Compute with Hivenet
Compute with Hivenet is the world's first truly distributed cloud computing platform, providing reliable and affordable on-demand computing power from a certified network of contributors.
Designed for AI model training, inference, and other compute-intensive tasks, it provides secure, scalable, and on-demand GPU resources at up to 70% cost savings compared to traditional cloud providers. Powered by RTX 4090 GPUs, Compute rivals top-tier platforms, offering affordable, transparent pricing with no hidden fees.
Compute is part of the Hivenet ecosystem, a comprehensive suite of distributed cloud solutions that prioritizes sustainability, security, and affordability. Through Hivenet, users can leverage their underutilized hardware to contribute to a powerful, distributed cloud infrastructure.
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Cocoon
Cocoon is a decentralized “confidential compute” network that enables users to run AI workloads on a distributed GPU infrastructure while preserving data privacy and control. It leverages the TON blockchain and connected GPU providers to execute AI tasks inside encrypted environments so that no single company or node operator can access your data, effectively returning compute and data ownership to users rather than centralized cloud providers. Jobs are executed only for the duration needed and leave no traces on centralized storage, helping ensure privacy, security, and decentralization. Cocoon’s design aims to break away from legacy big-tech cloud monopolies by offering a transparent, crypto-enabled infrastructure: providers are rewarded (e.g., in native tokens) for contributing resources, and users get access to powerful compute without giving away control.
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IONOS Cloud GPU Servers
IONOS GPU Servers provide an accelerated computing infrastructure designed to handle workloads that require significantly more processing power than traditional CPU-based systems. It integrates enterprise-grade NVIDIA GPUs such as the H100, H200, and L40s, as well as specialized AI accelerators like Intel Gaudi, enabling massive parallel processing for compute-intensive applications. GPU-accelerated instances extend cloud infrastructure with dedicated graphics processors so virtual machines can perform complex calculations and data-heavy operations much faster than conventional servers. It is particularly suitable for artificial intelligence, deep learning, and data science tasks that involve training models on large datasets or performing high-speed inference operations. It also supports big data analytics, scientific simulations, and visualization workloads such as 3D rendering or modeling that require high computational throughput.
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HPC-AI
HPC-AI is an enterprise AI infrastructure and GPU cloud platform designed to accelerate deep learning training, inference, and large-scale compute workloads with high performance and cost efficiency. It delivers a pre-configured AI-optimized stack that enables rapid deployment and real-time inference while supporting demanding workloads that require high IOPS, ultra-low latency, and massive throughput. It provides a robust GPU cloud environment built for artificial intelligence, high-performance computing, and other compute-intensive applications, giving teams the tools needed to run complex workflows efficiently. At its core, the company’s software focuses on parallel and distributed training, inference, and fine-tuning of large neural networks, helping organizations reduce infrastructure costs while maintaining performance. It is powered in part by technologies such as Colossal-AI, which significantly accelerates model training and improves productivity.
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