In the chart above, NVIDIA’s RTX 3090 is twice as fast as the RTX Titan, which was the top consumer video card from the last generation, while costing $1000 less and maintaining the same amount of VRAM. The faster the graphic card, the faster the GPU rendering. GPU rendering is becoming more and more popular as hardware gets more affordable, while performance keeps increasing. NUMA configurations also tend to perform worse. Generally, a more powerful CPU is better than a dual-socket or multi-socket CPU system. V-Ray runs on both AMD and Intel processors, so the choice is down to user preference. As a rule of thumb, the faster the hardware, the faster the rendering.

Another use case is the hybrid rendering with V-Ray GPU, where both the GPU and CPU components can render at the same time. When using the GPU engine, V-Ray utilizes the graphics cards for rendering, but also partially uses the CPU (for example, when calculating the Light cache GI solution). V-Ray GPU uses NVidia CUDA or RTX device(s) to perform the ray tracing calculations.Īs you could see, V-Ray is developed and optimized to take advantage of the full capabilities of all hardware components: CPU, GPU, RAM, storage, network and motherboard. Since GPUs are specifically designed for massively parallel calculations, they can speed up the rendering process significantly by an order of magnitude. GPU rendering allows V-Ray to perform the ray tracing calculations on the GPU cards installed in the system, rather than the CPU. V-Ray offers two rendering engines including V-Ray and V-Ray GPU.

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