NVIDIA GeForce RTX 3090 Review A Compute Powerhouse


NVIDIA RTX 3090 Specifications

The specifications for the NVIDIA RTX 3090 uses 24GB GDDR6X memory and 350W of power. Here is the high-level spec of the card compared to two GPUs from the previous generation, the Titan RTX and the Quadro RTX 8000.

GPU Comparison Chart NVIDIA Titan RTX Quadro RTX 8000 RTX 3090
GPU Comparison Chart NVIDIA Titan RTX Quadro RTX 8000 RTX 3090

The reason we are showing this higher-level spec comparison is that in our performance charts, the GeForce RTX 3090 is going to usually perform between the two options. I am currently working on a Quadro RTX 6000 review, so we will have comparisons from that angle soon.

Testing the NVIDIA GeForce RTX 3090

Here is our test configuration:

For the photos above, we had this GPU inside a Pelican 1485 case with foam we customized for the GeForce RTX 3090. That case, along with the studio blue backlighting is not included with the card (but maybe it should be a premium packaging bundle?)

NVIDIA GeForce RTX 3090 Heatsink Side 2
NVIDIA GeForce RTX 3090 Heatsink Side 2

Here is the obligatory GPU-Z shot of the NVIDIA RTX 3090 FE:


GPU-Z shows the primary stats of our testing the RTX 3090 FE. The GPU clocks in at 1395 MHz and can boost up to 1695 MHz. Pixel Fillrates run at 189.8 GPixels/s, and Texture Fillrate comes in at 556 GTexel/s, while memory runs at 1219 MHz. Again, we see 24GB of GDDR6X memory on the RTX 3090 FE.

NVIDIA GeForce RTX 3090 Heatsink Side 6
NVIDIA GeForce RTX 3090 Heatsink Side 6

Let us move on and start our testing with computing-related benchmarks.


  1. Are you using the Tensorflow 20.11 container for all the machine learning benchmarks? It contains cuDNN 8.0.4, while the already released cuDNN 8.0.5 delivers significant performance improvements for the RTX 3090.

  2. Chris Hubick

    Misha, as well known AMD shill, is being facetious – and this is a graphics card and not a compute card like the Ampere A100 – which trades the RT cores for FP64…

  3. Hi,

    I LOVE the GeForce and Threadripper compute reviews (especially the youtube video reviews!)

    However, for our work load, we really need to know how the hardware performs for double-precision memory-bound algorithms.

    The best benchmark that matches our problems (computational physics) is the HPCG benchmark.

    Would it be possible to add HPCG results for the reviews? (http://www.hpcg-benchmark.org/)

    Also, for some other computational physicists, having the standard LinPack benchmark (for compute-bound algorithms) would be really nice to see as well (https://top500.org/project/linpack/)

    – Ron


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