OpenBayes is a GPU cloud computing platform launched by Bei式计算, officially positioned as "making computing simpler" and "best practices for AI + HPC," mainly targeting users who need online machine learning and high-performance computing resources. According to the official page, the platform provides a variety of preconfigured computing power instances that can be used online without the need to build a local hardware environment yourself.
In terms of use, OpenBayes is aimed at AI and HPC scenarios and provides online machine learning services. After registering an account, users can directly use GPU and CPU computing power for common computing tasks such as model training and experiments. The official information also mentions that customized solutions can be provided for enterprises with needs, but the specific service contents and process materials are not provided.
In terms of main capabilities, the officially listed computing power configurations include: 1× NVIDIA RTX 5090, 32 GB VRAM, 16-core vCPU, 40 GB memory, 50 GB workspace; 1× RTX PRO 6000, 96 GB VRAM, 32-core vCPU, 90 GB memory, 200 GB workspace; 1× AMD EPYC 7773X, 64-core vCPU, 100 GB memory, 50 GB workspace; and 4-8 NVLink configurations, 80-640 GB VRAM, 64+ multi-core CPU, 512+ GB memory, 20+ TB storage space. The platform also provides CPU computing power, which the official information says is as low as 0.3 yuan/hour. In terms of storage, additional storage space starts at 0.5 yuan/GB/month. The page also indicates that registering immediately gives a "spend ¥10 get ¥10 coupon." The above prices and configurations are officially displayed information, and the actual ones are subject to the platform's current page.
In terms of usage, the official page provides a "Register Now" entry, and after registering you can experience the online machine learning service. Users with questions about pricing on the page can contact via online customer service. The platform also indicates that some clusters have recently completed security upgrade maintenance. Complete usage steps, image environments, framework support, data upload and instance management methods, etc., are not provided.
In terms of applicable scenarios, judging from the officially listed configurations, there are both single-card instances with 32 GB and 96 GB VRAM, as well as 4-8 card NVLink clusters with large VRAM, large memory, and large storage, which can cover training and computing needs of different scales. However, the official page does not clearly explain the specific models, frameworks, and industry scenarios supported, and related details are not currently provided.
In terms of limitations, the materials do not provide the free quota upper limit, billing cycle, refund policy, SLA, available regions, data security compliance statements, etc. Prices and configurationsmay change, and users should consult the platform's latest information before registering and purchasing.
