Gemini Nano Android: On-Device AI Guide (2026)

What is Gemini Nano?

Gemini Nano is Google's most efficient AI model, designed to run natively on Android devices without requiring cloud connectivity. While Gemini Pro powers web and cloud applications and Gemini Ultra handles the most complex tasks, Nano brings AI processing directly to your phone's hardware.

Key Differentiators

Gemini Nano comes in two variants:

• Nano-1: 1.8 billion parameters, optimized for low-memory devices
• Nano-2: 3.25 billion parameters, for devices with higher memory capacity

Both use 4-bit quantization and are created through distillation from larger Gemini models, inheriting their capabilities while fitting mobile hardware constraints.

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Supported Devices

Google Pixel

Samsung Galaxy

• Galaxy S24, S24+, S24 Ultra, S24 FE
• Galaxy S25, S25+, S25 Ultra (multimodal support)
• Galaxy Z Fold 6, Z Flip 6
• Galaxy Z Fold7 (upcoming)

Other Manufacturers

• Xiaomi 15
• Motorola Razr 60 Ultra
• Honor Magic Series
• Devices with MediaTek Dimensity, Qualcomm Snapdragon, or Google Tensor platforms with NPU support

Hardware Requirements

• Android 9+ with 2GB+ RAM
• AI accelerator (NPU/TPU) in chipset
• ~1GB storage for model download

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On-Device AI Capabilities

Text Processing

Summarization: Condense documents up to 3,000 words into bullet points. Supports English, Japanese, and Korean.

Smart Replies: Context-aware response suggestions based on recent conversation. Works in Google Messages, WhatsApp, Line, and KakaoTalk via Gboard.

Rewriting: Adjust tone and style—formal, casual, excited, or even Shakespearean. Magic Compose in Google Messages uses this for creative message drafting.

Proofreading: Grammar and spelling correction in seven languages: English, Japanese, German, French, Italian, Spanish, and Korean.

Multimodal Capabilities (Pixel 9+)

Image Description: Generate alt-text for accessibility. TalkBack uses this to describe images for visually impaired users.

Speech Recognition: On-device transcription powering Pixel Recorder and Call Notes.

Audio Processing: Real-time analysis for features like Scam Detection.

Pixel-Exclusive Features

• Pixel Screenshots: AI-powered search through your screenshots using natural language
• Call Notes: Automatic transcription and summarization of phone calls
• Scam Detection: Real-time fraud detection during calls—all processed locally
• Pixel Recorder Summaries: 3-bullet summaries of recordings over 30 minutes
• Magic Cue: Context-aware suggestions throughout the OS

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Enabling Gemini Nano

Pixel 8/8a (Manual Enablement)

Gemini Nano requires manual activation on Pixel 8 and 8a:

1. Update your device to the June 2024 update or later

2. Enable Developer Options:

Settings → About Phone → Tap "Build Number" 7 times

1. Activate AICore:

Settings → System → Developer Options → Search "AICore Settings"
Toggle ON "Enable On-Device GenAI Features"

1. Wait for download: The ~1GB Gemini Nano model downloads in the background. This may take 15-30 minutes on Wi-Fi.

Note: Manual enablement may cause instability or battery impact. Features roll out gradually.

Pixel 9+ and Samsung Galaxy

Gemini Nano is pre-enabled and automatically available. No user action required.

Checking Availability

For developers, check if Gemini Nano is available:

val generativeModel = Generation.getClient()
val status = generativeModel.checkStatus()

when (status) {
    FeatureStatus.AVAILABLE -> {
        // Ready to use
    }
    FeatureStatus.DOWNLOADABLE -> {
        // Model needs to be downloaded
        generativeModel.download().collect { downloadStatus ->
            when (downloadStatus) {
                is DownloadStatus.InProgress -> {
                    println("Download: ${downloadStatus.progress}%")
                }
                is DownloadStatus.Downloaded -> {
                    println("Model ready")
                }
            }
        }
    }
    FeatureStatus.UNAVAILABLE -> {
        // Device not supported
        println("Gemini Nano not available on this device")
    }
}

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Developer Integration

ML Kit GenAI APIs (Recommended)

Google's ML Kit provides the primary API for Gemini Nano integration:

Add Dependency:

// build.gradle.kts
dependencies {
    implementation("com.google.mlkit:genai-prompt:1.0.0-beta1")
    // High-level APIs
    implementation("com.google.mlkit:genai-summarization:1.0.0-beta1")
    implementation("com.google.mlkit:genai-proofreading:1.0.0-beta1")
}

Summarization API

Summarize long documents into bullet points:

import com.google.mlkit.genai.summarization.Summarization
import com.google.mlkit.genai.summarization.SummarizationRequest

val summarizer = Summarization.getClient()

// Check availability
if (summarizer.checkStatus() == FeatureStatus.AVAILABLE) {
    val request = SummarizationRequest.builder()
        .setInputText(longDocument)
        .setOutputFormat(OutputFormat.BULLET_POINTS)
        .build()

    // Streaming response
    summarizer.generateSummary(request).collect { result ->
        when (result) {
            is SummaryResult.Partial -> {
                updateUI(result.text)
            }
            is SummaryResult.Complete -> {
                finalUI(result.fullText)
            }
        }
    }
}

Proofreading API

Fix grammar and spelling errors:

import com.google.mlkit.genai.proofreading.Proofreading

val proofreader = Proofreading.getClient()

val corrections = proofreader.proofread(
    text = "Ther are many mistaks in this sentance.",
    language = Language.ENGLISH
)

corrections.collect { result ->
    result.corrections.forEach { correction ->
        println("${correction.original} → ${correction.suggested}")
        // "Ther" → "There"
        // "mistaks" → "mistakes"
        // "sentance" → "sentence"
    }
}

Prompt API (Custom Prompts)

For custom use cases, the low-level Prompt API provides direct access:

import com.google.mlkit.genai.prompt.Generation
import com.google.mlkit.genai.prompt.generateContentRequest

val generativeModel = Generation.getClient()

// Text-only prompt
val response = generativeModel.generateContent(
    generateContentRequest {
        text("Explain quantum computing in simple terms")
        temperature(0.3f)
        topK(10)
        maxOutputTokens(256)
    }
)

// Multimodal prompt (Pixel 9+)
val multimodalResponse = generativeModel.generateContent(
    generateContentRequest(
        ImagePart(bitmapImage),
        TextPart("Describe this image in detail")
    ) {
        temperature = 0.2f
        maxOutputTokens = 256
    }
)

Streaming Responses

For better UX, use streaming to display results as they generate:

generativeModel.generateContentStream(request).collect { chunk ->
    when (chunk) {
        is GenerateContentResponse.Partial -> {
            appendToTextView(chunk.text)
        }
        is GenerateContentResponse.Complete -> {
            finishGeneration()
        }
        is GenerateContentResponse.Error -> {
            handleError(chunk.error)
        }
    }
}

---

AICore Architecture

AICore is Android's system service (introduced in Android 14) that manages AI foundation models:

Responsibilities

• Model Distribution: Handles Gemini Nano download and updates
• Hardware Acceleration: Routes inference to NPU/TPU for optimal performance
• Memory Management: Efficiently loads/unloads models based on usage
• Privacy Protection: Follows Private Compute Core principles

How It Works

┌─────────────────────────────────────────────────────────┐
│                     Your App                             │
├─────────────────────────────────────────────────────────┤
│                   ML Kit GenAI APIs                      │
│  (Summarization, Proofreading, Prompt, etc.)            │
├─────────────────────────────────────────────────────────┤
│                      AICore                              │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐  │
│  │   Model      │  │   NPU/TPU    │  │   Privacy    │  │
│  │   Manager    │  │   Dispatch   │  │   Sandbox    │  │
│  └──────────────┘  └──────────────┘  └──────────────┘  │
├─────────────────────────────────────────────────────────┤
│                  Gemini Nano Model                       │
│  (Nano-1: 1.8B params or Nano-2: 3.25B params)         │
├─────────────────────────────────────────────────────────┤
│                Hardware Accelerator                      │
│  (Tensor TPU / Snapdragon NPU / MediaTek APU)          │
└─────────────────────────────────────────────────────────┘

LoRA Adapter Support

AICore supports Low-Rank Adaptation for fine-tuning Gemini Nano on specific tasks. Google uses this for Pixel Recorder summaries, where a custom LoRA adapter improves audio transcription quality.

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Privacy and Security

Data Protection Guarantees

Gemini Nano offers strong privacy by design:

Private Compute Core Integration

AICore follows Private Compute Core principles:

• Network isolation: Model cannot communicate externally
• Restricted binding: Isolated from other apps
• Open-source APIs: Transparency for security audits

Compliance Benefits

• GDPR compliant: Data never leaves the device
• CCPA compliant: Complete data sovereignty
• Enterprise-ready: Suitable for sensitive business applications
• Healthcare compatible: Works with HIPAA-regulated apps

Security Features

• Differential privacy protects against model extraction
• Hardware-level security via ARM TrustZone
• Model weights encrypted at rest
• Protected execution environment

---

App Integration Examples

Gboard Smart Reply

User receives WhatsApp message: "Want to grab lunch tomorrow?"

Gemini Nano analyzes context and suggests:
→ "Sure, sounds good! What time?"
→ "Sorry, I'm busy tomorrow"
→ "Let me check my schedule"

Supported apps: WhatsApp, Line, KakaoTalk (US English only)

Google Messages Magic Compose

Draft: "I can't make it to the meeting"

Available styles:
→ Formal: "I regret to inform you that I will be unable to attend the meeting"
→ Casual: "Hey, can't make it to the meeting today"
→ Excited: "OMG I'm SO sorry but I can't make it!"
→ Shakespearean: "Alas, mine attendance at the gathering shall not be"

Pixel Recorder

// After recording ends
val transcript = recorder.getTranscript()
val summary = recorder.getSummary()

// Returns 3-bullet summary:
// • Main discussion points about project timeline
// • Action items: review documents by Friday
// • Next meeting scheduled for Monday at 2pm

Impact: 24% boost in user engagement with AI-powered summarization.

Call Notes

Phone call with doctor's office (15 minutes)

Gemini Nano generates:
• Appointment confirmed for March 15 at 10am
• Bring insurance card and ID
• Arrive 15 minutes early for paperwork
• Fasting required before blood test

All processing on-device—audio never leaves your phone.

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Performance and Limitations

Performance Metrics

Context Limitations

• Total context window: 4,096 tokens
• Per-prompt limit: 1,024 tokens
• Summarization max: ~3,000 words
• No persistent memory: Context resets between sessions

What Gemini Nano Cannot Do

❌ Complex multi-step reasoning comparable to cloud models ❌ Long-form content generation (essays, articles) ❌ Image or video generation (different model required) ❌ Real-time knowledge (no internet access) ❌ Multi-turn conversations with persistent context ❌ Fine-grained image details in complex scenes

Device-Specific Limitations

• Pixel 9a: Nano XXS with reduced capabilities, text-only
• Pixel 8/8a: No multimodal support
• Some features Pixel-exclusive: Screenshots, Call Notes, Scam Detection

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Gemini Nano vs Apple Intelligence

Key Differences:

• Apple Intelligence is more polished for casual users with system-wide integration
• Gemini Nano offers broader device support and developer flexibility
• Apple uses Private Cloud Compute for advanced features; Google keeps Nano fully local
• Gemini Nano is accessible to third-party developers via ML Kit

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2025-2026 Roadmap

Current State (2026)

• ML Kit GenAI APIs: Officially launched at I/O 2025
• Nano v3: Latest version on Pixel 10 with Tensor G5
• Expanded device support: Beyond Pixel to major Android manufacturers
• Full multimodal: Images and audio processing on supported devices

Upcoming Developments

Assistant Replacement (2026):

• Gemini replacing Google Assistant on mobile devices
• Android Auto support by March 2026
• Transition requires Android 9+ with 2GB+ RAM

Platform Expansion:

• Google TV integration (TCL first, then broader)
• Smartwatch support
• Smart home devices
• Car infotainment systems

Developer Improvements:

• Simplified context window management
• Enhanced token limits
• More LoRA adapter support
• Expanded language coverage

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Getting Started Checklist

For Developers

// 1. Add ML Kit dependency
implementation("com.google.mlkit:genai-prompt:1.0.0-beta1")

// 2. Check device support
val status = Generation.getClient().checkStatus()

// 3. Handle download if needed
if (status == FeatureStatus.DOWNLOADABLE) {
    Generation.getClient().download().collect { /* ... */ }
}

// 4. Use high-level APIs for common tasks
val summarizer = Summarization.getClient()
val proofreader = Proofreading.getClient()

// 5. Use Prompt API for custom prompts
val generativeModel = Generation.getClient()
generativeModel.generateContent(request)

Best Practices

• Check status before use: Handle UNAVAILABLE gracefully
• Use streaming: Better UX than waiting for complete response
• Keep prompts short: Stay under 1,024 tokens per prompt
• Provide fallback: Cloud API for unsupported devices
• Test on multiple devices: Performance varies by hardware

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Key Takeaways

1. Gemini Nano runs fully on-device—no internet required, complete privacy
2. Wide device support—Pixel 8+, Samsung S24+, Xiaomi, Motorola, and more
3. ML Kit GenAI APIs are the official integration path for developers
4. 1.8B-3.25B parameters with 4-bit quantization fits mobile hardware
5. Sub-100ms latency on flagship devices with NPU acceleration
6. Privacy by design—GDPR/CCPA compliant, works with encrypted apps
7. Limited context (4,096 tokens) means targeted use cases, not general chat

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Next Steps

1. Compare local AI options for desktop
2. Check VRAM requirements for running larger models
3. Build AI agents for automation tasks
4. Explore WebLLM for browser-based AI
5. Understand small language models across platforms

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Gemini Nano represents Google's vision for ubiquitous, private AI. By running entirely on-device, it enables instant responses, complete privacy, and offline operation—features impossible with cloud AI. For developers, ML Kit GenAI APIs provide straightforward integration. For users, features like Smart Reply, Call Notes, and Scam Detection showcase what on-device AI can do today. As more devices support Gemini Nano and capabilities expand, on-device AI becomes the default rather than the exception.