I wouldn't be running out and grabbing RTX 2080 SUPER graphics cards in NVLink for 1440p gaming, but Shadow of the Tomb Raider hits its ceiling of just under 150FPS on all 3 of the SUPER NVLink configurations at 1440p in SOTTR.

The 2060 super should be near the same as the 2070 (and it has 8GB mem!) NVIDIA stopped production of the 10xx cards (and my beloved Titan V ...expensive but wonderful) If you can get them for a bargain it's worth considering. Most importantly it fits the budget so either way I'll get great performance. Where the RTX 2070 SUPER in NVLink could 'only' do 112FPS average in Shadow of the Tomb Raider at 4K, the spruced up RTX 2080 SUPER cards in NVLink hit the magical 4K 120FPS mark. Press J to jump to the feed. Sure, some of these results are rather tasty but you're spending $1400 on graphics cards that would be better spent on a single RTX 2080 Ti.

Really appreciate the reply. I don't think I'd recommend buying two RTX 2070 SUPER graphics cards for gaming these days unless you are aware of their issues in some games, and no multi-GPU support in many games and/or 100% scaling so that you fully benefit from buying the second graphics card. Previous Next Sort by votes.

You get a much more modest speedup WRT Turing (some 10% best case scenario), but you still get to double (or almost) the available memory. Eidos Montreal R&D department made lots of changes to the engine during the development of Shadow of the Tomb Raider to make it one of the best-looking games out right now.

Thanks for the encouragement, but I seem to have abandoned the 2080 Ti in the hopes of a more balanced build xD. 120FPS average on RTX 2070 SUPER NVLink is a 62% increase in performance over the single card at just 74FPS at 4K.
This means RTX 2070 SUPER in NVLink easily beats the higher-end RTX 2080 Ti and its 191FPS average, with the RTX 2070 SUPER NVLink setup 22% faster.

Posted by 11 months ago.

Personally when I am seeing 100% on Utilization I'm pretty happy. NVLink looks EXTREMELY cool and I really wanna get involved!
If any company representative wishes to respond, we will publish the response here. https://benchmark.chaosgroup.com/next/gpu, If this is your first visit, be sure to So why not? [ResNet-50 fp32] TensorFlow, Training performance (Images/second) comparison using 2 NVIDIA RTX 2070-Super GPU's, [ResNet-50 fp16 Tensor-cores] TensorFlow, Training performance (Images/second) comparison using 2 NVIDIA RTX 2070-Super GPU's, TensorFlow LSTM: Big-LSTM 1 Billion Word Dataset, Appendix: Peer to Peer Bandwidth and Latency results for 2 RTX 2070 Super GPU's, TensorFlow Performance with 1-4 GPUs -- RTX Titan, 2080Ti, 2080, 2070, GTX 1660Ti, 1070, 1080Ti, and Titan V, Note: How To Install JupyterLab Extensions (Globally for a JupyterHub Server), Note: How To Copy and Rename a Microsoft WSL Linux Distribution, Note: Self-Signed SSL Certificate for (local) JupyterHub, Note: JupyterHub with JupyterLab Install using Conda, RTX3090 TensorFlow, NAMD and HPCG Performance on Linux (Preliminary), NVIDIA GeForce RTX 3080 10GB & RTX 3090 24GB Review Roundup, Unreal Engine 4.25 - NVIDIA GeForce RTX 3080 & 3090 Performance, V-Ray GPU Rendering - NVIDIA GeForce RTX 3080 & 3090 Performance, RTX3080 TensorFlow and NAMD Performance on Linux (Preliminary), PCIe X16 vs X8 for GPUs when running cuDNN and Caffe, NVIDIA DIGITS with Caffe - Performance on Pascal multi-GPU, Install Ubuntu 16.04 or 14.04 and CUDA 8 and 7.5 for NVIDIA Pascal GPU, NVIDIA Titan GPUs (3 generations) - CUDA 8 rc performance on Ubuntu 16.04, 2 x RTX2070 Super with NVLINK TensorFlow Performance Comparison, 2 x NVIDIA RTX 2070 Super + NVLINK Bridge, Container image: nvcr.io/nvidia/tensorflow:19.02-py3 for "Big LSTM" and "CNN".

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