Dihuni, a global leader in artificial intelligence (AI), data center, and Internet of Things (IoT) solutions, today announced the launch of its new GPU Cloud platform. The company has rebranded the advanced Qubrid AI technology and is now offering GPU-as-a-Service (GPUaaS) and AI tools under its own brand.
For more than seven years, Dihuni has supported enterprise, educational, and government organizations worldwide with high-performance on-premises GPU servers and computing solutions. Building on this expertise, the company is now expanding into cloud-based GPU infrastructure, giving customers the flexibility to leverage cutting-edge resources without the significant capital investment required for hardware purchases.
The newly launched GPU Cloud enables enterprises, startups, and research institutions to access dedicated GPUs on demand, streamlining AI training, fine-tuning, inferencing, and enterprise-grade Retrieval-Augmented Generation (RAG) workflows. Customers can now choose between on-premises deployments, cloud services, or hybrid models based on their scalability, security, and budget needs.
Also Read: NVIDIA Launches Rubin CPX: Next-Gen GPU for Large-Context AI
With the growing demand for scalable GPU infrastructure, organizations often face complexity and delays in traditional hyperscale cloud environments. Through its partnership with Qubrid AI, Dihuni delivers a GPU Cloud platform designed for transparency, reliability, and performance ensuring seamless deployment across cloud, on-premises, or hybrid environments.
Key Features of Dihuni GPU Cloud Services
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On-Demand GPU Compute – Instant access to advanced GPU virtual machines for AI training, fine-tuning, and high-performance workloads.
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Dedicated Server Rental – Bare metal GPU servers available for monthly or annual rentals.
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AI Inferencing Pipelines – Scalable deployment and optimization of AI models for production use cases.
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Retrieval-Augmented Generation (RAG) – Enterprise-ready services combining knowledge retrieval with generative AI for enhanced accuracy and contextual intelligence.
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Hybrid Deployment Options – Workloads can run entirely in the cloud or on-premises via Qubrid AI’s controller software.
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Transparent GPU Allocation – Guaranteed dedicated GPU access without oversubscription or hypervisor inefficiencies.
By leveraging Qubrid AI’s next-generation platform technology, Dihuni ensures customers benefit from turnkey AI templates, enterprise-ready infrastructure, and performance-optimized environments helping accelerate AI innovation and reduce time to market.