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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CoreWeave
CoreWeave is a cloud infrastructure provider specializing in GPU-based compute solutions tailored for AI workloads. The platform offers scalable, high-performance GPU clusters that optimize the training and inference of AI models, making it ideal for industries like machine learning, visual effects (VFX), and high-performance computing (HPC). CoreWeave provides flexible storage, networking, and managed services to support AI-driven businesses, with a focus on reliability, cost efficiency, and enterprise-grade security. The platform is used by AI labs, research organizations, and businesses to accelerate their AI innovations.
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SF Compute
SF Compute is a marketplace platform that offers on-demand access to large-scale GPU clusters, letting users rent powerful compute resources by the hour, not requiring long-term contracts or heavy upfront commitments. You can choose between virtual machine nodes or Kubernetes clusters (with InfiniBand support for high-speed interconnects), and specify the number of GPUs, duration, and start time as needed. It supports flexible “buy blocks” of compute; for example, you might request 256 NVIDIA H100 GPUs for three days at a capped hourly rate, or scale down/up dynamically depending on budget. For Kubernetes clusters, spin-up times are fast (about 0.5 seconds); VMs take around 5 minutes. Storage is robust, including 1.5+ TB NVMe and 1 TB + RAM, and there are no data transfer (ingress/egress) fees, so you don’t pay to move data. SF Compute’s architecture abstracts physical infrastructure behind a real-time spot-market and dynamic scheduler.
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CUDO Compute
CUDO Compute is a high-performance GPU cloud platform built for AI workloads, offering on-demand and reserved clusters designed to scale. Users can deploy powerful GPUs for demanding AI tasks, choosing from a global pool of high-performance GPUs such as NVIDIA H100 SXM, H100 PCIe, HGX B200, GB200 NVL72, A800 PCIe, H200 SXM, B100, A40, L40S, A100 PCIe, V100, RTX 4000 SFF Ada, RTX A4000, RTX A5000, RTX A6000, and AMD MI250/300. It allows spinning up instances in seconds, providing full control to run AI workloads with speed and flexibility to scale globally while meeting compliance requirements. CUDO Compute offers flexible virtual machines for agile workloads, ideal for development, testing, and lightweight production, featuring minute-based billing, high-speed NVMe storage, and full configurability. For teams requiring direct hardware access, dedicated bare metal servers deliver maximum performance without virtualization.
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