GPU servers and CPU servers are currently more popular types of servers. The main difference between the two lies in the processors used. A CPU server uses a central processing unit (CPU) as a computing core, while a GPU server uses a graphics processing unit (GPU) as a computing core. You can choose the appropriate server type according to your actual needs. If you need to process tasks that require massive parallel computing, such as image and video processing, machine learning, and deep learning, you can consider using a GPU server. If you want to handle tasks such as sequential calculations, memory-intensive tasks, and large databases, then CPU servers will be a good choice.

The differences between GPU servers and CPU servers include:

1. Computing ability

GPU servers have more powerful computing capabilities, because GPUs are designed for image processing and parallel computing, and can complete a large number of parallel computing tasks in a short period of time. The CPU server is more suitable for processing a single or a small number of computing tasks.

2. Parallel computing

GPU servers have higher parallel computing capabilities and can handle multiple computing tasks at the same time, while CPU servers are more suitable for processing sequential computing tasks.

3. Storage

GPU servers usually have more video memory and can store more image and video data. A CPU is a general-purpose processor that can handle many different types of tasks, including sequential calculations, memory-intensive tasks, and large databases, which makes CPU servers more flexible when processing multiple tasks.

4. Power consumption

The power consumption of a GPU server is usually higher than that of a CPU server because the GPU requires more power to run.

5. Price

GPU servers are usually more expensive than CPU servers because GPUs cost more and require more complex hardware architecture and software support.