I work in AI and I'm surrounded by RTX-4090 and H100 servers but for much of the day to day AI training I use my RTX-970 in the desktop on my desk for convenience and it works just fine for most cases.
Literally 2 meters from my desk is a 2x RTX-4090 server and many times I just use my 8 year old GPU anyway so you don't need it.
For a long time I thought my RTX-2060 was just not capable and the other day I did a ffmpeg GPU transcode and was surprised by how well it did. So now I am thinking about putting on some of Google's new Gemma edge models (probably the smallest will work with my 6GB VRAM + 2 GB) setup. I am not a 100% sure what that 2GB is but I think it is borrowing from the system in some manner.
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I work in AI and I'm surrounded by RTX-4090 and H100 servers but for much of the day to day AI training I use my RTX-970 in the desktop on my desk for convenience and it works just fine for most cases.
Literally 2 meters from my desk is a 2x RTX-4090 server and many times I just use my 8 year old GPU anyway so you don't need it.
For a long time I thought my RTX-2060 was just not capable and the other day I did a ffmpeg GPU transcode and was surprised by how well it did. So now I am thinking about putting on some of Google's new Gemma edge models (probably the smallest will work with my 6GB VRAM + 2 GB) setup. I am not a 100% sure what that 2GB is but I think it is borrowing from the system in some manner.
Video encoding uses dedicated silicon, it's not using the card's compute.