What is the difference between on-device AI and cloud AI?
The difference between on-device AI and cloud AI is where the processing happens. On-device AI runs directly on your laptop, desktop, or phone, using its own processors. Cloud AI sends your request over the internet to remote servers in a data center, processes it there, and sends the result back.
Each approach has clear strengths. On-device AI is usually better for privacy, speed of response, and working offline. Cloud AI is usually better for raw capability, because data centers can run much larger AI models than a personal device can hold. Many of today's AI tools combine both.
This guide explains how local AI processing and cloud AI work, how they compare on privacy and latency, and how to decide which one fits a given task.
What is on-device AI?
On-device AI, also called local AI or edge AI, is artificial intelligence that runs entirely on your own device. The AI model is stored on the computer or phone, and your data is processed there instead of being sent to an outside server.
How local AI processing works
Local AI processing relies on the device's own hardware. On an AI PC, that work is shared among three processors:
The NPU runs sustained AI features efficiently, such as video-call effects and live captions. Learn more in our NPU guide.
The GPU handles heavier AI work, such as generating or editing images.
The CPU coordinates tasks and handles quick, lightweight AI jobs.
Because a laptop has far less memory and computing power than a data center, on-device AI usually runs smaller, optimized models. These include small language models (SLMs), which are compact versions of the large language models behind cloud chatbots. For example, Microsoft's Phi Silica is a small language model built into Windows 11 Copilot+ PCs. It runs on the NPU and handles tasks such as summarizing, rewriting, and short-form text generation on the device rather than in the cloud (Microsoft Support).
Examples of on-device AI
Background blur, auto-framing, and voice focus on video calls
Live captions and real-time translation
Face or fingerprint unlock
Photo enhancement and object removal
Rewriting and summarizing text with a built-in small language model
Predictive text and voice typing
What is cloud AI?
Cloud AI is artificial intelligence that runs on remote servers owned by a service provider. When you use a cloud AI tool, your device sends your request over the internet, powerful hardware in a data center processes it, and the answer is sent back to you.
How cloud AI works
You type a prompt, upload a file, or speak a request on your device.
Your device sends that input to the provider's servers over the internet.
Large AI models running on banks of high-end GPUs and AI accelerators process the request.
The result returns to your device, usually within seconds.
The main advantage of cloud AI is scale. Data centers can run the largest and most capable AI models, which need far more memory and computing power than any laptop has. Cloud providers can also update models frequently, so you get improvements without changing your hardware.
Examples of cloud AI
Web-based AI chatbots and AI assistants
High-resolution image and video generation services
AI search and research tools
Cloud-based transcription and meeting summaries
Enterprise AI tools that analyze large company datasets
On-device AI vs. cloud AI: side-by-side comparison
On-device AI trades some raw capability for privacy, speed, and independence from the internet. Cloud AI trades some privacy and responsiveness for access to the most powerful models.
On-device AI | Cloud AI | |
|---|---|---|
Where it runs | Your laptop, desktop, or phone | Remote servers in a data center |
Privacy | Data can stay on your device | Data is sent to and processed by a provider |
Latency | Low, with no network round trip | Depends on connection speed and server load |
Works offline | Yes, for supported features | No, it needs an internet connection |
Model size and capability | Smaller, optimized models | The largest, most capable models |
Best at | Real-time, repeated, and personal tasks | Complex reasoning, research, and large-scale generation |
Ongoing cost | Included with the device | Often a subscription or usage-based fee |
Battery impact | Low when run on an NPU | Low on the device, but needs a constant connection |
Updates | Arrive through software and driver updates | Providers can update models at any time |
On-device AI and privacy
On-device AI is generally more private than cloud AI because your data does not have to leave your device to be processed. When a video-call effect, caption, or text summary runs locally, the audio, video, or document stays on your computer.
With cloud AI, your input travels to a provider's servers. Reputable providers encrypt data in transit and publish policies on how long they keep it and whether they use it to improve their models. Even so, sending data off the device adds steps where it could be stored, reviewed, or exposed.
Local processing does not make a device automatically secure. Keep these points in mind:
On-device features can still store data. Some local AI features save screenshots, transcripts, or history on the device. Review their settings and turn off what you do not need.
Many tools switch to the cloud. Some apps run simple requests locally and send harder ones to the cloud. Check each tool's privacy settings to see when that happens.
Device security still matters. Strong sign-in, encryption, and regular updates protect data stored by on-device AI.
For businesses, on-device AI can help keep sensitive information, such as customer records or internal documents, inside the organization's own devices. Our AI privacy and security guide covers these risks in more detail.
On-device AI and latency
Latency is the delay between making a request and getting a response. On-device AI typically has lower latency because the request never has to travel across the internet and back.
Cloud AI latency depends on several factors outside your device:
Network speed. A slow or unstable connection adds delay to every request.
Distance to the data center. Data takes longer to travel to servers that are farther away.
Server demand. Busy services may queue requests during peak times.
Low latency matters most for real-time features. Background blur, noise suppression, and live captions must keep pace with live audio and video, where even a short delay is noticeable. These features almost always run on the device.
Lower latency does not always mean a faster finished result, though. A cloud model can take longer to start but still complete a complex task, such as writing a detailed report, faster than a smaller local model could. For quick, repeated, or real-time tasks, on-device AI usually feels faster. For large, complex tasks, the cloud's extra computing power often wins.
What is hybrid AI?
Hybrid AI combines on-device and cloud processing, sending each task to the place best suited to handle it. Most modern AI PCs and AI tools work this way rather than relying on only one approach.
A typical hybrid setup works like this:
Quick and private tasks stay local. Video-call effects, captions, and short text rewrites run on the device for speed and privacy.
Heavy tasks go to the cloud. Complex research, long documents, and high-resolution image generation use larger cloud models.
The device prepares the request. Local AI can tidy up or shorten a request before it is sent, so less data has to leave the device.
Hybrid AI gives you a balance: the responsiveness and privacy of local processing for everyday tasks, with the power of the cloud available when you need it. Some developer platforms, for example, let apps choose between a local small language model and a cloud-hosted large language model (InfoWorld).
When to use on-device AI vs. cloud AI
Choose on-device AI when privacy, speed, or offline access matters most. Choose cloud AI when you need the most capable model for a complex task.
Task or situation | Better fit | Why |
|---|---|---|
Video calls with background blur or noise removal | On-device | Needs real-time response and runs for long periods |
Live captions and translation | On-device | Must keep pace with live speech |
Working with confidential documents | On-device | Data stays on your computer |
Working on a flight or with poor Wi-Fi | On-device | Does not need an internet connection |
Quick rewrites and short summaries | On-device | Small models handle these tasks well |
In-depth research or long reports | Cloud | Benefits from the largest models and web access |
High-resolution image or video generation | Cloud, or a powerful local GPU | Requires heavy computing power |
Analyzing large company datasets | Cloud | Needs data-center scale storage and compute |
If you are buying a computer, an AI PC with a capable NPU gives you both options: on-device AI for everyday tasks and full access to cloud AI tools when you need them.
On-device AI vs. cloud AI frequently asked questions
Is on-device AI the same as edge AI?
They are closely related. Edge AI is a broader term for AI that runs near where data is created, such as on a phone, laptop, security camera, or factory sensor, instead of in a central data center. On-device AI is a type of edge AI that runs directly on your personal device.
Is on-device AI more secure than cloud AI?
On-device AI reduces some risks because your data does not travel to outside servers. However, security still depends on how the device is protected. Strong sign-in, disk encryption, and regular updates help keep data stored by local AI features safe. Learn more in our AI privacy and security guide.
Does on-device AI work without the internet?
Yes, for features designed to run locally. Video-call effects, live captions, and some text tools keep working offline. Cloud-based tools and any feature that needs current web information still require a connection.
Why can't all AI run on my device?
The most capable AI models are too large for personal devices. They need far more memory and computing power than a laptop provides, so they run in data centers. On-device AI uses smaller, optimized models that fit within a device's limits.
Does on-device AI drain my battery?
On-device AI uses little battery when it runs on an NPU, which is designed for efficient AI processing. The same task running on a CPU or GPU typically uses more power. See our NPU guide for details.
Is cloud AI free?
Some cloud AI tools offer free tiers, but many charge a subscription or usage fee for advanced models and higher limits. On-device AI features are usually included with the device and operating system at no extra cost.
Do I need an AI PC to use on-device AI?
Many devices can run some AI locally, but an AI PC with an NPU runs it far more efficiently. Some features, including those reserved for Copilot+ PCs, require an NPU rated above 40 TOPS. Our AI PC guide explains what to look for.
How can I tell whether an AI feature runs on my device or in the cloud?
Check the app's settings or privacy documentation, which usually explains where data is processed. A good clue is whether the feature works with your internet connection turned off. If it does, it runs on the device.
Related AI glossary guides
AI glossary: Definitions of key AI terms in one place
AI PCs: What makes a PC an AI PC and what to look for
Neural processing units (NPUs): The processor that powers on-device AI
Large language models: How the models behind cloud and local AI work
AI privacy and security: How to protect your data when using AI
AI features: Everyday AI capabilities and where they run
