I cut $800 in subscriptions by running free tools on hardware I already owned

[danie10@squeet.me]

“Subscription costs have a way of feeling invisible. You might have a cloud storage here, an AI tool there, a transcription service you barely use anymore. All of this can add up to something substantial. But if you own a mid-range GPU, there’s a good chance you’re paying for things your hardware could handle for free. I have an NVIDIA RTX 3060 (currently around $250), and last year it saved me $819.96 by allowing me to cut or downgrade four subscriptions. It wasn’t by doing anything exotic, but by running free, open-source tools locally that do the same job.”

I started to realise this myself, just this week, as I was experimenting with AI tools and AI image generation. I made the mistake when I upgraded my video card a few months ago, from a 6 GB VRAM card, to a 12 GB VRAM card. This was because I had a game that really wanted about 8 GB of VRAM and I reckoned that the 12 GB would give it a bit of headroom. DaVinci Resolve Studio also wanted 8 GB of VRAM for its new AI functions.

Yep, I know the prices get expensive as you go higher up, but I was thinking in a gaming mode, and not what else I could use that card for. Thinking now with this other mindset I realise I should have pushed higher on my new card.

Still that said, you can work efficiently with a 12 GB card, or even a bit smaller, if you don’t run too many GPU intensive apps together, and you can get away with smaller more efficient AI models too.

See howtogeek.com/ways-my-old-nvid…
#Blog, #GPU, #opensource, #subscriptions, #technology