What is still worth upgrading on an older PC?

[HitmanMatt53]

What devices are actually good enough right now to run local models smoothly?

[MurkyInlet]

Local AI has gone from a niche hobby to something a lot more people are actually considering for day to day use

What stands out to me is how quickly the hardware side has improved, because better laptops and desktop GPUs are making on device AI feel less like a compromise and more like a real option

There is still a tradeoff though. Cloud models usually have the edge on raw capability, but local models win on privacy, offline use, and not depending on a subscription for every task

I think the interesting question now is not whether local AI can replace cloud AI completely, but whether it is already good enough for most common jobs like writing help, coding support, and quick research

For regular users, that shift could matter a lot more than people expect because it changes who controls the data and how much it costs to use AI over time

Should I cite a summary generated by Google's AI Overviews feature like a source? | MLA Style Centerstyle.mla.org

[HardyBoy13]

Cloud AI still feels better for complex questions, so where do you draw the line?

[Mark7]

This seems useful for developers, but do average users really care about running models locally?

[Hannah]

I tried a small local model and it was decent, but the speed was not amazing. Has that improved lately?

[NightHarbour]

Would you trust a local model for work tasks, or only for personal experiments?

[Terry]

The subscription cost argument is getting stronger every month, especially if local tools keep improving.

[QuantumDay]

Is the bigger trend the model itself, or the fact that consumer hardware is finally catching up?

[BretHart_MainEvent]

Disagree slightly on the GPU-only mantra. My old workstation with an aging Xeon and 128GB of system RAM handles llama.cpp offloading remarkably well. Sure, it is not blazing fast, but being able to load a 30B model into system memory and let the CPU churn away overnight for heavy data processing is a totally viable budget workaround.