Windows 11 can run local AI, but in real day-to-day use it often feels like it's working against you—especially once you start stacking multiple AI tools, projects, and installs. What I found is that Linux generally delivers a smoother "AI desktop" experience: setups are more straightforward, common AI instructions match what you're actually running, and GPU-accelerated apps tend to behave more consistently. The result is less time spent troubleshooting and more time getting outputs.
On Windows 11, the biggest pain points showed up around friction and interruptions—extra steps during installs, more chances for version mismatches, and occasional driver or update moments that break a working setup. Even when performance is similar, the overall workflow can feel slower because you're dealing with more overhead and more "little problems" that add up.
Linux stood out for predictability: once things were working, they stayed working. Tools were easier to manage, projects were easier to separate, and the system felt more responsive while running AI tasks alongside normal desktop work.
If you're building a desktop or laptop mainly to run AI locally, this video explains why Linux often ends up being the more reliable, less stressful choice—and how to decide if it makes sense for you.
