Club Benefits
ChatGPT is the main Cloud AI for millions of users. The experience is arguably easy, clear and usually gives them the results they want after a little prompting. But there's another side of the AI world that's growing fast: local AI. It's just as easy but far more private.
Instead of sending your prompts to powerful servers in the cloud, local AI runs directly on your computer. Tools like LM Studio and Ollama make it possible to download AI models and use them entirely offline. The appeal is obvious: more privacy, more control and no monthly subscription required.
I've spent the past several weeks testing both cloud AI and local AI to see how they compare in everyday use. While they often look similar on the surface, the experience can be surprisingly different.
Here are the seven biggest differences I discovered.
1. Privacy
The biggest advantage of local AI is that your data never has to leave your device.
When you use a cloud-based chatbot, your prompts are sent to remote servers for processing. Major AI companies have privacy policies and security safeguards in place, but your data still travels beyond your computer.
With local AI, everything stays on your machine. Documents, conversations, notes and personal files never need to be uploaded anywhere.
For anyone working with sensitive information, that distinction alone may be enough to choose local AI.
Winner: Local AI
2. Speed
Local AI feels surprisingly fast. I expected local AI to feel sluggish, especially on a consumer laptop.
Instead, many responses appeared almost instantly. Because there's no network request involved, local AI can start generating text the moment you hit Enter. There's no waiting for servers to receive, process and return your prompt.
For shorter conversations, local AI often felt more responsive than cloud AI.
The trade-off is that speed depends heavily on your hardware. A powerful computer can feel lightning fast. An older machine may struggle.
Winner: Tie
3. Intelligence
It's safe to say that most of the time Cloud AI is usually smarter. This was the most obvious difference during testing.
When I gave both systems complex reasoning tasks, research questions and writing prompts, cloud AI consistently produced stronger responses, but that's not surprising.
Companies like OpenAI, Anthropic and Google run some of the largest and most powerful AI models in the world. Those models require enormous computing resources that most consumer laptops simply can't match.
Local models have improved dramatically, but they still tend to struggle with the kinds of difficult tasks that cloud AI handles effortlessly.
Winner: Cloud AI
4. Deep research
Cloud AI has the advantage in research — and in this category it wasn't even close. Cloud AI increasingly combines language models with web search, citations and real-time information. That means it can help explain current events, summarize newly published articles and research topics that didn't exist during training.
Local AI generally lacks those built-in capabilities, especially the plug-and-play Local AI. But unless you install additional tools and configure them yourself, a local model only knows what was included in its training data.
For anyone who regularly uses AI for learning, fact-checking or staying current, cloud AI remains the better choice.
Winner: Cloud AI
5. Offline AI
One of my favorite aspects of local AI is that it works even when the internet doesn't. Sure, this may sound obvious, but what's surprising is the number of offline uses.
During testing, I disconnected from Wi-Fi and continued chatting with local AI as if nothing had happened. Obviously, Cloud AI relies on an internet connection and functioning servers.
Most people won't notice this difference often, but travelers, remote workers and anyone with unreliable internet may appreciate having an AI assistant that works entirely offline.
Winner: Local AI
6. Customization
The customization experience is completely different and almost hard to "grade" in this test. Cloud AI platforms are designed to be simple, while local AI platforms are designed to be flexible.
With local AI, I could switch between models, adjust settings, experiment with different personalities and fine-tune how responses were generated. For me and other passionate AI users, that flexibility is one reason to use it.
Yet, the downside is that customization often comes with complexity. New users may find the number of options overwhelming.
Winner: Local AI
7. The costs look very different
Clouad AI is free with limits. However, ChatGPT Plus, Claude Pro and Gemini Advanced all charge monthly fees in exchange for access to their most capable models.
Local AI software is often free, but the catch is hardware. Running advanced models smoothly may require a powerful computer with substantial RAM and a capable GPU.
Essentially, cloud AI spreads the cost over time, while local AI often requires a larger investment up front.
Winner: user preference
One surprise: Local AI may use more energy than you think
Going into this test, I assumed local AI would automatically be the more efficient option because it doesn't rely on massive data centers. But research suggests the picture is more complicated.
A 2025 study from Greenspector found that running AI models directly on smartphones can increase battery drain and energy consumption because all of the processing happens on the device itself. While cloud AI still requires significant energy inside data centers, modern cloud infrastructure is often heavily optimized for AI workloads.
In practice, this means local AI may be better for privacy, but not necessarily better for the environment.
Winner: Depends on your setup
How to try local AI
If all this talk about local AI has you wanting to try it for yourself, the quickest way is to start with LM Studio —it's one of the easiest ways to run local AI without touching code. Just follow these steps and you'll be up and running in minutes.
- Step 1: Download LM Studio
- Step 2: Choose a model (beginner-friendly models include Gemma 3, Qwen 3 and Llama 4 Scout. The smaller models run faster while larger models are smarter.
- Step 3: Start chatting. From now on, it's essentially the same experience as ChatGPT.
Which one should you use?
After testing both approaches, I don't think cloud AI and local AI are actually competitors. Using local AI has taught me interesting tricks with cloud AI and vice versa.
They're really just different tools for different situations. If you want the smartest models, built-in web access and the easiest user experience, cloud AI is still the clear winner.
If privacy, customization and offline access matter most, local AI offers advantages that cloud platforms simply can't match.
Personally, I've found myself using both. I rely on cloud AI for research, brainstorming and complex projects. But for sensitive documents, personal notes and experiments, local AI has become a surprisingly useful addition to my workflow.
From my testing, it's obvious that not one approach is better than the other but ultimately finding the smartest ways to use using cloud and local together.
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