Review: NVIDIA Titan V, The Best You Shouldn’t Buy

Posted on December 26, 2017 by Brad Sams in Hardware with 8 Comments

Earlier this month, NVIDIA surprised many in the high-end PC community with the announcement of the Titan V. The card, which is not targeted at gamers, is designed for machine learning hardware and comes with a hefty price point of $2999. In addition, this card is based on the Volta architecture, unlike the current gen cards that are built on Pascal.

This card is for those who need high-compute performance to crunch massive databases for machine learning and AI applications. But, for those of you lucky out there to not have a budget and want to throw everything you can into a gaming rig, the Titan V is a great choice. And seeing as this card is $3000, I borrowed this card from Ryan and you should check out their very in-depth review, here, because if I spent $2999 on a graphics card, there would be no food on my table.

Everything aside, this card is the top dog of the market right now and no one is disputing this. It’s not a value proposition, it’s honestly not even a great gaming card, but it is the best card that money can buy right now.

With 5120 CUDA Cores, 640 Tensor Cores, 1200MHz core clock and a 1455 MHz boost clock, the Titan V is a beast. When you add in that it has 12GB of VRAM and can hit FP32 performance of 13.8TFLOPS, this card kills it in the performance category. Keep in mind the TDP is 250w running across 21.1 billion transistors.

During the holiday break, I have been playing a few different games with this card and documented the performance in the graphs below. The takeaway here is that it bests the 1080Ti in every benchmark and when you are paying a roughly $2200 premium for the Titan V over a 1080Ti, that’s not a surprise.

While the performance gains are a solid 10-15FPS over the 1080Ti, that’s not a massive jump but it is notable. But there is a huge caveat here, the drivers for this card are far from optimized for gaming and even at this point, they are barely optimized for just about anything as the card is only a few weeks old and it’s a new architecture.

The TimeSpy score is the easiest way to see the performance gains and it’s quite noticeable with a score crossing the 10,000 point mark. For reference, the machine used to test these cards is an i7-6700k, 16GB of RAM with Samsung 840 EVO SSD that is running on top of an MSI Z170A KRAIT GAMING motherboard. All cards used in these benchmarks tests are kept at their factory clock with the latest available drivers.

Also, the PUBG benchmarks are running on version 1.0 of that game which is notoriously un-optimized which means you shouldn’t look too deeply at these specs. That being said, it continued the trend of outperforming the 1080Ti in all aspects of that game with all settings on Ultra.

I fully expect performance out of this card to increase a modest amount during the next few months as NVIDIA releases driver updates and fine tunes the hardware. That being said, what we are seeing here is the future of the GTX lineup and what will likely become the 1100 series cards as well.

At the end of the day though, you should not buy this card for gaming. Yes, it is a beast, yes, it is the high watermark for the industry but for the gaming crowd, it is not a good value in any way as the performance gains are not large enough over a 1080Ti at this time to justify the price tag.

That being said, if money is no object and you are building for the highest performance possible, the Titan V is the card for you. And of course, if machine learning is your thing, the Titan V is the obvious choice.

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Comments (9)

9 responses to “Review: NVIDIA Titan V, The Best You Shouldn’t Buy”

  1. Demileto

    "...if I spent $2999 on a graphics card, there would be no food on my table."

    Psh, who needs food? ?

  2. webdev511

    Looks like it's overkill for video transcoding too. The future is available for those that can afford it.

  3. Jacob Klein

    I thought 2000 series of GPUs was next, not 1100 series.

  4. Jules Wombat

    It would have been nice to get some re4alistci ML benchmarks against some heavy TensorFlow calculations, e.g. running this unit against ImageNet, ResNet,GoogleLeNet Convolutional networks which can be download from the web. The expected customers of this Titan device need ML benchmark to compare this against a 2x SLI connected 1080Tis. I note that the Titan has dramatically improved the 64Bit FPS capability but with only marginal improvement on the basic precision FPS. So its unclear how many ML practioners will see the full benefits unless they keep 64bit floats throughout.

    I built a ML rig a couple weeks back with a 1080Ti 11Gb GPS, M.2 based SSD, X99 Gaming Motherboard and 32 Gb of DDR4 RAM etc, to process my keras/Tensorflow code on the graphics card. I would only be interested in this card, if I was confident it had at least 4x convolutional epoch performance improvements over my 1080Ti.

    How does Nvidia think this unit can scale up, when a typical ATX gaming motherboard can only fit two of these, as like the 1080 Ti cards, they physically occupy across two pci lanes. How do I build a rig with say 6 x Titan V for serious ML crunching?

    Hopefully, however, in a couple of years down the line, the ML computing environment will become more affordable to general ML practitioners.

  5. ErichK

    But can it run ... (you know what game I'm talking about)?

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