Hardware Requirements

OctaneRender® requires a Nvidia CUDA-enabled video card.

OctaneRender® V4 runs on Kepler (e.g., GTX 680, GTX 690) GPUs, Maxwell (GTX 7xx, GTX8xx, GTX9xx), Pascal (GTX10xx) GPUs, the high-end GTX Titans, and Volta GPUs. Texture limits and differing power efficiency ratings also apply depending on the GPUThe GPU is responsible for displaying graphical elements on a computer display. The GPU plays a key role in the Octane rendering process as the CUDA cores are utilized during the rendering process. microarchitecture. GPUs from the GeForce line are usually higher clocked and render faster than the more expensive Quadro and Tesla GPUs.

GeForce cards are fast and cost effective, but have less VRAM than Quadro and Tesla cards. OctaneRender scales perfectly in a multi-GPU configuration and can use different types of Nvidia cards at once — e.g., a GeForce GTX 1080 combined with a Quadro 6000. The official list of Nvidia CUDA-enabled products is located at https://developer.nvidia.com/cuda-gpus.


If intending to use the engine's Out-Of- Core features, below is the bare minimum hardware specification recommended:


Looking to buy a new GPU for OctaneRender®?

There are several things to consider when purchasing a new GPU. You’ll want to purchase a video card with the largest amount of RAM (we recommend a minimum of 2GB Video RAM), with the most amount of CUDA Cores for your budget. Make sure your Power Supply can handle the new card as well. If you’re using a Mac, make sure that you purchase an Apple-approved GPU.


To use Octane's Denoiser features, additional memory is required to collect all necessary information. As an example, a 4k render will require around 5 GB, while an 8k render will require around 20GB. High Definition renders on the other hand will only require around 0.5GB.

On top of this memory will be required for geometry, textures, post processing buffers and for other 3D modeling software. So it is necessary to increase the system ram available along with about ~450Mb VRAM on devices to run the denosier.


Use Out-of-core features to move geometry and textures onto system memory to free up some space for the Denoiser on device if needed.