Android XR vs Apple Vision Pro SDK: Spatial Computing for Apps

Spatial computing is no longer a tech demo. Apple shipped the Vision Pro in early 2024 and followed up with Vision Pro 2 in 2026, bringing the price down to $2,499 and the weight down to 450 grams. Google and Samsung answered with Android XR, powering the Samsung Project Moohan headset at $1,299 and a growing lineup of XR-capable smart glasses. Both ecosystems now have real developer SDKs, real app stores, and real users.

But the two platforms take fundamentally different approaches to spatial computing. Apple controls everything: hardware, OS, SDK, and distribution. Google provides the platform layer and lets OEM partners handle hardware. If you have built for iOS vs Android on phones, this dynamic will feel familiar. The stakes are higher here, though, because spatial apps require significantly more engineering effort than flat-screen mobile apps, and picking the wrong platform first can cost you six figures in wasted development time.

We have shipped spatial apps on both platforms for enterprise and consumer clients. This guide breaks down the real differences in SDKs, developer experience, hardware, distribution, and cost so you can make an informed platform decision for your next project.

Apple's visionOS SDK is, predictably, the more mature and opinionated of the two. If you already know SwiftUI, the learning curve is manageable. If you do not, budget an extra 4 to 6 weeks for your team to ramp up before writing any spatial code.

Core Frameworks

RealityKit is the 3D rendering engine that powers all spatial content on visionOS. It handles mesh rendering, physically based materials, spatial audio, skeletal animations, and physics simulation. RealityKit 4 (shipping with visionOS 3) added volumetric particle effects, improved hand-tracking fidelity, and a scene understanding API that lets your app intelligently place virtual objects on real surfaces. You build 3D scenes either in code or with Reality Composer Pro, Apple's visual scene editor bundled into Xcode.

ARKit for visionOS provides environmental understanding: plane detection, mesh classification (walls, floors, ceilings, furniture), image tracking, and world anchors that persist across sessions. The hand and eye tracking APIs are surprisingly precise. Eye tracking accuracy is within 1 degree, and hand tracking captures 27 joints per hand at 90Hz.

SwiftUI for Spatial extends SwiftUI with three container types that define how your app occupies space:

• Windows: Flat 2D panels that float in the user's environment. These feel like traditional app windows and are the easiest entry point for existing iOS developers.
• Volumes: Bounded 3D containers. Think of them as glass boxes your 3D content lives inside. Users can reposition them but cannot walk through them.
• Immersive Spaces: Full or mixed-reality experiences that take over the user's entire field of view. These are where spatial computing gets genuinely compelling, but they also require the most design and engineering effort.

What Works Well

The visionOS simulator in Xcode is excellent. You can test window management, volumes, gaze interactions, and even simulate hand gestures without owning a headset. Reality Composer Pro provides a visual workflow for 3D scene composition that designers can actually use. The entire pipeline from Xcode to TestFlight to App Store is the same one iOS developers already know, which dramatically reduces operational overhead.

What Hurts

You are locked into Swift and Apple's frameworks. No Kotlin, no Java, no cross-compilation. Building a visionOS app requires a Mac with Apple Silicon, Xcode 16+, and ideally a Vision Pro for final testing (the simulator misses important ergonomic issues). The developer program costs $99/year, and the hardware is $2,499 for Vision Pro 2. That is $2,598 before you write a line of code.

Google's Android XR platform launched in late 2025 with the Samsung Project Moohan headset, and the SDK has matured rapidly through 2026. The philosophy mirrors standard Android development: give developers multiple framework options, lean on open standards, and let OEMs differentiate on hardware.

Core Frameworks

Jetpack XR is the primary SDK for building spatial apps on Android XR. It extends Android's Jetpack libraries with spatial primitives: spatial panels (the equivalent of visionOS windows), orbiter menus that float around panels, and spatial environments that render virtual surroundings. If you know Jetpack Compose, Jetpack XR will feel natural. You define spatial layouts in Kotlin using composable functions, and the runtime handles placement, occlusion, and interaction.

Compose for XR specifically brings Jetpack Compose's declarative UI model into three-dimensional space. You can take an existing Compose-based Android app and promote its UI panels into spatial panels with relatively minimal code changes. Google claims a "few dozen lines" of spatial code can turn a flat app into a spatial one. In practice, we have found it takes more like 200 to 500 lines to get something that feels intentional rather than auto-adapted, but the starting point is genuinely easy.

ARCore for XR provides the environmental understanding layer: plane detection, depth sensing, mesh reconstruction, light estimation, and persistent anchors. Performance varies more across devices than Apple's ARKit because hardware capabilities differ between OEM headsets and glasses. The Samsung Moohan's depth sensor produces clean meshes, but cheaper XR glasses struggle with complex environments.

OpenXR Compatibility is a major differentiator. Android XR supports the OpenXR standard, which means engines like Unity and Unreal can target Android XR headsets through the same rendering pipeline they use for Meta Quest. This is a massive advantage for studios that already have OpenXR-based apps and want to reach Android XR users without a full rewrite.

What Works Well

The barrier to entry is lower. Android Studio (free, runs on Mac, Windows, or Linux) provides an Android XR emulator that simulates spatial panels, hand tracking, and passthrough environments. You write Kotlin, which most Android teams already know. The Samsung Moohan at $1,299 is half the cost of Vision Pro 2, and cheaper XR glasses from partners are expected below $500 by late 2026.

What Hurts

The ecosystem is fragmented. Different OEM headsets have different tracking capabilities, display resolutions, and sensor arrays. Testing on one device does not guarantee your app works correctly on another. The Jetpack XR APIs are still evolving, with breaking changes in minor releases through early 2026. Documentation is thinner than Apple's, and spatial-specific Stack Overflow answers are sparse. Google's track record of abandoning platforms (Daydream, Google Glass Enterprise Edition, Stadia) also gives developers understandable pause.

The day-to-day developer experience matters more than feature lists when your team is shipping on a deadline. Here is how the two platforms compare in practice.

IDE and Tooling

Apple: Xcode 16 with Reality Composer Pro integrated. The 3D scene editor is mature, supports drag-and-drop asset placement, material editing, and physics configuration. Xcode's SwiftUI previews work for spatial windows and volumes (not immersive spaces). Instruments provides spatial-specific profiling for GPU, thermal throttling, and hand-tracking latency. The downside: Xcode only runs on macOS, and Reality Composer Pro crashes more than Apple would like to admit when handling complex USDZ scenes with 100K+ polygons.

Google: Android Studio Narwhal (2025.1) with the XR plugin. The spatial layout preview lets you see how Compose for XR panels will arrange in 3D space. The emulator supports six-degrees-of-freedom head tracking simulation, hand gesture input via mouse, and passthrough camera simulation using pre-recorded room scans. Android Studio runs on Mac, Windows, and Linux. The XR plugin occasionally fails to render spatial previews, requiring IDE restarts.

Simulator and Emulator Quality

Apple's visionOS simulator is better. It renders at near-device fidelity, supports multi-window layouts, gaze simulation via trackpad, and pinch gesture simulation via mouse clicks. You can build and test 80% of your app in the simulator alone.

Google's Android XR emulator is functional but rougher. Spatial panel placement works well, but hand-tracking simulation feels clunky compared to Apple's approach. The emulator struggles with complex passthrough environments and occasionally drops frames during scene transitions. Plan to test on a real Moohan headset more frequently than you would test on a real Vision Pro.

Testing and QA

Both platforms require physical device testing for anything involving hand tracking, eye tracking, or spatial audio. Automated UI testing is limited on both. Apple's XCTest framework has basic support for spatial interaction recording, but it misses edge cases around gaze targeting. Google's Espresso does not yet have XR-specific extensions, so most teams write custom test harnesses using the Android XR Input Simulation API.

Budget 30% more QA time for spatial apps compared to flat-screen mobile apps. Users interact with 3D interfaces in unpredictable ways, and comfort issues (eye strain, motion sickness from poorly anchored objects) only surface during real-world testing sessions of 30 minutes or longer.

Building natively for both platforms doubles your development cost. Cross-platform tools can reduce that, but they come with real tradeoffs.

Unity

Unity is the most production-ready cross-platform option for spatial computing in 2026. The PolySpatial plugin lets you build visionOS apps using Unity's editor and C# scripting, rendering through RealityKit under the hood. For Android XR, Unity targets OpenXR directly. A single Unity project can produce builds for Vision Pro, Samsung Moohan, and Meta Quest with platform-specific adjustments.

The catch: Unity's PolySpatial layer adds overhead. Rendering performance on visionOS is 15 to 25% worse than native RealityKit, and some visionOS-specific features (ornaments, certain SharePlay interactions) are not accessible through Unity. The licensing cost also adds up. Unity Pro is $2,040/year per seat, and the visionOS plugin requires Pro or Enterprise. For a team of four developers, that is over $8,000/year in licensing before you count asset store purchases.

WebXR

WebXR lets you build spatial experiences that run in the browser on any XR headset. Safari on visionOS and Chrome on Android XR both support the WebXR Device API. You use Three.js, Babylon.js, or A-Frame for 3D rendering, and standard web technologies (HTML, CSS, JavaScript) for UI.

WebXR apps avoid app store review and distribution friction entirely. Users open a URL and they are in your spatial experience. The performance ceiling is lower than native (no access to advanced hand tracking, limited spatial audio, no scene understanding), but for product demos, virtual showrooms, educational content, and marketing experiences, WebXR is often the right choice. Development costs run 40 to 60% less than native spatial apps.

React Native XR

React Native does not officially support spatial computing, but community-driven experiments are progressing. The react-native-xr package (still in alpha) wraps Jetpack XR components for Android XR, and a separate visionOS target is in early development. We do not recommend shipping production apps on React Native XR yet. The abstraction layer is too leaky, performance is inconsistent, and the maintainer community is small. Revisit in mid-2027.

For most teams building serious spatial apps, the practical choice in 2026 is: build natively on your primary platform, use Unity if you need both platforms from day one, or use WebXR for lightweight experiences that do not require deep hardware integration.

Your platform choice is ultimately constrained by who your users are and what hardware they own. Here is where things stand in mid-2026.

Hardware Comparison

• Apple Vision Pro 2: $2,499, dual micro-OLED displays at 3660x3200 per eye, M4 chip, 12 cameras and sensors, 2.5 hours battery life, 450g. Available in 12 countries. Estimated install base: 1.8 to 2.2 million units worldwide.
• Samsung Project Moohan: $1,299, dual LCD displays at 2800x2400 per eye, Snapdragon XR2+ Gen 2, 6 cameras, 3 hours battery life, 490g. Available in 28 countries. Estimated install base: 2.5 to 3 million units.
• Android XR Smart Glasses (various OEMs): $399 to $799, single waveguide display, limited FOV (30 to 50 degrees), camera and microphone input, 4+ hours battery life, 45 to 80g. Combined install base: approximately 1.5 million units.

Apple's display quality is noticeably superior. The micro-OLED panels produce deeper blacks, higher contrast, and virtually eliminate the screen-door effect. The Moohan's LCD panels are good but visibly lower fidelity in side-by-side comparisons. For apps where visual quality is paramount (medical imaging, luxury retail, architecture visualization), Vision Pro 2 is the better target.

Samsung wins on price, availability, and install base. The $1,200 price gap matters enormously for enterprise deployments where you are equipping 50 or 100 employees. At $1,299 per headset versus $2,499, that is a $60,000 difference for a 50-unit deployment.

App Distribution

visionOS apps are distributed through the App Store, using the same review process and 30% commission (15% for small businesses under $1M revenue) as iOS apps. TestFlight works for beta distribution. Enterprise distribution via MDM is available for B2B apps that do not belong on the public store.

Android XR apps go through Google Play with the standard 15% commission on the first $1M in revenue, then 30% after that. Sideloading is supported, which matters for enterprise deployments and internal tools. Google Play's review process is faster than Apple's (hours versus days), and you can push updates without re-review for most changes.

One practical difference: Apple requires all visionOS apps to pass a "comfort review" that checks for motion-sickness-inducing patterns (rapid camera movement, unstable anchors, flickering). This adds 2 to 5 days to the review cycle for immersive space apps. Google has no equivalent requirement, which means more uncomfortable apps reach the store but your review cycle is shorter.

After shipping spatial apps across both platforms, here is our opinionated guidance on which platform to prioritize for different use cases.

Enterprise and Training Apps

Start with Android XR. The lower hardware cost makes fleet deployments feasible, sideloading simplifies internal distribution, and Kotlin/Java expertise is more common in enterprise development teams. Samsung's Moohan has better enterprise management features (Knox integration, MDM profiles, kiosk mode). Build for visionOS second if your client specifically requests Apple hardware or if the use case demands the highest visual fidelity (surgical training, luxury product visualization).

Consumer Social and Productivity Apps

Start with visionOS. Apple's spatial computing users skew toward early adopters with high spending power. The App Store generates higher per-user revenue than Google Play (this pattern holds from mobile and applies to XR). SwiftUI for spatial makes it faster to build polished window-based productivity apps. Apple's SharePlay API enables compelling multi-user experiences that Android XR does not yet match.

Gaming and Immersive Entertainment

Use Unity and target both platforms simultaneously. Gaming benefits most from cross-platform reach, and Unity's spatial rendering is good enough for most game art styles. The OpenXR compatibility on Android XR means your Unity game also runs on Meta Quest with minimal additional work, tripling your addressable market. Budget $150K to $300K for a polished spatial game with 2 to 4 hours of content.

Marketing and Short-Form Experiences

Use WebXR. If you are building a product configurator, virtual showroom, or branded AR experience, a web-based approach avoids app store friction entirely. Users tap a link and they are in your experience. Development costs run $30K to $80K depending on complexity, versus $100K+ for native spatial apps. You reach both platforms and Meta Quest from a single codebase.

Your Next Step

Spatial computing is past the hype phase and into the "real products for real users" phase. The platform you choose depends on your users, your team's skills, and your budget. If you are evaluating a spatial app and want a concrete technical plan with cost estimates tailored to your use case, book a free strategy call with our team. We have built on both platforms and can help you avoid the expensive mistakes we have seen other teams make.