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It's not weird at all. Those cards aren't meant as next buy for owners of non-Super 40xx cards. Cards are compared with cards that potential buyers currently have.
To me it's a bit strange because it assumes a buy / not buy perspective rather than a buy this / buy that perspective.
Is it a good time to pick up a 3060 now or no?
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My impression is a lot of the open source action is around the just-about-runs-in-12GB region - lots of models coming out with 7B/13B and 4-bit quantisation, a few 70B models (which won't fit in 24GB anyway) and only limited stuff in between. I suppose I could be getting a biased impression though, as of course many more people are in a position to recommend the more accessible models. What sort of things are you run…
As the ancestor commenter mentioned: > If you’re interested in ML training Training - at least the one I tried - requires to be run in fp16 mode. So a 7b net needs 14 GB for the model weights alone, plus some extra for the context and the stuff I don't really understand (some gradient values, oh that makes sense now that I've written it)
I’m wanting to know how this would compare to a 4090…as I’m thinking of upgrading my 3080FE.
AMD also released the 7600XT today. Not particularly interesting, but if you need/want a cheapish 16GB card you now have an option beside Intel. https://ir.amd.com/news-events/press-releases/detail/1176/am...
This is another very good release that is also being somewhat bizarrely panned too. Yeah, it's essentially a 7600 16GB/4060 16GB, and that's what people wanted a few months ago, more VRAM. It also opens up a bunch of possibilities for cheap ML (in the same way the 4060 Ti 16GB does). IMO this pretty well displaces the 4060 8GB and 16GB - it's cheaper (than even the already below-MSRP street prices) on 4060 Ti 8GB, it…
But future games are likely to run better in >8GB simply because the PS5 and XBox Series X have more than 8.
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With the current generation of text and image generators, 24GB is the sweet spot
I wouldn't be shocked if the 5090 is also the only one with 24GB. Seems like NVidia is trying their hardest to suppress memory increases.
> All three GeForce RTX 40 SUPER Series GPUs are faster than their predecessors It's weird that they're only comparing the new cards to the RTX 30's and 20's, and not the "v1" 40's. I assume the 4080 SUPER is faster than the 4080 (based on name?) but it seems cheaper and there's absolutely no comparison data
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It seems they’re being very careful not to undercut their enterprise offerings or even the 4090. Assuming they’re not completely tone deaf, I can only assume this is the explanation.
The Jetson AGX Orin Developer Kit [1] has 64 GB of unified 256-bit LPDDR5 memory. It costs $2,000 and might get some people someplace interesting. [1]: https://developer.nvidia.com/embedded/learn/getting-started-...
Here's a direct amazon link: https://www.amazon.com/dp/B0BYGB3WV4
And a running demo: https://forums.developer.nvidia.com/t/llama-2-llms-w-nvidia-...
Earlier quoted context omitted.
It seems they’re being very careful not to undercut their enterprise offerings or even the 4090. Assuming they’re not completely tone deaf, I can only assume this is the explanation.
The Jetson AGX Orin Developer Kit [1] has 64 GB of unified 256-bit LPDDR5 memory. It costs $2,000 and might get some people someplace interesting. [1]: https://developer.nvidia.com/embedded/learn/getting-started-...