Hivenet Compute gives you on-demand RTX 5090 and RTX Pro 6000 GPUs, plus vCPU instances, billed per second while they run. Hivenet owns and operates the infrastructure, with data centres in France, the UAE and the US, so EU teams can keep workloads and data in Europe.
Use it for training and fine-tuning, inference, notebooks, rendering and batch jobs. Launch from ready-made templates in a few minutes, or automate everything through the public Compute API. If you'd rather not run the serving layer yourself, the Inference API gives you an OpenAI-compatible endpoint.
Teams get organisations with role-based access, prepaid credits, and S3-compatible object storage alongside compute.
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Runpod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, Runpod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, Runpod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.
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Gemini Enterprise Agent Platform is Google Cloud’s next-generation system for designing and managing advanced AI agents across the enterprise. Built as the successor to Vertex AI, it unifies model selection, development, and deployment into a single scalable environment. The platform supports a vast ecosystem of over 200 AI models, including Google’s latest Gemini innovations and popular third-party models. It offers flexible development tools like Agent Studio for visual workflows and the Agent Development Kit for deeper customization. Businesses can deploy agents that operate continuously, maintain long-term memory, and handle multi-step processes with high efficiency. Security and governance are central, with features such as agent identity verification, centralized registries, and controlled access through gateways. The platform also enables seamless integration with enterprise systems, allowing agents to interact with data, applications, and workflows securely. Advanced monitoring tools provide real-time insights into agent behavior and performance. Optimization features help refine agent logic and improve accuracy over time. By combining automation, intelligence, and governance, the platform helps organizations transition to autonomous, AI-driven operations. It ultimately supports faster innovation while maintaining enterprise-grade reliability and control.
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Runware
Runware offers swift and economical generative media solutions that leverage custom-built hardware alongside renewable energy sources. Their Sonic Inference Engine achieves remarkable sub-second inference times with models such as SD1.5, SDXL, SD3, and FLUX, making it suitable for real-time AI applications while maintaining high quality. With the capability to support over 300,000 models, including LoRAs, ControlNets, and IP-Adapters, users can effortlessly switch between models as needed. Among its advanced capabilities are text-to-image and image-to-image generation, inpainting, outpainting, background removal, upscaling, and compatibility with technologies like ControlNet and AnimateDiff. Notably, Runware's entire infrastructure runs on renewable energy, resulting in a reduction of approximately 60 metric tonnes of CO₂ emissions each month. The platform features a versatile API that accommodates both WebSockets and REST, ensuring smooth integration without requiring costly hardware investments or specialized AI knowledge. This combination of speed, efficiency, and sustainability positions Runware as a leader in the generative media landscape.
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