Recently, SiliconFlow has formally introduced its enterprise-grade MaaS (Model as a Service) platform. This platform provides a comprehensive, closed-loop solution that encompasses every stage, from heterogeneous computing power management, model training, and inference deployment to scenario-specific applications. It enables clients in sectors like power, energy, manufacturing, finance, and the internet to implement large-scale models in a manner that is both cost-effective and high-performing, while also being secure and reliable.

The platform arrives pre-integrated with more than 100 widely-used open-source and closed-source large models. It supports inference acceleration across a variety of computing power cards. Moreover, it allows for the swift adaptation and synchronization of new models to enterprise private environments within a mere 1 - 3 days, substantially reducing the deployment timeline.

Leveraging intelligent routing, a self-developed inference framework, and dynamic scaling technology, the platform strikes an optimal balance between high performance and cost-efficiency. It also integrates built-in model evaluation and optimization toolchains, streamlining the deployment process. Furthermore, the platform guarantees the security and reliability of models, data, and services through multi-tenant data isolation, fine-grained permission control, and full-link auditing mechanisms.