People always talk about gpus being overpriced.<p>The 980 was $549 in 2014, which seems to be about $730? today.<p>that means the 5080 at $999 is 1.3x the price of the 980. Yet the geometric mean score is 8.5x.<p>if you compare 980 vs 5090, you get 2.7x price, but 14.3x perf.<p>I would imagine this must be pretty good compared to many other components.
Well, cpus maybe, not sure about memory or hd/ssd.
When I was in grad school doing research on the still brand new "deep learning", having a GTX TITAN X was considered bragging rights. I remember complaining to my advisor about my paltry GTX 970. One lab even had a cluster of 4 of them!<p>Crazy that even the last generation cards are 15x faster for ML tasks.
It's neat to see the 4080 Super doing well compared to the 5080 and 5090. It's clearly behind them in many cases, but seems to have better performance per watt ratio than them while also having some of the lowest temps. Also interesting the regular 4080 isn't too far behind the Super.<p>This was an enjoyable and clean dataset to read through, thanks Michael.
It's a shame they didn't test the Titan V, it was released in 2017 yet still has the best FP64 performance of all the NVidia GPUs by a longshot.