memory limits documentation to include local debugging commands, allowing you to simulate memory constraints in your local environment and validate your application's behavior under any memory limit enforcement.

Maximize bytecode optimization with R8

A highly effective way to reduce your app's memory footprint is to enable the R8 optimizer. By shrinking classes, methods, and fields into shorter names and stripping out unused code and resources, R8 significantly reduces your app's memory footprint by minimizing the amount of resident code required during execution.

R8 minimizes resident code, shrinking the memory footprint and lowering LMK termination risk. This results in more frequent warm starts over slow cold starts. Additionally, streamlined bytecode reduces main-thread CPU overhead, directly cutting ANR rates for a more fluid user experience. For example, the digital bank Monzo enabled full R8 optimization and saw a 35% reduction in their ANR rate, a 30% improvement in cold start rate, and a 9% reduction in overall app size.

The digital bank Monzo enabled full R8 optimization and boosted performance metrics by up to 35%.

To properly configure R8 in your build.gradle file:

Set isShrinkResources = true and isMinifyEnabled = true.
Use proguard-android-optimize.txt instead of the legacy proguard-android.txt, which actually prevents optimizations and is no longer supported in Android Gradle Plugin 9.
Remove android.enableR8.fullMode = false from your gradle.properties.

If you are using reflection in your code base, then add Keep rules to prevent R8 from optimizing those parts of the code. Make sure to scope the keep rules narrowly to get the maximum optimization.

To get the maximum optimization, make sure to follow these best practices in your keep rule file.

Remove global options like -dontoptimize, -dontshrink, and -dontobfuscate that prevent R8 from optimizing the entire codebase
Remove keep rules that prevent optimizing Android components like Activity, Services, Views or Broadcast receivers.
Refine the broad package wide keep rules to target only specific classes or methods.

To see more best practices, view our keep rules documentation.

Library Developer R8 Best Practices

If you are a library developer, strictly place the rules your consumers need into your consumer-rules file, and keep your library's internal protection rules in your proguard-rules.pro file. For more information on how to optimize libraries, see Optimization for library authors.

R8 Configuration Analyzer

To audit your R8 optimization, use the Configuration Analyzer. Configuration analyzer shows the current state of optimization with Obfuscation, Optimization, and Shrinking scores. With configuration analyzer, you can also understand how many classes, methods or fields are prevented from optimization by each keep rule. Refine these broad package wide keep rules to unlock the maximum optimization.

Using configuration analyzer, you can also identify keep rules that are subsuming other keep rules, redundant keep rules and unused keep rules.

The Configuration Analyzer shows the current state of optimization with Obfuscation, Optimization, and Shrinking scores.

R8 Agent Skill

You can also leverage the R8 Agent Skill with Android Studio agent or other AI tools to resolve misconfigurations and refine your rules resulting in improved app performance. (Insights from AI-driven skills will require technical verification)

Optimize image loading

Bitmaps are usually the largest common objects residing in your app's memory. They represent the final stage of the image loading process where compressed files, like JPEGs or PNGs, are decoded into raw pixel data for display. This means a tiny 100KB compressed image can balloon into several megabytes of RAM because memory consumption is determined by the image's pixel dimensions and color depth. Since bitmap operations are frequently on the critical path to drawing frames, unoptimized images cause severe memory bloat and UI jank.

Google recommends leveraging image loading libraries Coil for Kotlin-first projects, particularly when developing with Jetpack Compose and Glide for Java-based applications.

Adopt these five best practices

Downsample images: If you’re loading bitmaps manually, avoid loading a massive image into a tiny thumbnail view; use inSampleSize to load a smaller version. Glide and Coil downsamples images by default and you can configure this downsample strategy using DownsampleStrategy and ImageLoader respectively.
Cropping: Avoid embedding padding directly into an image file for letterboxing purposes (e.g., creating a transparent border to expand an image dimensions). Rather than baking in these borders, utilize InsetDrawable or apply padding directly within the View or Composable containing the bitmap.
Config: Balance memory and quality by choosing the right pixel format. Use RGB_565 when transparency isn't needed, which uses half the memory of the default ARGB_8888 format. In Glide you can configure this by using DecodeFormat and in Coil you can use bitmapConfig property.
Prioritize vector drawables: For basic geometric assets, leverage ShapeDrawable as a lightweight alternative to decoding rasterized bitmaps. By defining these assets once via XML, you ensure they scale seamlessly across all display densities while effectively eliminating resource-driven memory bloat.
Reuse: If your application manages Bitmaps manually then to minimize memory churn, when a bitmap is no longer required, the app should call bitmap.recycle() and immediately discard the Bitmap reference. If you use an image loading library like Glide or Coil, return the bitmap to the library’s managed pool. By providing an existing buffer for future memory needs, the pool effectively avoids the overhead of new allocations.

Check out our documentation on Optimizing performance for images to learn more.

Android Studio tooling

You can also eliminate redundant bitmaps using Android Studio Narwhal 4. Here is how to hunt them down in five simple steps:

Open the Profiler tab in Android Studio
Click Heap Dump (or "Analyze Memory Usage") and hit record to take a snapshot of your app’s current memory state.
Scan the analysis results for the yellow warning triangle ⚠️, which Android Studio uses to flag duplicate bitmaps being stored multiple times. Alternatively, navigate to the profiler header, choose "Filter by:" and pick the "Duplicate Bitmaps" setting.
Click on any flagged entry to open the Bitmap Preview pane, allowing you to see exactly which image is the repeat offender.
Use that visual confirmation to track down the redundant loading logic in your code and implement a better caching strategy.

Look for the yellow warning triangle ⚠️ in heap dumps when using the Android Studio Profiler.

Detect and fix memory leaks with Android Studio

Android Studio Panda 3 features a dedicated LeakCanary profiler task, allowing developers to analyze real-time memory leaks and map traces within the IDE.

The LeakCanary profiler task in Android Studio actively moves the memory leak analysis from your device to your development machine, resulting in a significant performance boost during the leak analysis phase as compared to on-device leak analysis.

LeakCanary memory leak analysis contextualized with Go to declaration for debugging

Additionally, the leak analysis is now contextualized within the IDE and fully integrated with your source code, providing features like go to declaration and other helpful code connections that drastically reduce the friction and time required to investigate and fix memory leaks.

Examples of common memory leaks

Memory leaks occur when an object persists in memory beyond its intended lifespan. This typically happens due to:

Retaining references to Fragments, Activities, or Views that are no longer in use.
Mismanaging Context references.
Failing to properly unregister observers, listeners, and receivers.
Creating static references to objects that are bound to components with shorter lifecycles.

Here are a few example scenarios:

Scenario	Compose-based example	View-based example
Leaking Context	Example: Passing LocalContext.current to a ViewModel Fix: Keep `Context` dependent logic within the UI layer. For non-UI layers, refactor to use dependency injection or observe UI state using Kotlin flow.	Example: Storing an `Activity` in a companion object or static variable. Fix: Don’t hold static references to UI components. Refactor to use dependency injection or observe UI state using Kotlin flow.
Leaking Listeners	Example: Using `DisposableEffect` to start a listener but leaving `onDispose` empty. Fix: Perform the unregistration and cleanup logic inside the `onDispose` block.	Example: Registering for SensorManager updates and forgetting to unregister. Fix: Manually call `unregisterListener()` in `onStop()` or `onDestroy()` lifecycle.
Leaking Views	Example: Holding a reference to a legacy `View` inside an `AndroidView` without a release strategy. Fix: Use the `release` block of the `AndroidView` composable to clean up the legacy `View`.	Example: Keeping a reference to a view binding object after the `Fragment` is destroyed. Fix: Set the binding variable to `null` inside the `onDestroyView`() lifecycle method.

Trim memory when app leaves visible state

Android can reclaim memory from your app or stop your app entirely if necessary to free up memory for critical tasks, as explained in Overview of memory management. Android will usually reclaim memory from your app when it’s not visible to the user, such as by discarding some of your app’s code and data pages in memory or compressing your heap allocations. When the user resumes your app and your app tries to access some memory that’s been reclaimed, the OS will swap that memory back in on demand. This swapping behavior can be slow, and cause unexpected jank or stutters in your app.

If you leave it to the OS to decide what memory to reclaim from your app, you may find that the OS reclaimed memory that you’ll need shortly after resuming your app. Instead, your app can voluntarily discard memory allocations that it can regenerate later, on demand and at a low cost. To do so, you can implement the ComponentCallbacks2 interface. You can implement onTrimMemory in your Activity, Fragment, Service, or even your custom Application class. Using it in the Application class is highly effective for global cache management.

The provided onTrimMemory() callback method notifies your app of lifecycle or memory-related events that present a good opportunity for your app to voluntarily reduce its memory usage.

In terms of memory lifecycle management, your implementation should focus exclusively on TRIM_MEMORY_UI_HIDDEN and TRIM_MEMORY_BACKGROUND. Since Android 14, the system has ceased delivering notifications for other legacy constants, which were formally deprecated in Android 15.

TRIM_MEMORY_UI_HIDDEN: This signal indicates that your application's UI has transitioned out of the user's view. This provides an opportunity to release substantial memory allocations tied strictly to the interface—such as Bitmaps, video playback buffers, or complex animation resources.

TRIM_MEMORY_BACKGROUND: At this level, your process is residing in the background and is now a candidate for termination to satisfy the system's global memory needs. To extend the duration your process remains in the cached state, and reduce the number of app cold starts, you should aggressively release any resources that can be easily reconstructed once the user resumes their session.

import android.content.ComponentCallbacks2
// Other import statements.

class MainActivity : AppCompatActivity(), ComponentCallbacks2 {

    /**
     * Release memory when the UI becomes hidden or when system resources become low.
     * @param level the memory-related event that is raised.
     */
    override fun onTrimMemory(level: Int) {

        if (level >= ComponentCallbacks2.TRIM_MEMORY_UI_HIDDEN) {
            // Release memory related to UI elements, such as bitmap caches.
        }

        if (level >= ComponentCallbacks2.TRIM_MEMORY_BACKGROUND) {
            // Release memory related to background processing, such as by
            // closing a database connection.
        }
    }
}

Note: The onTrimMemory integration may depend on SDK support. For instance, certain games rely on their game engine to enable this capability. Please check out the game memory optimization documents.

Advanced memory observability with ProfilingManager

To catch and diagnose memory issues in the field that cannot be reproduced locally, you should leverage the ProfilingManager API. Introduced in Android 15, this advanced observability API allows you to programmatically collect real-user Perfetto profiles.

For teams that lack a dedicated infrastructure to manage and host performance artifacts, Crashlytics is exploring a specialized solution to streamline this workflow. They are inviting developers to provide feedback.

Android 17 introduces new event-driven triggers, most notably TRIGGER_TYPE_OOM and TRIGGER_TYPE_ANOMALY:

The OOM trigger automatically collects a Java heap dump at the exact moment an OutOfMemoryError crash occurs, providing precise allocation states. A collected OOM profile is provided the next time the app starts and registers the registerForAllProfilingResults callback.
The Anomaly trigger detects severe performance issues, such as excessive binder spam or breached memory thresholds. The memory anomaly delivers a heap dump just prior to the system terminating the app.

  val profilingManager = 
applicationContext.getSystemService(ProfilingManager::class.java)
    val triggers = ArrayList()  


    triggers.add(ProfilingTrigger.Builder(
                 ProfilingTrigger.TRIGGER_TYPE_ANOMALY))
    val mainExecutor: Executor = Executors.newSingleThreadExecutor()
    val resultCallback = Consumer { profilingResult ->
        if (profilingResult.errorCode != ProfilingResult.ERROR_NONE) {
            // upload profile result to server for further analysis          
            setupProfileUploadWorker(profilingResult.resultFilePath)
        } 

    profilingManager.registerForAllProfilingResults(mainExecutor, resultCallback)
    profilingManager.addProfilingTriggers(triggers)

Once you’ve collected the heap dump, you can download the profile from the server, or locally via adb pull and drag and drop the file into the Perfetto UI. To streamline your memory debugging workflow, use the Heap Dump Explorer, this is the new default view for heap dumps in Perfetto UI. This tool provides an intuitive interface for inspecting Java heap dumps, allowing you to visualize object allocation hierarchies, compute retained memory sizes, and identify the shortest path from garbage collection root. By leveraging the Heap Dump Explorer, you can rapidly pinpoint memory leaks, bloated retained objects such as excessive bitmap allocations, and analyze heap object allocations all in one place.

Use the Heap Dump Explorer’s embedded flamegraph to visually inspect and navigate through objects with the highest heap allocations.

Conclusion

Optimizing bytecode with R8, adopting image loading best practices, and resolving memory leaks are critical steps toward delivering a high-quality user experience while managing resources effectively under pressure. Adopting these proactive measures helps maintain app stability and performance, preventing unexpected terminations while safeguarding user context. To further your performance expertise, explore our revised memory guidance.

Building Premium Android Experiences at Google I/O ‘26

2026-06-02T10:00:00.000-07:00

Posted by Ataul Munim, Android Developer Relations Engineer

A truly differentiated Android experience is about delivering premium delight wherever your users are. At Google I/O ‘26, we showcased how the latest advancements in the Android ecosystem can help you elevate your app's quality while maximizing development efficiency.

To help you build apps that stand out, we're diving into the key tools and libraries designed to optimize your core performance, extend the surfaces of your app to other devices, and streamline how your app handles high-quality media.

Here is a recap of the essential updates and sessions you need to know to deliver a next-level experience across form factors!

Maximize app performance and ROI with the R8 Configuration Analyzer

A premium experience is only as good as its foundation, and a performant foundation is what allows your app to scale across the Android ecosystem. This is especially true with the release of Android 17, which introduces conservative, device RAM-based app memory limits to target extreme memory leaks and outliers before they cause system-wide instability. To stay below these new system thresholds and prevent your app from being terminated, having a lean footprint is no longer optional: it’s a critical requirement.

This year, we’re making it easier to build highly optimized, fast apps by introducing the R8 Configuration Analyzer in Android Studio. R8 is your most powerful tool for improving app performance, but its effectiveness is often limited by overly broad "keep rules" that prevent the compiler from stripping away unused code. The new Configuration Analyzer provides optimization, obfuscation, and shrinking scores, allowing you to identify specific rules that are preventing the benefits of R8 optimization.

By optimizing their R8 configurations, developers at Monzo achieved a 30% improvement in cold starts and a 35% reduction in ANRs. Smaller, faster code isn't just about efficiency; it's about ensuring your app has the memory headroom to deliver delight on every form factor, from the phone to the car.

Extend your reach with a unified approach to Widgets on Phones, Watches and Cars

User interaction is shifting toward quick, glanceable moments—short bursts of information that keep users connected without needing to open the full app. To help you increase the reach of your app content, we are unifying the development experience across the Android ecosystem with Jetpack Glance. By using a consistent, Compose-based model, you can elevate the content most important to your users straight to the phone’s home screen, Wear Widgets (previously Tiles!), and cars with a familiar workflow.

In order to help users engage with your content and features, even outside your app, we are making widgets more expressive and adaptive with RemoteCompose. On Wear OS, RemoteCompose allows you to use the Compose tools you’re already comfortable with to define UI logic that renders natively on remote surfaces, ensuring that your glanceable experiences remain highly performant and responsive even on resource-constrained hardware. On mobile and cars, RemoteCompose is used as a new framework giving Widgets new expressive capabilities.

You can use Jetpack Glance (together with RemoteCompose on Wear) to deliver a cohesive user journey. Whether it’s viewing flight status on the car dashboard, checking a gate change on a watch, or managing a boarding pass from a phone widget, this shared approach maximizes your app’s presence while keeping your development effort focused and efficient.

Supercharge your media pipeline with a complete, production-ready toolkit

Android has become a world-class home for the entire media lifecycle, and we are simplifying the journey from the first capture to the final playback. By leveraging Jetpack CameraX and Media3, you can build professional-grade experiences that feel native across the entire ecosystem.

It starts with high-fidelity capture using the CameraXViewfinder Composable, which ensures your preview remains perfectly scaled and responsive on any form factor, including foldables and tablets. Use this to build adaptive capture experiences like a picture-in-picture view for multi-tasking, or that take advantage of modern features like high-frame-rate or slow-motion capture with CameraX v1.5.

The new Media3 AI Effects library will provide a unified interface for premium features like Image & Video Enhance, Magic Eraser, and Studio Sound. This allows you to focus on the creative intent while Media3 handles the heavy lifting of choosing the most efficient and reliable path for the device. Then, use the latest improvements in multi-asset editing with Media3 Transformer to composite your edited videos together!

Complete the pipeline with tools designed for professional-grade export and viewing, including:

CodecDB, which offers data-driven encoding recommendations tailored to specific chipsets, ensuring your exported videos maintain high visual quality with minimal noise or blurriness
Scrubbing Mode in ExoPlayer to provide the buttery-smooth seeking experience users expect from premium media apps
Enhanced Cast support with the new CastPlayer API in Media3

By unifying these technical pillars, you can build a cohesive, high-performance media journey that delivers both delight for your users and high ROI for your development team.

For more details, check out the premium Android experience YouTube playlist.

Top AI on Android updates for building intelligent experiences from Google I/O ‘26

2026-05-26T10:30:00.000-07:00

Posted by Jingyu Shi, Staff Developer Relations Engineer

At Google I/O 2026, we introduced Android’s shift from an operating system to an intelligence system. We also demonstrated how you can build intelligent experiences natively with the system and bring the power of Google’s AI into your apps. If you missed these updates, check out our quick recap video here:

1. Putting your apps at the center of the intelligence system

The Android OS already enables agents like Gemini to complete task automation, where it can navigate an app on the users behalf.

AppFunctions (Android MCP) provides you with more control over how your app integrates with the intelligence system. This new platform API and Jetpack library are currently available in experimental preview.

Android MCP: AppFunctions allows your application to act as an on-device Model Context Protocol (MCP) server. It means you seamlessly share your app's tools, services and data to the system and agents.

Streamlined Development: You can leverage the new skill to easily generate AppFunctions within your codebase.

Exploration and Testing: We’ve released a new test agent that allows you to experiment and debug your AppFunctions in a simulated agent environment.

Early Access Program: Want to be among the first apps to deploy app functions in production? Join our early access program today!

To see it in action, check out the live demo showcased during the What’s New in Android presentation.

2. On-Device Power with Gemini Nano 4 Preview

Last month, we launched Gemma 4, our state-of-the-art open models. You can already preview and prototype with the next generation of Gemini Nano (Nano 4) models with the AIcore developer preview. To make productionizing with Gemini Nano more reliable and performant, we are adding a few new features in ML Kit GenAI APIs:

Prototype to Production: Transition from prototyping in the AICore Developer Preview to building production-ready apps using the ML Kit GenAI Prompt API to leverage Gemini Nano 4 that’s launching in flagship devices later this year.

Structured Output: The upcoming Structured Output API will allow you to define object classes to be returned as outputs from Prompt API, ensuring reliable outputs in productionizing your intelligent features.

Prefix Caching: It optimizes your on-device inference performance with the prompt API. The new Prefix caching reduces inference time by storing and reusing the intermediate LLM state of processing a shared and recurring part of the prompt.

For highly customized or niche use cases, you can also use LiteRT-LM to bring your own fine-tuned small language model to Android.

3. Hybrid Inference & Agents

To help you build more advanced AI features like hybrid inference and explore building in-app agents, we’ve released new APIs, framework and guidances:

Firebase AI Logic Hybrid Inference: This new API provides the simple routing capability between on-device models and powerful cloud infrastructure. You can set explicit orchestration modes, such as PREFER_ON_DEVICE, PREFER_CLOUD, ONLY_ON_DEVICE, or ONLY_CLOUD, based on your need.

A2UI Jetpack Compose Renderer: The new A2UI library allows your agents to "speak UI". With the upcoming Jetpack Compose Renderer, you can automatically render these A2UI messages as native UI components.

ADK for Android: The first version of ADK for Android is available for experimentation. It allows you to build multi-agent workflows across both on-device and Cloud models while managing orchestration, context handling and sessions between agents.

From building with on-device models, exploring hybrid inference to building agents, you can see them in action in this talk:

Start Building Today

Whether you are experimenting with AppFunctions to prepare for the intelligence system, or looking to bring the power of Google’s AI within your own app, we’ve got you covered. Dive deeper into the code snippets, samples and comprehensive developer guides on the Android AI hub. For the full breakdown of what’s new, check out the official AI on Android at Google I/O 2026 playlist.

We are excited to see what you build!

17 Things to know for Android developers at Google I/O

2026-05-19T06:00:00.000-07:00

Posted by Matthew McCullough, VP, Product Management, Android Developer

Today at Google I/O, we announced the many ways we’re powering agentic workflows to increase your productivity and ensure your apps shine across the expanding Android ecosystem. Here’s a recap of 17 of our favorite announcements for Android developers; you can also see what was announced last week in The Android Show: I/O Edition. Stay tuned over the next two days as we dive into all of the topics in more detail!

Build High Quality Android Apps Using Agents

1: Android CLI: helping you build with any agent, LLM, and tool

Android CLI is now stable. It offers programmatic tools that allow any AI agent, including Claude Code, Codex, or Antigravity, to perform core Android tasks much more easily and efficiently. With today’s release, it also provides a bridge to tap directly into the "heavy-lifting" power of Android Studio to give you the production-ready polish needed for professional Android development. By leveraging the new android studio commands, developers can now grant their preferred agents the ability to perform semantic symbol resolution, analyze files for warnings, and even render Jetpack Compose previews. This release also enables official support for "Journeys" through new Android skills, which enables agents to execute end-to-end UI tests under your direction. Watch the developer keynote, and tune into the What’s New in Android tools talk for more information.

You can now easily install Android CLI for use with Google Antigravity 2.0.

2: Build production-ready apps with ease in Google AI Studio

Developers and creators can now build native Android apps, simply with a prompt in Google AI Studio. The apps are built with development best practices like Jetpack Compose, Kotlin, and APIs that leverage our recommended developer patterns. Google AI Studio enables developers to prototype, iterate via an embedded emulator, and deploy to physical devices without heavy local installations. Developers are then able to take those apps and share them to Android devices, as well as share them with others for testing through Google Play Console’s internal testing track. If a developer wants to prepare their app for a wider release, they’re able to take it to Android Studio for advanced debugging, testing, and UI polish. Watch the developer keynote, and tune into the What’s New in Android tools talk for more information.

Use the embedded Android Emulator to create Android apps in Google AI Studio

3: Accelerating AI coding assistance with Android Bench

Android Bench is our LLM leaderboard for Android development challenges. The goal is to accelerate model improvements, so you have more useful options for AI assistance. Many of you have been using open-weight models for AI assistance, so we’re now adding commonly used ones, such as Gemma 4, to the leaderboard, so you can see how LLMs that offer offline access and additional flexibility for power-users measure up. We're continuously working on increasing the difficulty of challenges we’re giving LLMs, to continue encouraging more useful improvements.

4: Convert iOS apps to Android with the Migration Assistant in Android Studio

The Migration Assistant in Android Studio is designed to port apps from platforms like iOS, React Native, or web frameworks to native Android. By simply selecting an existing project, developers can have the agent intelligently map features, convert assets like storyboards and SVGs, and implement Android best practices using Jetpack Compose and our recommended Jetpack libraries. This effectively transforms what used to be weeks of manual porting into a streamlined agentic workflow that only takes hours. We shared a preview of the incoming feature in the developer keynote.

A sneak peek of the Migration Assistant converting an iOS app into a native Android app

Building AI Into Your Apps

5: Building Intelligent Apps with generative AI

Generative AI enables you to create apps that are more intelligent, personalized, and agentic than ever before. This year, we introduced the latest advancements in on-device intelligence with a preview of Gemini Nano 4 for tasks like data extraction and summarization. We also expanded cloud capabilities via Firebase AI Logic, allowing developers to leverage Gemini models with robust grounding (including URL, Maps, and web search) to build smarter, more capable assistants. Furthermore, we unveiled our hybrid inference approach and the new Agent Development Kit (ADK) for Android, alongside communication protocols like AG-UI and A2UI that simplify the creation of autonomous, agentic experiences. To start integrating these powerful features, explore the developer documentation, and watch the technical deep dive session where we showcase all these technologies.

6: Experiment with AppFunctions today

AppFunctions is an Android platform API with an accompanying Jetpack library to simplify building Android MCP integrations. It empowers your apps to behave like on device MCP servers, contributing functions that act as tools for use by agents and assistants. AppFunctions integration with Gemini is currently in a private preview with trusted testers, and you can begin preparing your apps already. You can sign up for the Early Access Program and start experimenting using the API guidance, sample, and skill today.

The Future is Adaptive

7: Android is now Compose First; Views are now in maintenance mode.

Compose is our standard for UI development, and we are moving to a Compose-first approach for all future guidance and libraries. Building on five years of evolution, the latest releases deliver a more mature toolkit, from the highly customizable Styles API to refined shared element transitions and enhanced input support. These updates allow you to build beautiful, adaptive apps with less code and better performance. Learn more about what Compose-first means for Android Development in our blog post.

Build Android UI with Compose

8: Building seamless Android experiences across devices with Jetpack Compose

The Android ecosystem is now Adaptive by Default, moving fluidly across phones, foldables, tablets, cars, XR, and expanding usages with Googlebook and connected displays. With over 580 million large-screen devices, and users on multiple devices spending up to 14x more on apps, the investment in adaptive design presents a massive opportunity. Jetpack Compose is the definitive engine for this transition, offering core tools like our latest Jetpack Navigation 3 release, new experimental Grid and FlexBox layouts, enhanced non-touch input support, and CameraX for correct camera previews across any window size. Furthermore, new skills in Android Studio make updating your existing app to adopt these adaptive patterns easier than ever. Notability’s Android debut sets a new standard for premium productivity apps. Built with Jetpack Compose, Navigation 3, and Kotlin Multiplatform, it delivers an intuitive, adaptive experience across devices.

9: Create seamless experiences for Googlebook

Last week we announced Googlebook, a high-performance laptop that provides a large-screen canvas for your existing apps. Building with adaptive principles today helps ensure your app will work on Googlebook. Get started by reviewing relevant design guidance and developer guidelines for desktop experiences. Try out the new Desktop Emulator available in the Android Studio Canary to to test your apps for this form factor today.

New Desktop Android Emulator

10: Unified widget development experience with Jetpack Glance

Android 17 marks a shift toward a single, Compose-based development model for all widgets. By unifying the experience across mobile, Wear OS, and cars through Jetpack Glance, you can soon scale UI components across the ecosystem with a familiar workflow.

The breakthrough this year is the integration of RemoteCompose. On mobile and cars, it powers high-fidelity animations, while on Wear OS, it allows Wear Widgets (formerly Tiles) to render complex UI logic natively on remote surfaces. This ensures peak performance on low-power hardware while allowing a cohesive user journey—like checking a flight status on your car dashboard and seeing gate change updates on your wrist.

Four widgets are shown cycling through in the Android Auto interface. A clock, a contact card, Google Home favorites and a photo.

11: Expand your reach on the road with Android for Cars
To help you expand your reach when you build in-car experiences, we're making it easier to build once and deliver your apps to Android Auto and Android Automotive OS. With the latest releases of the Car App Library, you can build customized, distraction-optimized templated media apps for both platforms. We're introducing new components and template capabilities to give you increased flexibility and more options for laying out content. Parked experiences are expanding too, with immersive video playback coming to Android Auto for phones running Android 17. You can easily adapt your video apps for these parked experiences; apply now to the early access program to publish in these beta categories and learn more about the latest updates in our blog.

12: Accelerate your development with Android XR Developer Preview 4

Inspired by the innovative experiences you’ve built for the platform, we’re continuing to mature our tools with Developer Preview 4 of the Android XR SDK. A key milestone in this journey is the transition of our core libraries, XR Runtime, Jetpack SceneCore, and ARCore for Jetpack XR, moving to Beta soon to provide a more stable and performant foundation. We are also accelerating hardware access through the Android XR Developer Catalyst Program, where you can apply for XREAL’s Project Aura, audio glasses, or display glasses developer kits. Watch The latest in Android XR session or read our blog to see how these updates help you build experiences across the ecosystem.

Early preview of the Geospatial API in ARCore for Jetpack XR, enabling high-precision anchoring of digital content to real-world locations.

13: Android is your new home for professional-grade media experiences

Android 17 streamlines the entire media lifecycle with a production-ready toolkit. High-fidelity capture is now simplified with the CameraXViewfinder Composable, which handles complex scaling and responsiveness on foldables and tablets. For post-production, the new Media3 AI Effects library provides a single interface for premium features like Magic Eraser and Studio Sound, automatically optimizing for the device's hardware.

The pipeline is completed by CodecDB, offering chipset-specific encoding recommendations to eliminate export noise, and a new Scrubbing Mode in ExoPlayer for ultra-smooth seeking. Whether you’re compositing multi-asset edits with Media3 Transformer or using the streamlined CastPlayer API, these updates ensure a professional-grade experience with significantly less development overhead.

Low Light Boost and Magic Eraser in action

14: Increase app discovery and engagement on Google TV

Pointer remotes, which enable motion-controlled input, will be a future way for users to interact with Google TV as it unlocks faster user navigation. App developers can start declaring support for pointing input to ensure their apps are discoverable on future TVs with pointer remotes. Additionally, the Engage SDK, formerly known as the Video Discovery API, optimizes Resumption, Entitlements, and Recommendations across all Google TV form factors to boost app discovery and engagement. It’s a great time to start onboarding the Engage SDK now, since the legacy Watch Next API, which has been powering your continue watching 1.0 experience, will lose support in the 2nd half of 2027. Get all the details in our blog.

15: Performance: the foundation of a great app experience

To help developers navigate memory limits in Android 17, we've launched a suite of optimization tools. The R8 Configuration Analyzer identifies keep rules that are bloating your binary, while ProfilingManager and the integrated LeakCanary in Android Studio streamline memory leak detection. Furthermore, the new Android Performance Analyzer offers advanced AI integration for complex trace analysis and automated SQL query generation to pinpoint performance bottlenecks.

And The Latest on Driving Business Growth

16: What’s new in Google Play

Today's updates from Google Play help expand your reach and scale your business with less complexity. We’re redefining Play Store discovery with an immersive, short-form video format called Play Shorts, while expanding your audience beyond the store with app discovery in the Gemini app on Android and web. Plus, we’re introducing powerful new capabilities like agentic catalog management for seamless bulk price and SKU updates, and using Gemini models to enable Play Console to pre-populate store listings from imported documents—making global localization effortless.

Gemini will provide users with app suggestions during a search

17: And of course, Android 17

Android 17 includes new performance & system architecture improvements (in addition to app memory limits) like a lock-free MessageQueue and a GC with more frequent, less intensive young-generation collections to ensure system-wide stability and smoother UIs. The new contact picker and eyedropper API help minimize the use of sensitive permissions and unnecessary access to user data.

Review the behavior changes to make sure your app is ready for Android 17, including background audio hardening and SMS OTP protection. Get ready to target Android 17 (API 37) with changes such as mandatory large-screen resizability, certificate transparency by default, and restricted local network access. You can start testing today by enrolling your device in the Beta or using the latest 17.0 emulator images.

One more thing. the third beta of our Android 17 quarterly platform release (QPR1) just came out, and it contains a minor SDK release to support a few features that just couldn't wait for QPR2.

Check out all of the Android & Play Content at Google I/O

This was just a preview of some of the updates for Android developers at Google I/O. Tune into What’s New in Android for the latest news and announcements and follow Google I/O for much more over the following week!

Build native Android apps in Google AI Studio

2026-05-19T05:45:00.000-07:00

Posted by Emma-Louise Leavey, Group Product Manager and Mike Taylor-Cai, Product Manager

Starting today Google AI Studio can build entire Android apps for you in minutes from just a prompt. You don't need to install any software or configure any libraries, which significantly lowers the barrier to development. Whether you’re a seasoned developer looking to prototype at lightning speed or a creator building your first-ever mobile experience, you can now go from a single prompt to a high-quality, Kotlin-based Android app in AI Studio. You can easily install the app on your device, share it with others for testing, or send it to Android Studio for any further development.

The power of native Android

While AI has made it easy to generate web-based apps, people want more on their mobile devices. They expect the beautiful and usable modern app design and capabilities that come with native Android user experiences, built with the Kotlin programming language using Jetpack Compose, the official and recommended toolkit for Android development. Native Android apps bring the reliability of offline support, continuous background services, and the deep integration of hardware sensors like GPS, Bluetooth, and NFC. We've brought the technology that enables you to quickly create new projects with Gemini in Android Studio directly into the web-based AI Studio. Now, you get the best of both worlds: the ease of a prompt-based interface paired with the power of the Android SDK, all in your browser, no installation required.

A seamless, end-to-end workflow

We have streamlined the entire development lifecycle so you can focus on your idea:

1. Create your app and iterate in the cloud: Use the embedded Android Emulator directly in your browser to preview and interact with your app as it’s being built. No heavy SDKs to download, no local setup required.

Use the embedded Android Emulator to create and edit Android Apps right in the web browser

2. Install instantly: Connect your Android phone using a USB cable and install your app directly from AI Studio using the integrated Android Debug Bridge (adb).

Install the app on your Android device

3. Streamlined Publish to Google Play: Using your Google Play developer account, you can now publish your app directly from AI Studio for testing. AI Studio will automatically create your app record, package the bundle, and upload it to an internal testing track in Google Play Developer Console. Your app is available for you to install within minutes, and you can automatically update your app on your device as you develop it further in AI Studio.

Publish the app to an internal test track in Google Play

Seamless app development handoff

As you iterate on your app in AI Studio, you may find you need more advanced Android tools or support for a wider variety of Android device types. To move beyond the browser, you can seamlessly hand off your project to Android Studio by downloading a ZIP file or exporting it directly to GitHub.

Download zip file of Android app project files

When transitioning to a team environment or local development, you can leverage any IDE or agent you prefer. For a specialized experience, we recommend Gemini in Android Studio, which features models designed with Android in mind, or Antigravity, which integrates Android CLI commands into Google’s agentic development platform. This workflow makes building high-quality apps more accessible while giving you total flexibility in how you use AI to scale your project.

Start building today

To ensure a safe, high-quality ecosystem from day one, we have focused our initial release on specific capabilities including:

Personal utilities and simple social apps: You can rapidly prototype single or multi-screen apps, such as habit trackers, study quizzes, or event itineraries.
Hardware-enabled experiences: Because you are building native apps, you can leverage device features like the Camera, GPS/Location, Accelerometer and Bluetooth using the native Android APIs, letting you optimize hardware-level performance.
AI-powered experiences: You can create apps that feature Gemini API integrations, seamlessly embedding powerful AI capabilities directly into your mobile experience.

What’s Next?

We are moving fast to expand what’s possible for creators in AI Studio. Here is a sneak peek at what is coming soon:

Managing Google Play Test Tracks: Coming soon, we will be adding the ability to invite testers to try your app directly from AI Studio.
Firebase integrations: Out-of-the-box support for Firestore, Firebase Auth, Firebase App Check and other tooling critical for Android developers is coming soon.

Head over to Google AI Studio right now to start building. Here is some inspiration to get you started…

Turn your Google Pixel Watch into an aviation assistant

Prompt:

Build a small airplane "6-pack" instrument app for Google Pixel Watch. The 6 instruments should include attitude indicator, airspeed indicator, altimeter, turn coordinator, vertical speed indicator, and heading indicator. Use the Google Pixel Watch's sensors to power the instruments and display them clearly. Display one instrument at a time on the display. Swiping to the left or right should cycle through the instruments.

Interactive Harmonium app on Google Pixel Fold
Prompt: Build a Harmonium app for Pixel Fold devices, which plays like the instrument based on the hinge angle and touch gestures. The app should simulate the bellows and reeds accurately.

An Android app for guitarists to become better musicians by jamming to backing tracks

Prompt:

Build an Android guitar practice companion app that features a two-tab navigation system: 'Fretboard' and 'Library'.

The 'Fretboard' primary screen must contain an interactive guitar neck UI that visually maps out user-selected root notes, musical scales, and chords. Above the fretboard, implement a WebView-based YouTube player configured to play embedded videos inline. Additionally, include an AI generation feature that uses Retrofit to call Gemini Lyria 3 to create custom, 30-second backing tracks based on the user's currently selected key and scale. The generated audio files and their metadata must be saved locally using a database and displayed as a list in the 'Library' tab, where users can delete or play them.

Finally, implement a persistent, globally visible mini audio player at the bottom of the screen, complete with play/pause toggles, a progress slider for seeking, and timestamp text, allowing the user to seamlessly practice on the fretboard tab while listening to their tracks.

We are looking forward to seeing what you build next!

Explore this announcement and all Google I/O 2026 updates on io.google.

Increasing app discovery and engagement on Google TV

2026-05-19T05:00:00.000-07:00

Posted by Paul Lammertsma, Developer Relations Engineer

With over 300 million monthly active devices across Google TV and Android TV, it’s clear that the living room is a massive, distinct platform for apps to accelerate growth. Today, we’re excited to share Google TV features and developer tools designed to increase the discoverability of your content and prepare your app for future TV experiences.

Drive discovery and engagement with Gemini

Last year, we brought our AI voice assistant, Gemini, to our platform, so that people can easily find what to watch, learn something new on the big screen, and get everyday tasks done with just their voice.

Since launch, we’ve made improvements to how Gemini provides tailored responses to questions. Gemini shares a mix of visuals, videos, and text to help users find what they need, when they need it. For our streaming partners, Gemini is a helpful discovery engine—pulling from your app's metadata to surface your relevant content to viewers.

Declare support for pointing modality

The TV experience that we once knew is changing. Gemini is changing the way we discover and stream content with voice, but how we use the remote is evolving, too.

Pointer remotes bring motion-controlled input to the big screen, unlocking faster user navigation across the Google TV Home page and within content-heavy apps. To ensure your app is ready for this shift and provides a great experience for all users, now is the time to start thinking about pointing input. Here’s how to get started:

1. Adapt your TV app UI Library

You’ll need support for hover states, scrollable containers, and cursor clicks to enable pointer remote interactions for your app on Google TV. While implementation varies by UI stack, Jetpack Compose streamlines this transition, as most core components handle these multi-modal interactions natively out of the box.

Hover state: Every focusable element on your screen (buttons, movie posters, setting toggles) needs a clear visual feedback mechanism for a hover state. This is often subtler than a focus state but critical for feedback.
Scrollable containers: Pointer remotes will also have a small circular touchpad for scrolling. Users can use this touchpad to scroll up or down, or left or right in your app. Your app will need to respond to touch events to scroll.
Cursor clicks: Many TV apps today expect a simple D-pad OKAY button “click.” With a pointer remote, a user may “click” on an element that’s not the D-pad focus state, but is instead from a hovered state (similar to a mouse click).

2. Test pointing interactions with a mouse today

To see how your app handles hover, scroll, and clicks, simply connect a bluetooth mouse or wired mouse to your Google TV. Keep in mind that a mouse has more precise control, since users are closer to the screen and typically rest the mouse in a stable position. Pointer remotes can often be less precise, since users are sometimes 10 feet away from the screen, making rough gestures with the remote from their couch. As a TV designer or developer, you can mitigate this lack of input precision by having larger hover targets for elements.

3. Declare TV app support for pointer remotes on Google Play

Finally, tell Google Play that your TV app is designed to work with a pointer. This ensures that users with pointer remotes will be able to easily find, install, and interact with your app.

Within your AndroidManifest.xml, declare the meta-data tag, android.software.leanback.supports_touch. This tag informs the platform that your TV app “spatially supports touch,” since pointer remotes simulate touch events from a distance.

AndroidManifest.xml

<manifest ...>
    <!-- Signal whether the app is adaptive or built just for TV -->
    <uses-feature android:name="android.software.leanback" android:required="true|false" />

    <!-- Ensure the app can be installed on conventional TVs -->
    <uses-feature android:name="android.hardware.touchscreen" android:required="false" />

    <!-- Signal whether the app supports pointer remotes -->
    <meta-data android:name="android.software.leanback.supports_touch" android:value="true|false"/>

    <application ...>
        ...
    </application>
</manifest>

Tips:

The android.software.leanback feature declaration indicates that your app supports D-pad navigation and is intended for distribution only on TV devices via Google Play.
The new software attribute of android.software.leanback.supports_touch declares that in addition to D-pad, you have ensured that your TV app works well for pointer/cursor experiences via mouse (of today) and pointer remotes (of future).
If you haven't already, now is the time to adopt Jetpack Compose. Hover, scroll, and clicks are common input modalities that are supported on various form factors, and building your app with an adaptive UI framework enables code reusability and reduced maintenance.

Onboard the Engage SDK

The Engage SDK, formerly known as the Video Discovery API, optimizes Resumption, Entitlements, and Recommendations across all Google TV form factors to boost app discovery and engagement.

Resumption: Partners can easily display a user's paused video within the 'Continue Watching' row from the Home page.
Entitlements: The Engage SDK streamlines entitlement management, which matches app content to user eligibility. Users appreciate this because they can enjoy personalized recommendations without needing to manually update all their subscription details. This allows partners to connect with users across multiple discovery points on Google TV.
Recommendations: The Engage SDK even highlights personalized recommendations based on content that users watched inside apps.

It’s a great time to start onboarding the Engage SDK now, since the legacy Watch Next API, which has been powering your continue watching 1.0 experience, will lose support in the 2nd half of 2027. To get started, head to goo.gle/engage-tv to learn more.

We're excited to see how our latest Gemini experience and developer tools will optimize your discovery and drive user engagement on our platform.

Explore this announcement and all Google I/O 2026 updates on io.google.

Android CLI Now Stable 1.0: Accelerate developing for Android using any agent

2026-05-19T04:45:00.000-07:00

Posted by Simona Milanovic and Ben Trengrove, Developer Relations Engineers

As Android developers, you have many choices when it comes to the agents, tools, command-line interfaces (CLI), and LLMs you use for app development. Whether you use Gemini in Android Studio, Antigravity 2.0, Antigravity CLI, or third-party agents like Anthropic's Claude Code or OpenAI'sCodex, our mission remains the same: to ensure that high-quality Android development is possible everywhere.

At Google I/O ‘26, we shared the latest leaps forward in agentic development, and showcased some of the newest capabilities of Android CLI—now stable at version 1.0 and ready for all Android developers to use. From new skills to enabling agent access to powerful Android Studio capabilities, we’re giving your agents the right tools to build alongside you.

If you’re already using Android CLI and want to jump into using all the new features, just run android update. Otherwise, read further to learn more about how we’re making the agents you choose be better at building for Android.

Android development unlocked for Antigravity

Google Antigravity now includes an optional bundle of Android resources—including the Android CLI and skills—that you can install. You can either install the bundle during onboarding after installation, or later from the Settings > Customizations > Build With Google Plugins menu.

This provides Antigravity with all the powerful tools and knowledge of Android CLI, enabling it to perform the core tasks necessary for Android app development more easily and efficiently—from creating projects to deploying your app on a new Android virtual device.

You can now easily install Android CLI for use with Google Antigravity 2.0.

Unlocking Android Studio capabilities for any agent

Android CLI provides a lightweight interface for AI Agents to perform tasks and retrieve knowledge about Android development. However, there's benefits to specialization — Android Studio contains over a decade of Android expertise, built to handle even the most complex Android projects. This includes Android Studio's powerful static analysis engine, refactoring tools, dependency management, UI design and rendering libraries, and more. AI Agents can now tap into Android Studio's tools to gain many of these same capabilities.

Your agents can now use Android CLI to access powerful capabilities of Android Studio.

The latest version of Android CLI introduces the new android studio command. This enables the agent of your choice to leverage the deep, contextual capabilities of Android Studio to better understand and perform actions on an open Android project. By running Android Studio alongside your preferred agent with Android CLI, your agent’s tasks can more efficiently navigate the codebase to produce more precise code changes. And, when you use Android CLI to create and iterate on your project, transitioning to Android Studio is much easier, so that you can use the purpose built tools—such as, performance profilers, Compose Previews, and Android Device Streaming—to get that production-grade polish.

When you have a project open in the latest preview version of Android Studio Quail, you (or your agent) can run the following command to check whether Android CLI has a connection established with your open project:

$ android studio check
pid: 32942
version: Android Studio
Projects:
    READY     JetSet /Users/adarshf/AndroidStudioProjects/jetset-main

From there, the agents can use the android studio command to access powerful IDE tools to interact with projects more efficiently. Key commands include:

analyze-file: Analyzes a file for errors and warnings using the editor's built-in inspections.
find-declaration: Finds the exact definition site of a symbol (class, method, variable, field, constant, or Android resource/color) across the project using semantic resolution.
find-usages: Finds all references and declarations of a symbol (class, method, variable, or Android resource) across the entire project using semantic analysis.
render-compose-preview: Renders a Jetpack Compose UI Preview and returns a path to the image and UI hierarchy if successful.
version-lookup: Get the latest information about which versions for specified app dependencies are available in common repositories, such as the Google Maven repository. By providing a programmatic solution, dependency management is less tedious and much less prone to flakiness.
open-file: Opens a file directly in Android Studio. This is useful if the agent wants to direct your attention to view Compose Previews, performance traces, or other specific files in the IDE.

For example, agents can now run the following commands to render a Compose preview for a new layout for your Android app, and then open the previews in Android Studio for you to take advantage of seeing multiple Compose Previews side by side and make AI-assisted edits right from the IDE.

$ android studio find-declaration HotelDetailScreen
$ android studio analyze-file .../JetPacker/feature/detail/src/main/java/com/example/jetset/feature/detail/HotelDetailScreen.kt
$ android studio open-file feature/detail/src/main/java/com/example/jetset/feature/detail/HotelDetailScreen.kt

To learn more about how to use these commands, run android help. And, to make sure your agents understand how to work with this tool, make sure to update the Android CLI skill by running android init.

More ways to get started

To make integrating Android CLI into your environments as seamless as possible, we’re making it available in more ways. You can now download and install Android CLI using more package managers: apt-get, winget, and homebrew. For example, you can run the following to install Android CLI using winget:

winget install -e --id Google.AndroidCLI

We’ve also updated the installation to a user-local directory, by default. You can find the commands for all supported operating systems plus additional download options on the Android CLI page.

Support for Journeys

Journeys are natural language descriptions of core user experiences.

(sped up) An agent running a Journey it generated for an app.

Agents can run these journeys using the Android CLI to navigate your app exactly like a user would. This unlocks entirely new ways to test, validate, or collect data across the critical experiences of your app, all driven by natural language and executed by your agent.

Expanding Android skills

To help models better understand and execute specific patterns that follow our best practices, we are continuing to expand our library of Android skills. We’re shipping new skills that make Android development everywhere more capable, efficient, and productive:

Display Glasses and Jetpack Compose Glimmer for XR: Provides guidelines for developing projected applications for Android Display Glasses using the Jetpack Compose Glimmer UI toolkit.
Migration to CameraX: Helps you migrate legacy Android camera implementations (Camera1 or raw Camera2 APIs) to CameraX.
Perfetto SQL: Translates natural language data prompts into Perfetto SQL queries and executes them against a local trace file.
Adaptive UI: Instructions to make or update an app's UI so that it adapts to different Android devices
Testing setup: Creates a basic testing strategy.
Styles: Helps with adoption of the new Jetpack Compose Style API for new components, and supports migration to Styles API.
AppFunctions: Analyzes Android codebases to recommend and implement new AppFunctions, and refines KDoc documentation for Model Context Protocol optimization.

You can add these new skills to your workflow directly from the command line. To help your agents understand and use Android CLI right away, you can initialize your environment and install the base android-cli skill by running:

android init

From there, you can browse and set up your agent workflow by searching for the exact capabilities your agent needs:

android skills list

Once you've found the right skill, install it to your environment by running:

android skills add –skill=<skill-name>

Get started today

To download the stable 1.0 release of the Android CLI, explore the new tools, and browse the complete documentation, head over to d.android.com/tools/agents today! Also, make sure you update to the latest preview version of Android Studio to unlock the latest features that Android CLI offers. We can't wait to see what you build with Android CLI 1.0 and how these new features supercharge your daily workflows. Join our vibrant community on LinkedIn, Medium, YouTube, or X and share your feedback.

Explore this announcement and all Google I/O 2026 updates on io.google.

Build for the future with the Android XR Developer Catalyst Program — Apply now!

2026-05-19T04:15:00.000-07:00

Posted by Android XR Team

The Android XR ecosystem is expanding, and we’re committed to supporting developers who will build its next great experiences. Today, we’re opening applications for the Android XR Developer Catalyst Program, a dedicated initiative to accelerate the development of Android XR apps ready to launch within the next year.

This program is designed to provide the resources, hardware, and grants to help you build and scale innovative experiences across wired XR glasses, like XREAL’s Project Aura, and intelligent eyewear (audio and display glasses). We are especially interested in seeing innovative experiences across media, gaming, productivity, and health, but we welcome any unique use case that helps users expand what's possible.

Why join the catalyst program?

We want to help developers navigate common barriers to entry for XR development by providing:

Development Kits: Get early access to hardware development kits for wired XR glasses (XREAL’s Project Aura) and / or intelligent eyewear (audio and display glasses).
Technical support: Gain access to specialized technical resources and support forums specifically designed to help you prepare your app for Google Play.
Grant Opportunities: Submit a request and you may be eligible to receive a non-recoupable grant to accelerate your development.

Ready to start building?

Applications are open to developers looking to publish apps for the Android XR ecosystem in the next 6-12 months. You can build with Kotlin and the Jetpack XR SDK, or with Unity, Unreal Engine or Godot. If you need a spark of inspiration, you can check out existing XR Experiments and Samples to see how you can use the SDK for everything from spatial music to navigation.

Once you have your concept ready, be sure to submit your application by June 30th by 11:59PM PDT. We can’t wait to see what you build.

Start Your Application

Explore this announcement and all Google I/O 2026 updates on io.google.

Adaptive development for the expanding Android ecosystem

2026-05-19T04:00:00.000-07:00

Posted Fahd Imtiaz, Senior Product Manager, Adaptive Apps

With the release of Android 17, we are transitioning into an adaptive first development standard. Your users no longer rely on a single form factor; they transition between phones, foldables, tablets, laptops, automotive displays, and immersive XR environments throughout their day.

Now, with over 580 million large screen devices in the hands of users, adaptive is no longer just a technical goal. It’s a massive opportunity to reach highly engaged users. To thrive in this multi-device ecosystem, your app must be resilient, responsive, and ready for virtually any surface.

The multi-device opportunity

The Android device universe is now a multi device reality. Users are buying into entire ecosystems, moving from handhelds to foldables, tablets, and cars. And the data is clear: users with multiple devices often spend more than users with only a phone.

Drive higher revenue: Multi-device users spend 9x more on average than phone only users. On foldables, that engagement multiplier can reach 14x. (Source: Google Internal Data, 2026)
Capture high-value segments: Large-screen users (tablets, foldables, and Chromebooks) typically spend roughly 5x more than phone-only users.

To help amplify your reach with these users, we've rolled out a new badge in Google Play. Apps meeting adaptive quality standards now earn an "Optimized for large screens" badge, making it easier for users to discover high quality experiences.

Latest in adaptive Android development from Google I/O

Android 17, new Jetpack updates and advanced tools help you build apps that feel native across diverse surfaces, from pocket-sized foldables to Googlebooks.

Adaptive by default: Android 17 updates

In Android 16, we introduced significant changes to orientation and resizability APIs to facilitate adaptive behavior, while providing a temporary opt-out to help you make the transition. Android 17 (API level 37) sets a new quality baseline by removing that developer opt-out for orientation and resizability restrictions on large screen devices (sw > 600 dp). When you target API level 37, your app must be capable of adapting to a variety of display sizes. This helps your app deliver an experience that matches the users’ expectations.

Tip: You can start testing these behaviors by enabling the UNIVERSAL_RESIZABLE_BY_DEFAULT flag in App Compatibility Changes under Developer Options under SDK 36.

Your app on even more surfaces

In addition to your mobile app running on large screens devices including foldables, tablets, Chromebooks and XR, we are also expanding the Android surface area for your mobile apps:

Connected Displays: Now in stable as of Android 16 QPR3, Connected Displays support enables supported Pixel and Samsung mobile devices to transform into a desktop environment via external display support.
Automotive & TV: With the Car Ready Mobile Apps program and enhanced pointer support for Android TV, your adaptive app can now benefit from engagement on the infotainment system and the living room with ease.

Googlebook: Evolving desktop computing

Talking about more surfaces, we’re evolving our work in the desktop space with Googlebook, the next generation of ChromeOS. Built with parts of the Android stack, we are enabling your apps to achieve a "laptop-class" feel with native level performance.

Building with adaptive principles today helps ensure your app is ready for this new generation of high performance hardware.

To help you prepare for this new generation of devices, we’ve released comprehensive new documentation including comprehensive design guidance and developer guidelines. Built on the principles of adaptive, these guidelines offer a playbook for transitioning your mobile apps to offer a premium desktop class experience.

Try out the new Desktop Emulator, available now in the Android Studio Canary to get started today.

Building adaptive layouts with Jetpack Compose

We are now Compose first and Jetpack Compose is our recommended way to build modern, adaptive UIs to help you manage layout complexity efficiently.

New layout primitives: We’re introducing Grid and FlexBox layouts, bringing powerful, CSS-inspired capabilities to Compose for both 1D and 2D layouts.
Navigation 3: The 1.1 release for compose-navigation3 introduces Scene Decorators, allowing you to wrap your screens with other content, such as bars, rails and dialogs.
MediaQuery API: The new experimental MediaQuery API provides observable device UI capabilities, such as window size and pointer precision, that allow you to adapt and optimize your app's UI for the current device configuration.
Styles API: Dynamically evolve the visual properties of your app using the new state-based experimental Styles API.

Beyond layouts: non-touch input

Adaptive app quality goes beyond window dimensions, including handling non-touch input paradigms e.g. keyboard, trackpad, mouse, stylus that are primary input methods on large screens.

Trackpad support: Compose 1.11 now brings trackpad support on par with mouse, and provides new APIs to automate non-touch input testing including TrackpadInjectionScope and performTrackpadInput.
Focus indicators: Enhance accessibility with built-in support for standard focus rings in Compose.

AI-Powered developer tools

Android Studio and Android CLI are evolving to help you architect adaptive apps faster than ever.

Android Skills: These modular AI instructions are designed to assist any LLM through complex architectural tasks, including helping you with View-to-Compose migrations, implementing adaptive layouts, Navigation 2 to Navigation 3 transformation, and migrating off of legacy camera libraries to CameraX. Get started with these latest skills on the Android Skills Github repo and via Android CLI.
New Project Agent: Available in Android Studio Panda 2, this agent initializes new projects with adaptive best practices by default.

For developers working with cross-platform frameworks, we continue to provide full support for Web, Qt, and Unity. Whether you are building from scratch or modernizing a legacy codebase, these tools are designed to meet your users exactly where they are.

We’re excited to see how you bring these new adaptive capabilities to your apps. By moving to an adaptive first approach, you’re not just reaching more users but you’re delivering the seamless, high quality experiences they expect across the entire Android device landscape.

Get started with adaptive development and start shaping the future of your apps.

Explore this announcement and all Google I/O 2026 updates on io.google.

Updates to the Android XR SDK: Introducing Developer Preview 4

2026-05-19T03:45:00.000-07:00

Posted by Stevan Silva, Group Product Manager and Amy Zeppenfeld, Developer Relations Engineer

Today we're excited to launch Developer Preview 4 of the Android XR SDK, continuing our focus on unifying cross-device development for headsets, wired XR glasses, and intelligent eyewear. To keep our platform intuitive, we are adopting more descriptive naming for our form factors, where AI glasses are now audio glasses and display AI glasses are now display glasses, with these changes appearing in our documentation starting today.

This release is packed with updates that help you build incredible experiences for XR devices, enable deeper immersive experiences on XR headsets, and streamline the path for creating augmented experiences on audio and display glasses. Also, our core libraries—including XR Runtime, Jetpack SceneCore, and ARCore for Jetpack XR— will be officially moving to Beta soon!

To give you early access to hardware and resources for building immersive and augmented experiences on upcoming devices—like display and audio glasses and XREAL’s Project Aura — we’re announcing the Android XR Developer Catalyst Program. Learn more and start your application today.

Building Augmented Experiences for Audio and Display Glasses

Starting out with our libraries for augmented experiences, Developer Preview 4 introduces new APIs that help you create and test your apps.

Jetpack Projected: Device Availability and ProjectedTestRule APIs

The Jetpack Projected library helps bridge app experiences from the phone to the user's field of view. We've added the Device Availability API, which consolidates wear state and connectivity signals into standard Android Lifecycle.State values. This lets you adjust your applications behavior based on whether the device is worn.

val xrDevice = XrDevice.getCurrentDevice(projectedContext)

// Observe the device lifecycle flow
xrDevice.getLifecycle().currentStateFlow
    .collect { state ->
        when (state) {
            Lifecycle.State.STARTED -> { /* Device is available (worn) */ }
            Lifecycle.State.CREATED -> { /* Device is unavailable (not worn) */ }
            Lifecycle.State.DESTROYED -> { /* Device is DISCONNECTED */ }
        }
    }

To simplify testing, the new ProjectedTestRule API in the projected-testing artifact automates the setup of projected test environments. This helps you write clean, reliable unit tests without the boilerplate code.

// from the 'androidx.xr.projected:projected-testing:1.0.0-alpha07' artifact
@get:Rule
val projectedTestRule = ProjectedTestRule()

@Test
fun testProjectedContextInitialization() {
    // by default, ProjectedTestRule automatically creates and connects
    // a projected device before each test
    val projectedContext = ProjectedContext.createProjectedDeviceContext(context)

    // assert the projected context is successfully initialized
    assertThat(projectedContext).isNotNull()
}

Jetpack Compose Glimmer: Google Sans Flex and new components

Our UI library for display glasses, Jetpack Compose Glimmer, now includes Google Sans Flex for improved legibility on optical see-through displays. We’ve also added several interactive components:

Stacks: Designed for touchpad-optimized groups, showing one item at a time.
Title Chips: Provides categorization and context for content cards.

Building Immersive Experiences for XR Headsets and Wired XR Glasses

If you're looking to build fully immersive experiences for XR Headsets and wired XR Glasses, we have several big updates.

Beta Transition & Modern Architecture

XR Runtime, Jetpack SceneCore, and the ARCore for Jetpack XR perception features (Depth Maps, Eye/Hand Tracking, Hit Testing, and Spatial Anchors) will soon move to Beta, so we’ve streamlined the Jetpack XR APIs. We've removed legacy Guava and RxJava3 packages in favor of a modern, Kotlin-first architecture.

Jetpack SceneCore: glTF and Custom Meshes

We're expanding 3D model capabilities by adding the ability to fine tune 3D models and access specific nodes with a 3D model. Using GltfModelNode, you can modify properties like pose, materials, and textures, and even run animations for specific nodes.

// Create a new PBR material
pbrMaterial = KhronosPbrMaterial.create(
    session = xrSession,
    alphaMode = AlphaMode.OPAQUE
)

// Load a texture.
val texture = Texture.create(
    session = xrSession,
    path = Path("textures/texture_name.png")
)

// Apply the texture and configure occlusion
pbrMaterial.setOcclusionTexture(
    texture = texture,
    strength = 0.5f
)

// Access the hierarchy of nodes
val entityNodes = entity.nodes

// Find the specific node
val myEntityNode = entityNodes.find { it.name == "node_name" }

// Apply the PBR material override
myEntityNode?.setMaterialOverride(
   material = newMaterial
)

We're also bringing Custom Meshes to SceneCore. Custom meshes let you build geometry on the fly programmatically, which is ideal for creating custom 3D models. This feature will launch as experimental, so try it out and let us know what you think!

// Create the meshval roadMesh =
    CustomMesh.BuilderFromMeshData(session, roadVertexLayout)
        .addVertexData(ByteBufferRegion(roadDataBuffer, 0, vertexDataSize))
        .setIndexData(ByteBufferRegion(roadDataBuffer, vertexDataSize, indexDataSize))
        .setTopology(MeshSubsetTopology.TRIANGLES)
        .build()

// Define the material
val roadMaterial = KhronosPbrMaterial.create(session, AlphaMode.OPAQUE)

// Instantiate the entity using the custom mesh and material
val roadEntity =
    MeshEntity.create(
        session,
        roadMesh,
        listOf(roadMaterial),
        pose = roadPose,)

Compose for XR: Native glTF Support

We now have native glTF support directly in Compose for XR with SpatialGltfModel. Use this along with SpatialGltfModelState to access nodes and animations in the glTF model, or use them to add textures and materials to your 3D models.

   val myGltfModelState = rememberSpatialGltfModelState(
        source = SpatialGltfModelSource.fromPath(
            Paths.get("models/my_animated_model.glb")
        )
    )

    val myGltfAnimation =
        myGltfModelState.animations.find { it.name == "animation_name" }

    DisposableEffect(myGltfAnimation) {
        myGltfAnimation?.loop()

        onDispose {
            myGltfAnimation?.stop()
        }
    }

    SpatialGltfModel(state = myGltfModelState, modifier = modifier)

ARCore for Jetpack XR: Geospatial API Preview for Wired XR Glasses

We’re also providing an early preview of the Geospatial API for wired XR Glasses in ARCore for Jetpack XR. This update enables high-precision anchoring of digital content tied to real-world locations in over 87 countries.

By combining ARCore’s Visual Positioning System (VPS) with the reasoning and audio capabilities of the Gemini Live API, you can create contextually aware experiences that understand both the location and position of your user. Imagine building an immersive, AI-guided walking tour that provides real-time audio descriptions of nearby places, seamlessly blending digital information with the physical environment.

Start Building the Future Today

It's an amazing time to develop for Android XR. With the Jetpack XR SDK moving to Beta soon and a robust set of new tools at your fingertips, explore each of the following areas to get your app's experiences ready for XR!

Read the documentation, explore the samples, and check out the XR experiments

Head to the official Android Developer site for full technical guides, API reference, and instructions on setting up the new emulator. Get inspired with our samples and experiments. See how we've used these APIs to build immersive spatial layouts, load 3D models, explore spatial audio, and more!

Check out what's new for game engines

We've added official support for Unreal Engine and Godot, and we've launched two new tools to accelerate development for Android XR with Unity and the Android XR Interaction Framework. And, based on your feedback, we are introducing the Android XR Engine Hub to allow you to run your experiences directly from your preferred engine,

Read the blog post about what's new for game engines

Apply for the Android XR Developer Catalyst Program

Don’t miss your chance to build for the latest Android XR hardware. Apply today for the opportunity to gain access to pre-release hardware, including our audio and display glasses prototype and XREAL’s Project Aura.

Learn more and apply today.

We look forward to seeing the amazing XR experiences you build as we move toward the launch of more Android XR devices later this year!

Explore this announcement and all Google I/O 2026 updates on io.google.

Android XR Updates for Unity, Unreal, and Godot

2026-05-19T03:30:00.000-07:00

Posted by Luke Hopkins, Android Developer Relations Engineer for OpenXR & Ryan Bartley, Android XR Product Manager

Today, we are excited to announce that official support for Unreal Engine and Godot has arrived for Android XR. Alongside these engine expansions, we are also launching new tools designed to boost your productivity and enable new XR capabilities: the Android XR Engine Hub and the Android XR Interaction Framework.

Android XR Engine Hub

The Android XR Engine Hub is currently available for Windows and is your mission control for development. It unifies your workflow across Unity, Unreal Engine, and Godot by serving as a high-speed bridge that streams device-created perception data straight from your device into the engine of your choice.

Real-Time Streaming via OpenXR

The Hub bridges the gap between desktop power and mobile sensor data. Instead of requiring a full build to see how your app reacts to the world, the Hub streams OpenXR extensions from the physical Android XR device directly to your Windows machine.

This means you can iterate on complex interactions in "Play Mode" while receiving live, high-fidelity data from the headset’s sensors. Without this streaming capability, testing even a minor change to eye-tracking or spatial mapping would require a full APK export and installation.

The Hub enables low-latency testing for the following streamed extensions:

Core & Interaction Support

XR_EXT_hand_tracking & hand_interaction: Streams 26-point hand meshes and joint data for immediate interaction testing.
XR_EXT_eye_gaze_interaction: Virtualizes eye-gaze data to test UI and foveated logic on your PC.
XR_EXT_palm_pose & XR_EXT_uuid: Real-time precision tracking and persistent object ID streaming.

Android XR Vendor Extensions

Eye & Face Tracking (XR_ANDROID): Stream expressive avatar data to your editor to refine social presence without building.
Passthrough & Trackables: Access live environmental understanding—like plane detection and hit testing—directly within the engine's viewport.

By virtualizing the device's hardware capabilities and streaming them over a low-latency desktop bridge, the Android XR Engine Hub allows for game engine developers to quickly iterate.

Download the Hub:
Get the Android XR Engine Hub for Windows
Learn more about Direct Preview

Expanding Game Engine Support

Through our commitments to OpenXR standards, we are ensuring that whether you are a veteran studio or an indie developer, you have best-in-class tools to help bring your creative vision to life.

Unreal Engine

Unreal Engine support is now available in developer preview, targeting version 5.6.1. This integration is built directly on using OpenXR with the support for AndroidXR vendor specific API using the Android XR vendor plugin for Unreal, you can access platform-specific extensions for advanced hand tracking, face tracking, and scene understanding (like plane detection and depth) whilst making use of Unreal blueprints or C++ support.

Get Started with Unreal:

Godot

In partnership with the Godot Foundation and W4 Games, we are bringing official Godot support to Android XR for Godot 4.6.2 and higher.

We are already seeing incredible momentum from W4 as they have ported experiences like MoAT and Expedition to Blobotopia that are already live on Google Play, proving that Godot is ready for production-grade spatial experiences today.

To unlock the full potential of the platform, use the Godot OpenXR Vendors plugin 5.1, which provides the necessary Android XR vendor extensions for features like scene meshing, dynamic resolution, light estimation and much more. We're collaborating with Godot to optimize the OpenXR implementation for the Android XR power profile and input standards.

Get Started with Godot:

Unity

The Unity OpenXR: Android XR 1.13 package is now available for Unity 6.5 Beta. Unity has expanded Application SpaceWarp support to include both uGUI and TextMeshPro. Keep an eye out for the general release of Unity 6.5 and more platform enhancements arriving this summer.

Android XR Extensions v1.3.1 for Unity

Everything else you need for comprehensive platform integration is available in our latest Android XR Extensions release:

Spatial API Support: You can now manage the android.software.xr.api.SPATIAL manifest tag directly through XRSessionFeature settings, making it easier than ever to define your app's Spatial API requirements and target levels.
Fine Eye Face Tracking: A new Fine Eye Poses feature provides high-precision eye poses using the TryGetFineEyePoses extension method.
Direct Preview Support: The Android XR Streaming feature enables Direct Preview support within Unity Editor's PlayMode (Windows only).

Note: Android XR (Extensions): Hand Mesh has been removed; you should now use the unified Hand Mesh Data within the extensions package.

Android XR Interaction Framework for Unity

The Android XR Interaction Framework (AXRIF) is now available in developer preview. AXRIF is an unstyled, opinionated input toolkit that abstracts the complex logic required to build interfaces that are consistent with Android XR system interactions.

Instead of focusing on UI visuals, AXRIF prioritizes the underlying mechanics of the Android XR user experience. At its core is the same Transition Manager that powers the system's rich multimodal inputs, enabling state switching between 6DoF controllers, 3D mouse, hand tracking, and eye gaze. By leveraging this framework, developers can significantly reduce the implementation burden required to bring Android XR's full complement of robust interactions to their apps.

At launch, the framework provides three core capabilities:

Automated Multimodal Input Transitions: The framework manages the state machine for switching between input modalities. For example, it handles the transition logic when a user moves from gaze-targeting an object to directly touching it, simplifying simultaneous support for hands, controllers, and mice.
Gaze-Assisted Gesture Interaction: AXRIF combines gaze vector targeting with hand gesture recognition (such as pinch-to-select) for precise distant interaction, matching the system's default behavior.
Physics-Based 2D UI Interaction: The framework maps high-fidelity hand tracking to 2D plane interactions, enabling intuitive poke and swipe gestures on floating panels while respecting physical boundary constraints.

By adopting AXRIF, your app inherits the platform's native interaction model, ensuring your app feels consistent with the rest of the OS.

Explore the Toolkit:
Interaction Framework Documentation
Download the Unity Package

Get Started Today:

There has never been a better time to dive into Android XR development. With support across Unity, Unreal, and Godot, the platform is ready for your creative vision, no matter which engine you call home. Explore our official engine partners to get started:

Explore this announcement and all Google I/O 2026 updates on io.google.

Introducing Android Performance Analyzer : The Next Evolution in Profiling for Android

2026-05-19T03:00:00.000-07:00

By Simon Cooke, Developer Relations Engineer (X) and Mayank Jain, Product Manager (X)

What is Android Performance Analyzer?

Android Performance Analyzer (APA) is Android’s new profiler and performance analysis tool for the Android mobile ecosystem.

APA is intended as a profiling tool for any developer building for Android who needs to make their app or game run better and faster. It is helpful for all performance-minded engineers, especially those using Vulkan in their game engines who want to squeeze every bit of performance out of their code.

APA aims to be the tool that helps you optimize apps and games for all modern Android devices and simplifies your most common workflows, with a simple interface that anyone on your team can quickly learn and be productive.

Available today in open beta is APA’s new System Profiler that you can use to analyze the CPU, GPU, Memory, and power usage of your app or game - and see how it interacts with system behavior.

Developed in collaboration with Samsung Austin Research Center (SARC) and LunarG, APA relies on Perfetto for system tracing and its upcoming frame profiling/debugging features (stay tuned!) are powered by LunarG’s GFXReconstruct technology for graphics capture and replay.

Devices running Android 12+ will provide the best experience for capturing system-wide performance and GPU counters and render stages.

We’re also working across the Android ecosystem with our esteemed industry partners to bring more profiling & optimization related data into APA.

Android Performance Analyzer

How to get Android Performance Analyzer

APA ships in two different forms, and you can download whichever one suits your needs best

As a lightweight standalone desktop app.
And also integrated directly into Android Studio as the updated System Trace viewer (available in Panda 4 canary builds and later).

The standalone desktop app is intended to be used without an Android Studio project or Gradle build - and provides deep customization of recording configuration, built-in Vulkan layers for graphics analysis, deep inspection of GPU counters and much more.

APA is also cross-platform: works natively on Windows, MacOS, and Linux.

Features in this release

Basic profiling functionality

Capturing your profile data

You don’t always want to take a capture immediately at application or game launch. APA allows you to choose, and capture traces from your device at launch or triggered manually. The user interface allows you to select which GPU counters and other data is captured in a trace - and if you have more complex needs, you can provide your own custom Perfetto configuration.

Deep-Dive System Analysis

With APA, you can analyze the entire system’s behavior in one view. For example, you can easily examine CPU cores - both their frequencies and the work scheduled on them or inspect processes & their thread activity.

For graphics-heavy apps, APA provides GPU performance counter data across hardware from Qualcomm, Arm, Imagination, and Samsung. You can even track battery and power consumption to see the impact of your code on power consumption.

To understand exactly where frames are spending time, SurfaceFlinger events provide deep visibility into the rendering and display composition pipeline, from initial code acquisition to final display. And with the new screenshots feature, you can visually scrub through to easily find the exact areas where you want to focus your attention.

You can open existing Perfetto traces, zoom through the timeline for precise detail, and use rulers to measure the duration of work and events. APA also lets you bookmark and annotate interesting findings, and you can pin critical tracks to the top of your screen to keep your focus exactly where it needs to be as you optimize.

Workflow features

Tabbed interface and split windows: You can open multiple traces in side-by-side tabs or split a single trace into two windows to compare different regions of the same trace simultaneously.

Tabbed interface showing two traces side-by-side.

Project-based workflow: APA uses a project model that allows you to keep track of multiple traces from the project sidebar. This is especially useful for gathering the results of A/B testing and longitudinal tests, and keeping all of your results together for comparison & quick access purposes.

The new project window helps you manage multiple traces.

Navigate visually using screenshots: APA lets you capture screenshots during a trace (without any noticeable performance overhead) to home in on areas where you saw something affect performance by scrubbing through the timeline. Or even just to get your bearings.

Scrubbing the timeline using screenshots for navigation (trace taken from NetMarble’s Seven Deadly Sins: Origin).

Persistent view customizations: When you pin or vertically resize tracks, we save those customizations so that they persist the next time you open the trace.

Analysis tools & new skills for AI agents

Vulkan debug trace markers for render passes: We support Vulkan debug annotations for render passes - which allow you to view Render Pass names you set from your codebase directly in the tracks and slices shown in APA.

This immensely helps you to make logical connections between the workloads you see in the profiler to where they are originating from in your codebase.

Vulkan Debug Markers allow you to keep track of what kind of work is being performed in your trace.

Use AI to build SQL queries for custom analysis work: APA supports trace analysis via SQL queries and ships with a new Perfetto SQL skill for use with your favorite AI agents. This makes it easier to build queries without needing to remember Perfetto SQL schemas or the SQL syntax.

AI helps you build SQL queries to perform custom analysis on traces.

Ask Gemini to analyze traces for you: We’ve also added another Perfetto Analysis skill to answer high-level questions for you - like “Why is my app startup slow?” - helping you to find starting points when analyzing complex traces, using your favorite AI agent to pinpoint the answers.

Agentic trace analysis in Android Performance Analyzer

FPS and Frame Duration times : You can review the FPS and Frame duration time at a glance in the tracks to correlate it with other activity happening in your trace.

FPS and Frame timing tracks in APA

Speed & robustness improvements

Speed and robustness improvements: Rendering a trace is now typically 6x to 26x faster than Android GPU Inspector, and APA is significantly more stable when working with large traces.

Case studies

We’ve worked with our early access partners to create detailed case studies showcasing how APA could be used to improve performance for Vulkan apps & games.

The Forge Interactive

The Forge used Android Performance Analyzer to identify the need to batch calls to vkCmdBindDescriptorSets, which reduced CPU setup costs by ~50%. This, in turn, slowed heat production on their device by 2-3x, leading to longer session times. They also used APA to identify opportunities to move font and UI rendering work over to the GPU, improving scalability.

You can read the full case study from The Forge here.

Note: This case study demonstrates how to use custom SQL queries in the profiler to generate a total rendering cost metric.

The Forge case study showing frames presented consistently at a stable 30 FPS using APA

NetMarble – Seven Deadly Sins: Origin

Netmarble used Android Performance Analyzer to fine-tune their game Seven Deadly Sins: Origin, focusing particularly on improving performance by making changes to the precision of their shaders, and exploring the impact of upscaling on the performance of their renderer.

This allowed them to reduce the GPU cost of rendering some scenes by up to 90%.

Read the full NetMarble case study here.

Netmarble validating pre- and post-optimization performance changes using APA for their game: Seven Deadly Sins: Origin

Profiling model complexity in Google’s Filament engine

Google has been improving the Filament glTF Viewer, our physically-based rendering engine.

We spent some time digging into the viewer with a variety of scenes, and showed how to use Android Performance Analyzer to identify scenes that are too complex for the GPU, and how to trim them down to hit a target 60FPS, by improving texture compression and optimizing geometry. Memory consumption was also reduced in this process.

You can read our exploration of Filament here.

Screenshot showing GPU wait time was reduced from 25ms to 20ms by introducing dynamic resolution and measuring it through APA

Try out the Android Performance Analyzer Beta today!

The Android Performance Analyzer is available for you to try out and use today:

Standalone profiler: https://developer.android.com/android-performance-analyzer
Android Studio Canary Build (Panda 4 canary builds and later): https://developer.android.com/studio/preview

This is beta software, which means that you might run into an occasional bug – please report it to us if you find any (Help Menu > Submit a bug report).

We’re excited to see how you use the new Android Performance Analyzer, and how it will help your project’s performance and reliability.

Explore this announcement and all Google I/O 2026 updates on io.google.

Android Studio I/O Edition: What’s new in Android Developer tools

2026-05-19T02:30:00.000-07:00

Posted by Matthew Warner, Google Product Manager

This year at Google I/O we are going beyond iterative changes, towards a fundamental shift in how apps are built. Our newest tools are built for the agentic era with features that boost productivity for you as an Android developer AND supercharge the AI agents you deploy in your codebase. So, whether you are building exclusively with AI or you prefer being the architect of every line of code, our tools will keep you ahead of the curve.

As we move from "AI-assisted" to "Agentic" development, we’re making it easier than ever to turn a spark of an idea into a high-quality production app with significantly less developer effort.

So what’s new with Android developer tools? We will cover 3 main areas in this blog:

Let your agent handle it: Whatever development task you are working on, the Android Studio agent can help: from planning the app architecture and design, to writing code, to unit testing and bug fixing.
Any AI provider, anywhere you build: In Android Studio, you can use any model and we even help guide you to the best performing ones. Choose any of the top remote models from Google, Anthropic, OpenAI, or if you need to run locally - Gemma 4 is our most capable and efficient local model! And with Android CLI, you can build Android apps faster and easier using the agents and developer environments of your choice.
As always, performance and quality remain top priorities: We continue to invest in the Android developer tools you love: from the Emulator, to Profilers, performance analyzers, and more!

1: Let your agent handle it

Agent skills

Android Studio now supports Agent Skills, modular instruction sets that ground LLMs in specialized workflows and domain-specific knowledge. By adding skills to your project, you can teach the agent to follow specific best practices, architecture patterns, or library workflows. This enables more accurate, context-aware code generation and automated skill activation for an appropriate task, ensuring the agent acts as an expert. We’ve bundled many of the top Android and Firebase agent skills in the latest Android Studio Canary build, so you can skip straight to building!

Skills in Agent Mode

You can create your own skill, or use Android CLI to install our official skills - a repository that covers some of the most common workflows that some Android developers and LLMs may struggle with. They help models better understand and execute specific patterns that follow our best practices and guidance on Android development, such as XML to Compose migration, Edge-to-edge, Navigation 3, and more. You can even build for Android XR, starting with a beautiful Display Glasses app with Jetpack Compose Glimmer. Official Android skills are automatically bundled with the latest Android Studio so the Agent is ready to build!

Build full-stack apps with Firebase in Agent Mode

Firebase services like Auth and Firestore databases can now be enabled directly within Agent Mode in Android Studio using the Agent Skills for Firebase. Your agent will be able to complete Firebase integration and configure backend services. This integration empowers you to build robust, full-stack Android applications without ever leaving your IDE!

Building a full-stack app with Firebase via Agent Mode

Parallel conversations

You can now run multiple conversations with Agent Mode in parallel. In one conversation, run tests and while you are waiting, you can kick off planning mode for a new feature in your app while using a third conversation thread to write documentation for your app. These improvements will save you time and improve your productivity.

Parallel conversations in Agent Mode

A more capable New Project Agent

Android Studio's New Project Agent has evolved into a powerful full-stack development tool, utilizing a multi-step execution plan and an autonomous "generation loop" that self-corrects build errors and configures dependencies across multiple files. This advanced capability is significantly amplified by its new integration with Firebase Agent Skills, allowing developers to seamlessly build, debug, and deploy complete full-stack applications directly from a single prompt to final production.

Building an app with New Project Agent

Additionally, it now offers support for large screens. You can scaffold your project with layouts, navigation, and components optimized for tablets, foldables, and laptop devices from the get-go. It has additional logic to test your app on large-screen emulators if you have one enabled. Simply configure the required device in the Android Emulator and the Agent can test it out!

Build large screen apps for foldables and tablet devices

2: Any AI provider, anywhere you build

Build Android apps in Google AI Studio

Google AI Studio now features full Android app development capabilities. Users can generate new applications, preview them instantly via an embedded Android Emulator, and deploy them directly to physical devices using ADB over USB. Additionally, developers can publish straight to Google Play; AI Studio handles the app record creation, bundles the package, and uploads it to an internal testing track. For advanced development and production readiness, projects can be exported as a ZIP file and opened seamlessly in Android Studio. To get started, visit Google AI Studio today and start building!

Google AI Studio build mode with Android framework

Android CLI helps you build faster, more efficiently with any agent

Android CLI enables you to build apps using any agent, LLM, and tool of your choice. Android CLI is designed to help AI agents build faster, and use less tokens when compared to only using generic LLM tools. By grounding agents with Android Knowledge Base and Android skills, you can now have your agent of choice follow the latest best practices across any coding environment.

Additionally, when using the latest Canary version of Android Studio Quail, Android CLI enables your agent to leverage powerful capabilities of the IDE, such as analyzing files for issues or finding symbol declarations. Google Antigravity 2.0 now offers official support for Android development with Android CLI.

Android CLI enables any agent with the tools and knowledge to build for Android.

Google AI plan

You can now use your Google AI Pro or Ultra plan to get access to dedicated capacity and higher rate limits for Gemini in Android Studio. This is especially helpful for long agentic Android development sessions, which can require using more tokens. Android Studio detects your subscription automatically when you log in with your Google account.

Use your Google AI plan in Agent Mode

Gemma 4 for local code assist and on-device AI

Gemma 4 is a state-of-the-art local model trained for Android development. It’s our most efficient local model and is capable of complex multi-step agentic coding in Android Studio. It’s ideal for developers who require data privacy, offline access, or have run into quota issues with other models.

And now in the latest Canary build, you can download and run Gemma 4 directly from the IDE, without needing to set up an external server.

Model selector in Agent Mode

Bring your own model to Android Studio

Android Studio allows developers to bring any model they choose into the IDE for agentic AI assistance. Power your workflow with models like Gemini, GPT, and Claude or use a local model like Gemma 4. This flexibility offers developers greater control over performance, privacy, and cost.

Settings, Model Provider

Android Bench highlights the top models

Earlier this year we launched Android Bench, the benchmark and leaderboard designed to evaluate how effectively LLMs handle real-world Android development tasks. The goal is to accelerate AI improvements, leading to more helpful models for you to use for AI assistance, which will lead to better quality apps for Android users.

You asked us to evaluate open models, so we added them to the leaderboard to help you see how LLMs with additional privacy and offline access measure up. We are also working on significantly increasing the difficulty of challenges we’re giving LLMs, to continue encouraging improvements. This includes creating long running tasks, which take a typical Android engineer multiple days to complete.

Latest results as of May 18th 2026, check here for updates

3: As always, performance and quality remain top priorities:

Test multi-device interactions with the Android Emulator

The Android Emulator now features a new networking stack that enables zero-configuration, peer-to-peer connectivity between multiple virtual devices on the same host machine. This update eliminates the need for manual port forwarding, allowing developers to easily test multi-device scenarios like local multiplayer gaming, file sharing, and companion app pairing. By creating a shared virtual network backplane, the Android Emulator provides a more stable and consistent environment for building complex, interconnected app experiences across different form factors.

Multi -device testing with the Android Emulator

Android Debug Bridge Wi-Fi 2.0

ADB Wi-Fi 2.0 offers significantly more reliable wireless debugging. With the latest ADB command line tool from Android Platform Tools v37 and an Android 17 device, you can now change networks, shut down your machine, and go about your typical day and your devices will stay connected. Additionally, devices with wireless debugging enabled will automatically show in Android Studio’s Device Manager, streaming the pairing process and making it easier than ever to connect Android phones, watches, and more.

Pair devices with Wi-Fi

Android Studio now lets you publish to Google Play for testing

Android Studio now gives you the ability to upload new releases of your app directly to Google Play Console test tracks. You can do this by selecting a new option to continue to “Publish for Testing” at the end of the Generate Signed App Bundle flow. This integration supports uploading an initial release of a brand-new app to Play Console’s internal test track. You can also use this feature to upload releases to existing apps to test tracks. You need to be registered on Google Play Console to take advantage of this functionality. Read the ‘What’s new in Google Play’ blog to learn about all the updates from Play at I/O.

Upload App Bundle to Google Play

Android developer verification support

You can now see your app's registration status right in Android Studio when you generate a signed App Bundle or APK. Seeing this information in Android Studio enables you to address registration issues early and ensure your apps are ready before the verification requirement goes into effect for certified Android devices starting in September 2026.

App registration status with Android developer verification

Memory leak detection with LeakCanary

Memory leaks in Android occur when your code holds onto an object's reference long after its life cycle has ended. This prevents the Garbage Collector (GC) from reclaiming that memory, eventually leading to sluggish performance or OutOfMemoryError (OOM).

The Android Studio LeakCanary profiler task significantly enhances developer productivity by enabling the analysis and inspection of memory leak traces directly on the desktop development environment rather than on the mobile device. Furthermore, Android Studio streamlines troubleshooting by providing tools like “Go to declaration” to map the leak analysis directly to the codebase, allowing developers to quickly locate and resolve memory leaks.

Starting from the Android Studio Quail 1 release, you can now also request Gemini to review the memory leak for you using the “Fix with Agent” button.

Review memory leaks identified via LeakCanary through the “Fix with Agent” button

Android Performance Analyzer (APA)

Android Performance Analyzer (APA) is the next generation of performance profiler for Android and provides a cohesive analysis of CPU, GPU, memory, and power usage for your apps and games running on Android 12+ devices. APA is engineered for reliability and performance with trace rendering speeds which are up to 26x faster from previous tooling.

Android Performance Analyzer (APA) running in Android Studio showing two traces side by side

APA integrates natively with AI agents and offers two new skills: Perfetto SQL skill and the Perfetto Analysis skill, which helps with questions like "Why is my app startup slow?"

Analysis of traces using Perfetto Analysis skill

R8 Configuration Analyzer

R8 is one of the best ways to improve your app’s performance and reduce memory footprint. The performance benefits you can get from R8 are directly correlated to how much of your codebase R8 is able to optimize. We’ve introduced a new tool to help you to unlock the maximum optimization from R8 – the R8 Configuration Analyzer. It provides insights into R8 configuration quality and how your keep rules impact your app. We have also introduced three scores that show how much of your codebase is available for optimization, obfuscation, and shrinking.

Suggested fixes for crashes with Agent integration in AQI

The App Quality Insights tool window is now integrated with the AI agent to analyze crash data along with your source code to provide detailed explanations and suggest potential fixes. After selecting a crash in the App Quality Insights tool window, navigate to the Insights tab and click “See more” to see a detailed explanation of the crash. Click “Fix with AI” to have the agent suggest code changes that you can review and accept.

App Quality Insights and Fix with AI

Get started

Android Studio is closing the gap between ideation and implementation. With powerful tools built for agentic development, it’s never been easier to build and ship high-quality Android apps.

Download the latest Android Studio Quail preview build and try these new features. As always, your feedback is crucial to us. Check known issues, report bugs, and be part of our vibrant community on LinkedIn, YouTube, or X. Happy coding!

Explore this announcement and all Google I/O 2026 updates on io.google.

Android UI Development is Compose First

2026-05-19T02:00:00.000-07:00

Posted by Nick Butcher, Product Manager

In the almost-5-years since Jetpack Compose launched, we've invested in bringing you all the features, performance and tools that you need to build amazing UIs across the variety of Android devices. Compose helps you to build beautiful, adaptive UIs that meet the demands of modern UI design.

Rich feature set: With a powerful library of layouts, input, graphics, animation APIs, and the latest Material Design components, Compose empowers you to build anything.
Highly performant: Out of the box, Compose offers native performance, delivering a delightful experience to your users.
Adaptive: Compose offers the easiest way to build adaptive apps that work across the range of Android form factors.
Productive: With powerful tools like Previews and Live Edit and the full expressiveness of Kotlin, teams tell us that they move much faster when building with Jetpack Compose, reducing the time to market.

Compose has matured into the standard for Android UI development—we believe that all Android UI should be built with Compose; we call this going Compose First. From today, we'll provide all APIs, libraries, tools and guidance in Compose. We now consider the View components that Compose replaces (components in the android.widget package) to be in maintenance mode. We have no plans to deprecate or remove View components and will continue to support them with critical bug fixes, but they will receive no new features.

View-based Jetpack Libraries
The same goes for View based libraries like Fragments, RecyclerView or Viewpager — we consider them complete and will only publish critical bugfixes. For a complete list of libraries now in maintenance mode, see here.

Tools
Any new Android Studio UI tools will be built for Jetpack Compose only. Existing view-based tools (such as the Navigation Editor and Layout Editor) are now in maintenance mode and will not receive new features.

Guidance
Documentation, codelabs, and samples will focus on building UI with Jetpack Compose. You can still find Views-specific documentation linked from pages that contain generic and Compose information, where relevant.

Happy Composing

We recommend that you build all new features with Compose and convert existing features when you touch them to gain the many Compose benefits. Check out our XML to Compose migration skill to help you convert existing layouts to Compose.

To learn about the latest Compose release, check out What’s new in the Jetpack Compose April ‘26 release blog and the roadmap for what’s planned ahead.

Thank you for all of the feature-requests and feedback that have helped shape Compose to become our recommended UI toolkit. As always, if you have any more feedback, let us know. Happy composing!

Explore this announcement and all Google I/O 2026 updates on io.google.

What's new in Android for Cars: Unifying platforms and unlocking premium experiences

2026-05-19T01:30:00.000-07:00

Posted by Jan Kleinert, Developer Relations Engineer, Android for Cars, Noam Gefen, Senior Product Manager, and Thomas Weathers, Developer Relations Engineer, Android for Cars

We're thrilled to see developers continuing to bring their apps and experiences to Android for Cars! Over the past year, we've continued to see strong growth and momentum in the app ecosystem on Android Auto and cars with Google built-in. This year at Google I/O, we're introducing updates that benefit both drivers and developers by enabling richer, more differentiated in-car experiences. With new features and templates that allow you to build once to reach users across different infotainment screens and car platforms, it's easier than ever to build for the road.

What's new in the Car App Library

We're bringing more flexibility, new components, and new template capabilities to the Car App Library. Car App Library 1.8.0-beta01 and Car App Library 1.9.0-alpha01 are now available.

Build templated media apps for both Android Auto and Android Automotive OS

Developers can now build customized, distraction-optimized, media browsing and playback experiences for Android Automotive OS, making it easier to build once and deliver these templated media apps to more users and more cars.

To help you test the experiences on Android Automotive OS, we'll be launching updated system images for the Android Automotive OS emulator. Beginning with revision 3, the API level 35-ext15 system images will support apps built using the Car App Library media templates.

Unlocking developer creativity with Car App Library 1.9.0 alpha

With the 1.9.0-alpha01 release of the Car App Library, we're bringing features to help you build more differentiated, expressive experiences across Android Auto and cars with Google built-in.

We're increasing the modularity of existing templates to give developers more flexibility and options for laying out content. These improvements include expanded headers for better visual emphasis, such as on detail pages, spotlight sections that can be placed in scrollable areas to highlight specific content, and grid item variations to support different content types and states.

We're introducing new components and template capabilities to help developers build even more engaging experiences. For media apps, we're introducing an adaptive mini-player, so users can browse while still easily managing playback. Finally, we're adding more component types including Chip and CondensedItem to increase the ways that content can be displayed and interacted with.

App developers, including those shown below, have already begun building upgraded media experiences using these new Car App Library features. You can join these developers and prepare to distribute your own media apps built with the Car App Library templates by applying to participate in our early-access beta program.

Amazon Music, Gaana, PocketFM, Spotify, TuneIn, YouTube Music

Distribute your adaptive video apps to more cars with minimal effort

You’ve already built the apps, now we’re helping you reach more users. For the first time in Android Auto, users will be able to sit back, relax, and watch videos while parked. Apps, like YouTube, will be able to deliver smooth, 60fps HD video playback. This brings the Android Auto parked experience in line with the high-fidelity, immersive experiences users already enjoy in cars with Google built-in.

This capability will start rolling out to compatible vehicles later this year, for users with phones running Android 17 and higher. If your video app is already adaptive, making it available for parked use cases in cars requires minimal effort. To express interest in making your video app available on Android Auto, fill out this form.

Widgets are coming to cars

The next generation of Android Auto brings a more expansive user interface and the Material 3 Expressive design system you know from the phone into the car, built to seamlessly fill larger screens no matter what shape they are. With this new design, the investments you've already made in mobile widgets will be available to users of Android Auto this year, and cars with Google built-in later on, opening up new ways to reach and engage with your users while they're on the road. We're excited to unlock these new glanceable user journeys!

The road ahead

You can look forward to even more updates coming to cars later this year.

To deliver a more continuous user experience, we're making it possible for you to provide a templated experience while driving that can seamlessly transition to a native, adaptive app experience when the vehicle is parked.
New components and conversational templates will be coming to the Car App Library, so you can integrate agentic and voice-based flows more seamlessly in apps.
Improved app brand expression across all car surfaces allow experiences built with the Car App Library to feel easily recognizable by your users.
Google Maps SDK support is coming to cars with Google built-in. With this change, you'll be able to use the Google Maps SDK to render map-based content with the MapWithContentTemplate in point-of-interest (POI) and Weather apps on both Android Auto and cars with Google built-in.

Stay updated on these features and start building with the latest at goo.gle/cars-whats-new.

Explore this announcement and all Google I/O 2026 updates on io.google.

I/O 2026: What's new in Google Play

2026-05-19T01:15:00.000-07:00

Posted by Paul Feng, VP, Google Play Eng, Product, UX

At Google Play, we’re passionate about helping people connect with the experiences they’ll love, while empowering developers like you to turn great ideas into lasting business success.

At this year’s Google I/O, we talked about our evolving business model that offers more choice and new ways for your apps and content to be discovered on and off the store. We also unveiled advanced tools and insights that will help scale your business with less complexity. Watch the keynote video below, or keep reading for the biggest updates from this year’s event.

Expanding your reach by meeting users where they are

Your apps and the incredible worlds you build are no longer just a single destination, but connected experiences that reach users across surfaces and devices. To help you meet users where they are, Google Play continues to evolve into a content-forward destination that delivers immersive and personalized experiences on the store, across their devices, and directly within your apps and games.

Beyond the store: Expanding discovery to new surfaces & devices

We're unlocking new opportunities for your apps and content to be discovered across the wider Android ecosystem.

Surfacing your apps and content in Gemini: As people increasingly start their journeys with virtual assistants, we want to ensure your apps and their content are an essential part of this. In the coming weeks, we're enabling app discovery in the Gemini app on Android and Web, connecting your apps and games to millions of Gemini users. Later this year, Gemini will also surface over 450,000 movies and TV shows, as well as where to stream live sports, and deep-link users directly into your app content.

Gemini will provide users with app suggestions and direct access
to entertainment content during a search.

Delivering personalized content across the ecosystem: Engage SDK surfaces deliver your content to over 30 million monthly active users and drive millions of app opens every month—a massive 45% increase year-over-year. And we’re making it even more powerful by expanding support for new surfaces and devices.
- Store listing integration: Starting next month, existing users will see Engage SDK content directly on your store listings.
- New tablet surfaces: We’re broadening reach across Android tablet surfaces, including home screen Collections.
- Global scale: Every Engage SDK surface can now scale your content across over 80 Play markets.

Boost re-engagement by integrating with Engage SDK today. If your app is already integrated, no further action is required to benefit from these updates.

On the store: Enhancing content formats and conversational search

We’re also optimizing the Play Store to help grow your audience with engaging content formats and a more intelligent search experience, to make it easier than ever for users to find and connect with your app.

Capturing attention with Play Shorts: Our full-screen, portrait, short-form video feed gives users a glimpse of your app’s look, feel, and functionality. Play Shorts is rolling out to users in the US and select developers, and we look forward to expanding this to more markets and developers in the coming months.

Play Shorts provides a glimpse into your app’s look, feel & functionality.

Enabling deeper search journeys with Ask Play: Building on AI-powered Q&A, which already answers 95% of user queries, we’re introducing Ask Play. This AI-powered overlay turns discovery into a natural conversation, understanding the full context of a user's question and adapting to follow-ups to recommend the right app. Plus, with Ask Play highlights, users can get a high-level summary of complex searches directly on the search results page to help find the right apps or games more effortlessly.

Ask Play understands the full context and helps users find the right apps or games.

In your games: Deepening player engagement and community

Once players launch your title, the real challenge is keeping them in the action. Play Games Sidekick provides an in-game overlay that gives players instant access to gaming information—like AI-generated Game Tips, rewards, and achievements — driving higher engagement while keeping players immersed. Sidekick has already debuted in over 100+ titles, and we’re building on this momentum with:

New social features: Starting next month, players can see which friends are playing the same game and track their achievements
Global expansion: Sidekick expands to all participating titles this summer. Head over to Play Console to enable Sidekick and begin testing the user experience so that you're ready for our global launch, while also meeting one of our core Level Up program guidelines.

Scaling your business with less complexity

We’re streamlining your day-to-day tasks while providing more comprehensive reporting to help you capture more growth opportunities.

Streamline your Play Store operations with AI

We’re using Gemini models to handle the heavy lifting of localizing your store content and managing your catalog.

Localize with less effort: Eliminate manual copy-pasting by uploading a structured file (like a CSV or Google Sheet). Gemini models enable Play Console to pre-populate your listings across different languages for your review. You can also leverage AI-translated subscription benefits to quickly scale your localization efforts.

Instantly pre-populate store listings with localized translations.

Convert search trends into growth: We’ve simplified the path from insight to action. When you click a keyword recommendation on your Grow overview page, Gemini creates a new custom store listing automatically tailored to that keyword—ready to deploy with just one click.
Simplify catalog management: We’re introducing agentic catalog management to help you manage your one-time products. Soon, you can leverage new in-console capabilities to execute bulk price changes, import SKUs, and configure metadata, saving hours of manual work.

New agentic capabilities in Play Console will make managing your catalog seamless.

For a detailed look at these features and more, watch this video.

Behind-the-scenes features that optimize your revenue

We’re building tools to maximize your revenue at every stage—with zero developer work required. When a user decides to buy, our platform helps ensure that the transaction completes at the point of conversion, renewal, and retention.

Optimizing conversion with delayed charging: When a payment initially fails, our risk models evaluate the transaction. If it’s low-risk, we grant the user access to your paid content while we retry the charge in the background. This means your lowest-risk subscribers get the best experience and you are less likely to lose them due to a temporary glitch.
Boosting renewals with extended recovery periods: To prevent involuntary churn, we’ve extended the default account recovery period from 30 to 60 days to give subscribers more time to fix failed payments, like expired credit cards. This shift has driven up to an 18% reduction in involuntary churn and a 9% reduction in total churn for top developers.
Maximizing retention with flexible flows: A rigid experience makes retention nearly impossible. Coming soon, our new in-app subscription management API lets subscribers change plans or accept a downgrade offer the moment they hit “cancel.” Combined with replacement modes that automate prorated refunds, you’ll have a powerful toolkit to save at-risk subscribers.

Flexible flows let subscribers change plans or accept downgrades to boost retention.

More reporting and AI-powered insights

We’re providing more data and more AI-powered insights to help you understand your performance and ROI on Play.

Measure your full marketing impact: See your app’s total visibility on Play with our new reach metric. Gain better insight into store listing performance with indirect value not previously reported. Analyze downstream impact—like engagement, retention, and monetization—with our new traffic source breakdowns.
Optimize the path to purchase and retention: We’ve added cart conversion rates to your core performance metrics to help you identify and fix friction in your checkout flow. New data on subscriber tenure and churn reasons allow you to better pinpoint why subscribers leave and which segments are most at risk.
Get faster answers: Using Gemini models, we’re expanding chart descriptions from the Statistics page to the Reach & Devices and Store Performance pages to help you spot trends instantly. With new interactive Q&A and proactive monetization insights, you can ask why a metric shifted and instantly receive tailored recommendations to optimize your business.

Get instant answers and recommendations for optimizing your business.

Protecting your success

In addition to making it easier and faster to publish safer apps, we’re also making it easier to secure your app’s revenue and reputation.

Defend your business against fraud and abuse: The new Protected with Play dashboard helps you monitor and configure your integrity, distribution, and monetization defenses all in one place. We’re also reducing warm-up latency for Play Integrity API, so you can use these checks during speed-critical user journeys to block threats and risky devices faster.

The Protected with Play dashboard provides centralized insights to help you safeguard your app.

Get proactive protection for your store and revenue: We work behind the scenes to help stop malicious activity before it impacts your business. Last year, our automated anti-spam protections blocked 160 million spam ratings and reviews while our anti-fraud efforts automatically protected apps using Play Billing from 3.2 billion dollars in fraud and abuse.

Growing your business on Google Play

Our latest updates reinforce our commitment to deliver the highest return on your team’s investment, by expanding your reach beyond the store, simplifying your day-to-day operations, and helping you better safeguard your success. We’re excited to see you use these new capabilities to create even more impactful experiences. Thank you for being a part of the Google Play community.

Learn more about these announcements and all other Google I/O 2026 updates on io.google starting May 21.

What's New in Wear OS 7

2026-05-19T01:00:00.000-07:00

Posted by John Zoeller, Developer Relations Engineer

Today, we are excited to introduce Wear OS 7, a major update that brings a new era of power efficiency and intelligence to users and developers alike.

We recognize that watches are essential, all-day companions to your users. That’s why we're continuing to invest in power optimizations so your users can do more with their favorite apps. For watches upgrading from Wear OS 6 to Wear OS 7, average users can expect up to 10% improvement in battery life.

As part of a broader rollout to the Android ecosystem, select watches arriving later this year will come with Gemini Intelligence, providing proactive and personalized help to our users so they can focus on what matters.

With Wear OS 7, we’re introducing new system capabilities and enhanced developer tools. New user-facing features like Live Updates, and enhanced media controls deliver a smarter, more intuitive personalized experience on the wrist. And with enhancements to our developer toolkit such as Wear Compose 1.6 and AppFunctions, developers will be able to streamline their apps for efficient, intuitive experiences on the wrist.

Let's dive right in!

Wear OS 7 Canary

You can now try out the next version of Google’s smartwatch platform, Wear OS 7 Canary Emulator, based on Android 17 that's arriving later this year.

The new emulator allows you to get hands-on with the developer features and tools mentioned above while testing your app for compatibility with the upcoming platform.

Check out what’s changed and start testing your app today.

Explore new Wear OS features

Wear OS Widgets

Full-screen Tiles have been a go-to surface on Wear OS, providing users with instant, glanceable access to their essential updates. As the Android ecosystem moves further toward a unified vision for widgets, we’re bringing the watch closer to the rest of the Android family with the goal of minimizing efforts for developers.

Today, we’re excited to introduce the next step in the evolution of Tiles: flexible and dynamic Wear Widgets.

Powered by Jetpack Glance and the new RemoteCompose framework, Wear Widgets offer greater expressiveness and consistency with Compose than the Tiles ProtoLayout libraries. Wear Widgets support two new card layouts—small and large, that align perfectly with the 2x1 and 2x2 formats on mobile, ensuring your designs feel cohesive across devices, while still allowing you to optimize your designs for the wrist.

It’s easy to adapt the UI from the mainSlot of your full-screen tile to a 2x2 Widget. Take a look!

Check out the Widgets I/O Talk later this week for full details on the new features, and try out our Widgets Getting Started Guide to add a Widget to your Wear OS experience.

Live Updates

Wear OS 7 brings Live Updates to watches!

You can use Live Updates to surface real-time, important information from your watch or mobile app, providing your users with timely updates at a glance.

In your watch app, use Live Updates instead of the Ongoing Activities API to provide local update publishing on all Wear 7 devices. For supporting OEMs, Live Updates published by your phone app will also be bridged to users' watches.

Check out how Just Eat provides updates to their users, above!

For more information, check out Notifications on Wear OS.

Connect your app to the intelligence system

We're working on several ways for developers to provide agentic experiences on the watch, from AppFunctions to task automation tools.

We’ll announce these on our developer blog when they’re ready, and provide an all-encompassing developer guide to help you choose the right one and craft a robust implementation. For now, here's a quick look.

AppFunctions

The AppFunctions API allows developers to integrate their apps with agents and assistants, like Google Gemini, enabling users to complete tasks using voice, often replacing the need for step-by-step, manual navigation with your UI.

For example, to start a run with the Samsung Health app, users are able to tell Gemini: “Start tracking my run.”

We’re currently running an Early Access Program for any developers who are interested. Sign up in our form to express your interest.

Task automation

Also coming soon, without any development effort at all, users will be able to invoke and track automated app tasks, for selected phone apps, directly from their watch, like placing an order with DoorDash!

Keep an eye out for these flexible options on how to prepare and connect your app to the Android intelligence system on our developer blog.

Wear Workout Tracker

We know that building a full-featured, high-quality fitness tracking experience on Wear OS from scratch is resource-intensive, so we built the all new Wear Workout Tracker experience for exercise apps. It will be included in Wear OS later in the year.

The workout tracker provides a rich standardized workout tracking experience which includes heart rate monitoring, media control, and a collection of other useful features to help you reduce development investment while guaranteeing a high-quality experience for your users.

We’ve been working closely with ASICS Runkeeper to bring it to their users, check it out!

Enhanced System Media Controls in Wear OS 7

Wear OS 7 enhances the System Media Controls, giving users more control and seamless experiences for their media.

Per-App media auto-launch controls

Users can now personalize their media auto-launch experience per-app directly from the System Media Controls on the watch.

For any app where the user has ‘Auto-launch Settings’ toggled on, media controls will automatically appear on the watch when media is started on the phone.

Developers with an existing implementation of media apps that extend on the watch can benefit from this feature without additional effort.

Seamless audio routing with the Remote Output Switcher

Managing audio output is now easier than ever with the new Remote Output Switcher integrated into the System Media Controls.

When listening to media on a paired phone, users can effortlessly switch the device the media is played back on directly from their wrist.

UI Library updates

To go along with all these new features for users, we’re introducing some powerful enhancements to our developer toolkits to help developers prepare for the future of Wear OS!

Compose for Wear OS 1.6

As the foundation for Wear OS development, Compose for Wear OS 1.6 has arrived.

It includes powerful updates including:

Streamlined navigation with Navigation 3

Developers can Integrate with Navigation 3 to provide a more flexible and Compose-idiomatic way to handle navigation on Wear OS.

@Composable
fun WearApp() {
    val backStack = rememberNavBackStack(MenuScreen)
    WearAppTheme {
        AppScaffold {
            val entryProvider = remember {
                entryProvider<NavKey> {
                    entry<MenuScreen> { GreetingScreen() }
                    entry<ListNavScreen> { ListScreen() }
                }
            }
            val swipeDismissableSceneStrategy = rememberSwipeDismissableSceneStrategy<NavKey>()
            NavDisplay(
                backStack = backStack,
                entryProvider = entryProvider,
                sceneStrategies = listOf(swipeDismissableSceneStrategy)
            )
        }
    }
}

List management improvements for TransformingLazyColumn

Significant improvements are here for advanced list management with TransformingLazyColumn, including enhanced padding support via the new minimumVerticalContentPadding modifier, and other new features like snapping and reverse layout.

val listState = rememberTransformingLazyColumnState()
val transformationSpec = rememberTransformationSpec()

/*
 * TransformingLazyColumn takes care of the horizontal and vertical
 * padding for the list and handles scrolling.
 */
ScreenScaffold(scrollState = listState) { contentPadding ->
    TransformingLazyColumn(
        state = listState,
        contentPadding = contentPadding
    ) {
        item {
            ListHeader(
                modifier = Modifier
                    .fillMaxWidth()
                    .transformedHeight(this, transformationSpec)
                    .minimumVerticalContentPadding(
                        ListHeaderDefaults.minimumTopListContentPadding
                    ),
                    transformation = SurfaceTransformation(transformationSpec)
            ) { Text(text = "Header") }
        }
    }
}

Optimize ambient experiences with LocalAmbientModeManager

The all new LocalAmbientModeManager is optimized for handling ambient flows, giving developers greater control over how their ambient experiences are presented to users.

override fun onCreate(savedInstanceState: Bundle?) {
    setContent {
        val ambientModeManager = rememberAmbientModeManager()
        CompositionLocalProvider(LocalAmbientModeManager provides ambientModeManager) {
            val localAmbientModeManager = LocalAmbientModeManager.current
            val ambientMode = localAmbientModeManager?.currentAmbientMode

            Column(
                verticalArrangement = Arrangement.Center,
                horizontalAlignment = Alignment.CenterHorizontally,
                modifier = Modifier.fillMaxSize(),
            ) {
                val ambientModeName =
                    when (ambientMode) {
                        is AmbientMode.Interactive -> "Interactive"
                        is AmbientMode.Ambient -> "Ambient"
                        else -> "Unknown"
                    }

                val color = if (ambientMode is AmbientMode.Ambient) Color.Gray
                    else Color.Yellow
                Text(text = "$ambientModeName Mode", color = color)
            }
        }
    }
}

Protolayout & Tiles updates

While we encourage developers to adopt the new Wear Widgets, we will continue to support our Protolayout and Tiles libraries for some time, and we’ve got new stable versions of both.

Protolayout 1.4 and Tiles 1.6 work together to provide several notable new features including:

Inlined Image Resources: ImageResource can now be directly inlined within a layout, and Tiles now support automatic resource collection through ProtoLayoutScope,removing the need for manual resource mapping and splitting into separate methods. In addition to better code quality, this improves Tiles loading latency via consolidation into a single binder call from system to the provider service.
Material3TileService: Tiles can be implemented as a Material3TileService – an all-encompassing suspend function which returns both tile layout and resources, while automatically managing the MaterialScope and ProtoLayoutScope to simplify the development experience.
Dynamic Service Switching: On Wear 7, multiple TileService instances can now be grouped in the manifest to enable dynamic switching between different services that represent the same tile.

Check out the new Tiles sample here.

WFF 5

Watch Face Format version 5 (WFF5) is now available with a host of new features to make it easier to build watch faces, including:

Enhanced Alignment Options: Text elements like TextCircular have additional alignment options, including verticalAlign on the same baseline for multiple text elements.
Auto-Size Enhancements: isAutoSize can now be used on TextCircular,and a new attribute, minSize, has been added to the Font element to limit the minimum size when autosizing is enabled.
Blend Modes: Group and ComplicationSlot elements now support blend mode, in addition to existing support on Part* elements.
Stroke Joins: Stroke and WeightedStroke elements now include a join attribute.
Hierarchical settings: User Styles can now be structured as a hierarchy, where some settings are visible only when other settings have specific values. User Styles can now enable or disable complication slots as well. These can be configured using the childSettingIds and complicationSlotIds on User Style Options.

Check out our new developer guidance to learn more about WFF 5.

Start building for Wear OS 7 now

With these updates, there’s never been a better time to develop an app on Wear OS. These technical resources are a great place to learn more about how to get started:

We’re looking forward to seeing the experiences that you build on Wear OS!

Explore this announcement and all Google I/O 2026 updates on io.google.

How FotMob leveraged cross-device discovery to score record Wear OS adoption

2026-05-15T09:00:00.000-07:00

Posted by Garan Jenkin, Wear OS Developer Relations Engineer

FotMob recently experienced its largest single-day increase on Wear OS among its installed audience in 5 years, at 2-3x the daily average. The secret? A simple cross-device installation flow that helps users discover their Wear OS app directly from their phone.

FotMob is one of the world’s most popular football (some call it soccer!) platforms, known for its mobile app that provides real-time scores, statistical analysis, and news.

FotMob is available on mobile and Wear OS

In addition to the mobile app, FotMob is available on Wear OS, allowing users to keep on top of the latest scores and results directly from their wrist.

“Many FotMob users follow matches live, and that often happens when they’re not actively using their phone,” says Roy Solberg, Android Tech Lead at FotMob. “Wear OS gives fans a quick way to glance at scores, match events, and updates directly from their wrist, so we saw it as a natural extension of the FotMob experience.”

By providing a smooth experience across different form factors, FotMob ensures that their users can continue to get the most from their platform, in the most convenient form. This includes ensuring that settings and preferences–such as favorite teams–are synced across devices.

The Discovery Gap

Despite many FotMob users having a Wear OS device, FotMob realized that some users might not be aware of the Wear OS app. This led the team to consider technical options for how to educate users about and ultimately install the Wear OS app directly from within the core phone app.

Fortunately, the Wearable library on Android and Wear OS provides exactly the building blocks that FotMob needed to create an in-app experience that would allow their users to do just that.

Detecting Eligible Wear OS Devices

Within the FotMob phone app, the team used the NodeClient to identify connected Wear OS devices - candidates for the Wear OS app:

val connectedNodes = nodeClient.connectedNodes.await()

Additionally, the team defined a capability within the Wear OS app, indicating that FotMob was installed on the device. This is defined as an XML resource in the Wear OS package, and then queried within the phone app:

val nodesWithApp = capabilityClient
    .getCapability(CAPABILITY_WEAR_APP, CapabilityClient.FILTER_REACHABLE)
    .await()
    .nodes

By looking for only nodes without the capability, the team ensured the FotMob phone app only lists Wear OS devices without the app.

Initiating the install flow

The FotMob team designed an educational half-page prompt that quickly makes the user aware of the opportunity, allowing them either to kick off the install flow, or dismiss it. This featured a prominent screenshot of the Wear OS experience, allowing the user to immediately see how the app might look on their watch.

To start the installation, the app uses the RemoteActivityHelper API, to launch the Play Store on the watch:

val remoteActivityHelper = RemoteActivityHelper(context)

remoteActivityHelper.startRemoteActivity(
    Intent(Intent.ACTION_VIEW)
        .setData("market://details?id=${context.packageName}".toUri())
        .addCategory(Intent.CATEGORY_BROWSABLE),
    nodeId
).await()

Results

“The Wearable APIs made the implementation straightforward,” says Roy. “Being able to detect connected devices and query capabilities meant we could quickly determine whether the watch app was already installed. From there it was mostly about designing a prompt that felt helpful to users rather than intrusive.”

The rollout of the cross-device installation feature saw the largest single-day increase in FotMob’s installed audience on Wear OS in 5 years, 2-3x higher than the normal install rate. Within 48 hours of the rollout reaching 100%, the watch app gained over 1,500 new installs¹.

“Within the first 10 days we saw a significant jump in new Wear OS installs,” says Roy. “The watch app has been around for years, but this confirmed that many users with compatible devices simply weren’t aware it existed.”

Evolving cross-device installs

In addition to the solution employed by FotMob, we’ve now launched a library to make it even easier to implement these cross-device installation journeys through the In-App Install Prompts library.

The following is an example of adding an installation prompt at the appropriate point in your app:

val crossDevicePromptManager = CrossDevicePromptManagerFactory.create(activity)
val request = CrossDevicePromptInstallationRequest.create()

try {
    val info = crossDevicePromptManager.requestInstallationPromptFlow(request).await()
    crossDevicePromptManager.launchPromptFlow(activity, info).await()
} catch (e: CrossDevicePromptException) {
    Log.e(TAG, "Cross-device prompt failed with error: ${e.errorCode}", e)
}

Next steps: Start building your own cross-device journey today

Dive into the DataLayer sample to learn more about how to add cross-device functionality to your app, and explore the new In-App Install Prompts library, providing you with options for how you help your users achieve cross-device installation.

[1]. Install data from Play Developer Console