When using artificial intelligence, a **technical question** has very concrete consequences: does the AI run « in the cloud, » on a provider’s servers, or « locally, » on your own machine? This choice affects confidentiality, cost, performance, and autonomy. Understanding the difference helps you choose the right approach based on your needs. This guide clearly compares local AI and cloud AI, without jargon.
Two ways to run AI
Cloud AI runs on a provider’s powerful servers: you send your request, processing happens remotely, and the response comes back. Local AI, on the other hand, runs directly on your device: nothing leaves your machine. These two approaches serve **different needs**, and the right choice depends on what matters most to you: simplicity, confidentiality, cost, or power.
The benefits of the cloud
- Simplicity: nothing to install, everything works immediately from a browser.
- Power: access to highly performant models without expensive hardware.
- Updates: you always benefit from the latest versions.
- Accessibility: usable from any connected device.
For most **everyday uses**, the cloud is the simplest and most powerful solution. It’s the default choice for discovering and using AI without technical constraints.
Cloud AI means using someone else’s supercomputer over the internet. It’s like renting a powerful tool instead of buying it—you get the latest tech without the hassle, but your data travels through their servers.
A small marketing agency uses cloud-based AI to generate social media posts. They don’t need to buy expensive hardware or install anything; they just log in, type their request, and get results instantly. No data leaves their control, but the AI provider handles all the heavy computing.
The right reflex. If your uses are common and your data non-sensitive, the cloud is almost always the best choice: simple, powerful, no hardware. Reserve the reflection on local AI for cases where confidentiality is truly crucial.
The benefits of local AI
Local AI excels in one **decisive point**: confidentiality. Your data never leaves your machine, eliminating any risk of reuse or interception by a third party. It also offers independence—no dependency on a provider, no subscription, and functionality even without a connection. In return, it requires sufficiently powerful hardware and a bit of technical know-how to install and run.
How to choose?
The choice comes down to your **priorities**. For simple, occasional use with non-sensitive data: the cloud wins hands down, thanks to its ease and power. To process confidential data, maintain full control, or operate without dependency: local AI makes perfect sense, provided you have the hardware and a minimum of skills. Many people actually combine both depending on the nature of each task.
To anticipate. Local AI isn’t « free » for all that: it requires a powerful computer (i.e., an investment) and energy. Evaluate your resources and skills carefully before diving in, or get help. It’s not always the simplest solution, despite its advantages.
Real-world scenarios: who chooses what
The curious individual: cloud without hesitation—zero installation, free for the most part, always up to date. The lawyer or doctor: local (or professional offer with strong guarantees) for anything related to files—the professional secret is non-negotiable. The SME: hybrid—cloud for writing and marketing, local or dedicated offer for customer data and accounting. The developer or equipped enthusiast: local for the pleasure of control, no subscription, and experimentation. The frequent traveler: a small local model on the laptop, which works on the plane and in dead zones. The right answer fits the need—and often, it’s a mix.
Frequently asked questions
Is local AI less performant?
It used to be significantly so, but the **gap is narrowing**: good local models now rival the cloud on many everyday tasks, while preserving confidentiality.
Do you have to choose one or the other?
Not necessarily: you can use the cloud for everyday tasks and local for sensitive data. Complementarity is often the best approach.
What hardware is needed for decent local AI?
A recent computer with a good amount of memory already runs lightweight but very useful models. For more ambitious models, a powerful machine is required—but the entry threshold is lowering with each generation of optimized models.
What to remember
Local AI or cloud AI: the choice depends on your priorities. The cloud offers simplicity, power, and accessibility, ideal for most everyday uses. Local AI guarantees confidentiality and independence, valuable for sensitive data, at the cost of suitable hardware and a bit of technical know-how. There is no universal answer: assess your needs in terms of confidentiality, power, and simplicity. And nothing prevents combining both: cloud for everyday use, local for what must stay with you.
A local and confidential AI project for your organization?
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