| BMS：8*4090D - $ 1100/month 8*4090 - $ 1300/month 8*A100 pcie40G - $ 2100/month 8*A100 pcie80G - $ 5000/month 8*A100 nvlink80G - $ 6500/month 8*A800 nvlink80G - $ 6300/month 8*H20 - $ 5000/month 8*L20 - $ 1500/month 8*H100 - $ 11000/month |
 Shenzhen Cloud Engine possesses a vast array of high-performance GPU computing power, offering not only a rich variety of graphics card types but also a collection of cost-effective computing resources for your selection. Computing power is an indispensable resource in the modern computing field, and its importance is not only reflected in graphics rendering but also extends to general-purpose computing and the AI domain, with particularly prominent applications in deep learning. As a powerful driving force behind AI technology, our GPU computing power provides services such as various GPU cloud rentals, graphics card purchases, and full server purchases. This offers users flexible, efficient, and affordable access to powerful computing capabilities, greatly facilitating the rapid deployment of new technologies and applications for our clients. A massive pool of high-performance cloud computing resources to help you easily meet the explosive demand for computing power in various cycles. Support for flexible scheduling and deployment of computing power across multiple domestic and international regions. 3090/4090 CPU*Optional
Memory*512～1024
GPU*8
System*480G～960G Storage*2T-8T A100/A800 CPU*Optional
Memory*512～1024
GPU*8
System*480G～960G Storage*2T-8T H100/H800 CPU*Optional Memory*512～1024 GPU*8 System*480G～960G Storage*2T-8T H20/L20及其他 CPU*Optional Memory*512～1024 GPU*8 System*480G～960G Storage*2T-8T Artificial Intelligence AI training and inference, image recognition, speech recognition, etc.
In the periodic large-scale training and inference of large models, there is a need for a massive high-performance single-precision floating-point computing cluster and dynamic GPU computing resources to effectively support deep learning training and real-time AI inference scenarios. Scientific computing Seismic analysis, molecular modeling, genomics, computational fluid dynamics, etc.
In the field of scientific computing, extremely powerful double-precision computing capabilities are often required. While consuming substantial computational resources, these processes also generate a large amount of temporary data, which places extremely high demands on storage, bandwidth, and latency. Graphics processing Graphics production and rendering, engineering modeling and simulation, medical imaging, game testing, etc. In scenarios such as film and animation rendering, CAE simulation and modeling, graphic and image processing, real-time streaming, and cloud gaming, there is a significant consumption of computing clusters and graphics card resources. |