What makes Nano AI so fast on mobile devices

Artificial Intelligence (AI) is no longer something that only works in powerful data centres; it now lives in your phone. From instant translations to photo editing, today’s smartphones can run Nano AI models that handle complex tasks in seconds, without always requiring an internet connection.

Nano AI refers to small, efficient AI models designed to run directly on mobile devices. These models make AI faster, more private, and less dependent on cloud servers. Companies like Google, Apple, and Qualcomm are leading this change, using Nano AI to improve how we interact with our phones.

So, what exactly makes Nano AI so fast, and how is it changing mobile technology?

What is Nano AI?

Nano AI refers to lightweight, on-device AI systems designed to operate seamlessly on smartphones, tablets, and wearables. Unlike traditional AI that sends data to remote servers for processing, Nano AI performs all calculations locally on the device.

This makes tasks faster, safer, and more responsive. Instead of waiting for a cloud server, users get real-time results when translating text, generating messages, or enhancing photos.

× Click to Read More

For example, Google’s Gemini Nano, found in Pixel phones, can summarise recordings, write texts, and suggest replies entirely on the device. Similarly, Apple’s Neural Engine and Samsung’s Galaxy AI process tasks locally for instant results without sharing data externally.

This marks a new trend: AI that lives closer to users faster, smarter, and more energy-efficient.

Why Nano AI is so fast

1. Smaller and smarter models

Traditional AI models are huge, with billions of parameters that need advanced hardware to run. Nano AI models are built differently. Engineers use special techniques such as quantisation, distillation, and pruning to reduce their size while keeping accuracy high.

• Quantisation makes data lighter by turning 32-bit numbers into smaller 8-bit or 4-bit ones.
  
• Distillation trains a smaller “student” model to copy a larger “teacher” model.
  
• Pruning removes unnecessary data from the model.
  

Together, these methods make AI models small enough to run smoothly on phones without losing much performance.

2. Special chips for AI tasks

Modern phones now include Neural Processing Units (NPUs) chips built specifically for AI. These work faster and use less energy than regular processors.

Companies like Qualcomm, Apple, and Google have developed powerful AI chips. For instance, Qualcomm’s Snapdragon AI Engine can perform over 45 trillion operations per second, while Apple’s Neural Engine handles 38 trillion. Google’s Tensor G3 chip, used in Pixel phones, is designed to run Gemini Nano efficiently.

These chips give Nano AI its speed and allow phones to handle tasks like speech recognition and image enhancement instantly.

3. On-device processing 

Nano AI works on the principle of edge computing, meaning tasks are processed on the device rather than in the cloud.

Normally, cloud-based AI requires data to travel to a remote server and back, which creates delays. With Nano AI, that round trip is eliminated; the phone does the work itself.

This makes the experience almost instant and also improves privacy, since personal data doesn’t need to leave the device.

4. Energy efficiency

AI can easily drain a battery, but Nano AI models are designed to be energy-efficient. By reducing model size and using specialised hardware, they use less power and stay cool.

Some chips can even switch between high-performance and power-saving modes depending on the task. This means users can enjoy fast, intelligent features without worrying about battery life.

Related article: How Gemini Nano brings generative AI to low-end phones

Real-world uses of Nano AI

Nano AI is already part of our everyday smartphone experience:

• Voice assistants like Gemini Nano and Siri can now respond instantly, even offline.
  
• Cameras use Nano AI to detect scenes, improve images, and apply effects in real time.
  
• Messaging apps generate smart replies and summaries directly on your device.
  
• Accessibility tools provide live translations and transcriptions.
  
• Security features like face and fingerprint recognition run locally for better privacy.
  

These examples show how Nano AI makes phones faster, smarter, and safer.

Why Google leads in Nano AI

While several companies are investing in on-device AI, Google stands out with its Gemini Nano model. Gemini Nano powers Pixel-exclusive features such as Smart Reply, Summarise in Recorder, and context-aware suggestions, all running on-device. Google’s combination of its Tensor G3 chip and Gemini AI models ensures smooth and efficient performance.

This focus on on-device AI not only improves user experience but also addresses privacy and connectivity issues, especially in areas with weak internet access.

The Future of Nano AI

Nano AI represents the next stage of AI evolution. As chips become faster and AI models smaller, devices will rely less on the cloud and more on local processing.

In the future, your smartphone could act as a personal AI hub learning your habits, predicting needs, and working privately without sending data online. Beyond phones, Nano AI will also power wearables, smart glasses, and IoT devices.

For users, this means faster, more private, and more reliable technology. For developers, it’s a new era focused on efficient, human-centred AI. The future of intelligence is already here, and it fits in your pocket.

× Click to watch