I Was Originally Using An Rtx 3080 Which Performs Very Well For Most Ml Tasks.
It has exceptional performance and features that make it perfect for powering the latest generation of neural networks. I didn't compare directly to other cards because the rtx titan was what i had available at the time. For the tasks that rely heavily on the gpu (primarily noise reduction and openfx), the rtx 3080 ti can be 12% faster than the rtx 3080, while the rtx 3070 ti is 21% faster than the rtx 3070.
It Depends How Complex Your Workload Is.
It was really confusing to choose between rtx 3080 and radeon 6800xt. I ended up switching to an rtx 3090 as i needed the additional vram to handle larger models. Since rtx 3080 founder's edition is not available now and only choice for 3080 is expensive after market cards.
Nvidia Rtx 3080 Ti Review & Benchmarks.
Lambda is working closely with oems, but rtx 3090 and 3080 blowers may not be possible. The 3080 should be more than fine for most applications though. I could do ai training with a gtx 1060 lol.
But With The Increasing And More Demanding Deep Learning Model Sizes The 12 Gb Memory Will Probably Also Become The Bottleneck Of The Rtx 3080 Ti.
Normally universities or colleges don’t require anything above. That these results for the rtx titan are much improved over past testing that i have done using earlier versions. Nvidia's rtx 3090 is the best gpu for deep learning and ai.
I Am Planning On Building A Computer For My Deep Learning Projects And Casual Gaming Too.
Lambda's rtx 3090, 3080, and 3070 deep learning workstation guide. 3070 is an obvious choice, if you want to make an affordable working machine with high end graphic specific machine without spending $1200 on 2080ti also with more cuda cores. Naturally, we’ll be stacking the rtx 3080 founders edition against the class of “80” cards from the rtx 20 series.