AI cloud vendors extend upward, GMI Cloud enhances agent industrialization.

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The products showcased by AI cloud vendors are extending beyond GPU computing power to model invocation and agent deployment.

At the 2026 World Artificial Intelligence Conference (WAIC) held from July 17 to 20, AI cloud service provider GMI Cloud showcased products including AI Cloud, Cluster Engine, Inference Engine, and AgentBox. These products cover aspects such as GPU resources, computing power scheduling, model inference, and AI agent deployment.

This product portfolio reflects changes in AI companies' demands for cloud infrastructure.

In the past, when companies purchased AI cloud services, their primary concern was whether they could obtain enough GPUs. As large models gradually enter real business scenarios, companies also need to address issues like computing resource scheduling, multi-model access, high-concurrency operation, and application deployment.

GMI Cloud attempts to connect these stages.

The underlying AI Cloud mainly provides GPU resources. As one of the Reference Platform NVIDIA Cloud Partners, GMI Cloud offers GPU resources such as Nvidia H100, H200, B200, GB200, and GB300, mainly used for model training, fine-tuning, and production-level inference.

On top of the GPU resources, GMI Cloud also showcased Cluster Engine, a computing power management platform tailored for AI workloads, mainly solving the problem of how GPU resources can be used effectively.

For AI enterprises, computing power costs depend not only on individual GPU prices, but also on resource utilization rate, task queue time, and cluster stability. Model inference traffic often fluctuates significantly; allocating large numbers of GPUs with fixed configurations can lead to idleness, while temporary expansion during business peaks may affect response speed.

The cluster scheduling platform thus becomes an additional capability as AI cloud vendors extend upward.

Another highlight from GMI Cloud at WAIC is AgentBox, a deployment, operation, and distribution platform for production-level AI agents. It has a built-in MaaS model library, allowing seamless access to 170+ world-leading large models via a single API key.

The products showcased reflect changing trends in the AI cloud market.

As simply acquiring GPUs is no longer the only issue companies face, AI cloud vendors are also beginning to extend from resource providers to the model and application layers.

For GMI Cloud, GPUs are still the foundation of their product ecosystem, but their business boundaries have expanded to inference and agent operation. The focus of future competition among AI cloud vendors may not only be on how much computing power they possess, but also on whether they can help companies deploy models and agents stably into real business scenarios.

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