OctaneRender® requires a Nvidia CUDA-enabled video card. It runs on Kepler (e.g., GTX 680, GTX 690), Maxwell (GTX 7xx, GTX8xx, GTX9xx), PascalTM (GTX10xx), high-end GTX Titans, VoltaTM, and Turing 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 clocked higher 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 well in a multi-GPU configuration, and can use different types of NVIDIA® cards at once, such as 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.
To use the engine's out-of-core features, we recommend using at least the following hardware:
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 suggest at least 2 GB VRAM), 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 the OctaneRender® denoiser features, you need additional memory to collect all necessary information. As an example, a 4k render requires around 5 GB, while an 8k render requires around 20 GB. High-definition renders require around 0.5 GB.
Memory is also required for geometry, textures, post-processing buffers, and for other 3D modeling software, so it's necessary to increase the system RAM along with about 450 MB 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 the device.