Is it better to run an AI model on my own computer or use a cloud service?

It depends entirely on what you value more: your privacy or your convenience. Running a model on your own computer — often called 'local inference' — means everything stays on your machine. No data ever leaves. For a therapist, a lawyer, or anyone handling sensitive information, this is a huge deal. The catch? You need a pretty beefy computer. A single GPU with enough memory can run smaller, open models surprisingly well. According to a recent paper, the trend of running large language models on a single GPU is having its 'Stable Diffusion moment' — meaning it's suddenly becoming practical for normal people, not just researchers. On the other hand, using a cloud service like ChatGPT or Claude is effortless. You open a browser, you type, you get an answer. The company handles all the expensive hardware. The model is usually much larger and more capable than what you can run at home. The trade-off is that you're sending your conversations to a server you don't control. For most casual questions, that's fine. For a secret business strategy? Maybe not. Here's a practical way to think about it. Imagine you need to summarize a public news article. Cloud is perfect. Now imagine you need to analyze a private contract with client names and financial figures. A local model, even if it's slightly less eloquent, is the safer bet. A tip I've learned the hard way: don't obsess over running the biggest model. A smaller, well-tuned 7-billion-parameter model on your own machine can feel faster and more responsive than a giant cloud model, simply because there's no network lag. Sometimes, speed feels smarter.