NVIDIA GeForce RTX 3090 Review A Compute Powerhouse


NVIDIA RTX 3090 FE Rendering Related Benchmarks

Next, we wanted to get a sense of the rendering performance of the GeForce RTX 3090.

Arion v2.5

Arion Benchmark is a standalone render benchmark based on the commercially available Arion render software from RandomControl. The benchmark is GPU-accelerated using NVIDIA CUDA. However, it is unique in that it can run on both NVIDIA GPUs and CPUs.

Download the Arion Benchmark from here. First-time users will have to register to download the benchmark.

NVIDIA RTX 3090 FE Arion
NVIDIA RTX 3090 FE Arion

Like our first set of benchmarks, the GeForce RTX 3090 shows impressive single GPU results. This is a huge plus when one considers the costs of moving to more expensive dual GPU configurations in NVLink. We will see this trend in our rendering benchmarks.

MAXON Cinema4D 3D

ProRender is an OpenCL based GPU renderer that is available in MAXON’s Cinema4D 3D animation software. A fully functional 42-day trial version is available for downloaded from the MAXON website here. Note: Even after expiration, the trial can still be used to measure render times.

NVIDIA RTX 3090 FE Cinema4D
NVIDIA RTX 3090 FE Cinema4D

With a one-second difference, the GeForce RTX 3090 approaches Titan RTX and Quadro RTX 8000 in NVLink configurations.

OctaneRender 4

OctaneRender from Otoy is an unbiased GPU renderer using the CUDA API. The latest release, OctaneRender 4, introduces support for out of core geometry. Octane is available as a standalone rendering application, and a demo version is available for downloaded from the OTOY website here.

NVIDIA RTX 3090 FE OctaneRender
NVIDIA RTX 3090 FE OctaneRender

OctaneRender generates a very heavy load on GPUs. Here the GeForce RTX 3090 again approaches Titan RTX and Quadro RTX 8000 NVLink configurations.


Redshift is a GPU-accelerated renderer with production-quality. A Demo version of this benchmark can be found here.

NVIDIA RTX 3090 FE Redshift
NVIDIA RTX 3090 FE Redshift

With Redshift, we have a new version of the Demo at v3.0.31 to take advantage of the latest NVIDIA RTX 3000 series of graphics cards. Here, the GeForce RTX 3090 takes the top spot with a blistering 180 seconds to finish. This result is over twice as fast as the Titan RTX!

Next, we will have 3DMark results before moving onto power consumption, thermals, and our final thoughts.


  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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