# Hyperbolic Hyperbolic is an open-access GPU and AI cloud for deploying on-demand H100, H200, B200, and other GPU capacity. It supports experimentation, training, fine-tuning, inference, and production workloads through on-demand instances, reserved clusters, and Private Cloud infrastructure. - Findings24: - ウェブサイト: - 料金: Freemium - カテゴリー: AI推論プラットフォーム, GPUクラウド ## Hyperbolicとは？ Hyperbolic is an open-access GPU and AI cloud that provides on-demand and dedicated compute for AI development. Users can launch H100, H200, B200, and other high-performance GPUs for experimentation, training, fine-tuning, inference, batch jobs, and production workloads. The platform offers three infrastructure options: usage-based On-Demand GPUs with no fixed commitment, Reserved Clusters for predictable capacity at discounted rates with commitments under one year, and Private Cloud infrastructure for teams seeking dedicated, long-term capacity through Hyperbolic’s supplier network. Its stated workflow supports choosing virtual machines or bare metal, selecting GPU counts from a single node to 1000+ GPUs, choosing InfiniBand or Ethernet, and launching a cluster in minutes. ## Hyperbolicでできること ### On-demand GPU instances Launch and manage GPU instances through a self-serve dashboard with usage-based billing and no minimum term for on-demand capacity. ### Reserved multi-GPU clusters Reserve dedicated GPU capacity for sustained workloads, with commitments under one year and discounted reserved rates. ### Private Cloud infrastructure Access dedicated GPU infrastructure through Hyperbolic’s supplier network for longer-term capacity and greater infrastructure control. ### Distributed cluster configuration Select a virtual-machine or bare-metal setup, set the GPU count from a single node to 1000+ GPUs, and choose InfiniBand or Ethernet interconnects. ### GPU selection and pricing Access H100, H200, and B200 capacity. Listed starting rates are $3.19 per GPU hour for H100 SXM, $3.99 for H200, and $5.99 for B200; rates are refreshed weekly based on supplier availability. ### Failure billing notifications Receive a notification within three minutes if an instance fails, with no charge for failed instances; billing applies to GPUs that come online. ## 利用シーン ### Foundation-model training Use reserved multi-node H100, H200, or B200 clusters for long training runs that need dedicated capacity and high-performance interconnects. ### Fine-tuning and LoRA Run fast iteration on open-source checkpoints and custom models with bare-metal single-node or small multi-node capacity. ### Research and evaluation Start on-demand instances for experiments, benchmarks, evaluations, data processing, and other compute-heavy research tasks. ### Agent workflows and automation Programmatically launch and manage GPU resources for agent workflows, evaluation pipelines, and other automated workloads. ### Production and private infrastructure Move predictable workloads to reserved clusters or Private Cloud environments when a team needs dedicated hardware, isolated networking, and longer-term capacity. ## よくある質問 ### How much does GPU rental cost? Listed starting rates are $3.19 per hour for an NVIDIA H100 SXM, $3.99 per hour for an H200, and $5.99 per hour for a B200. Pricing is refreshed weekly based on the best available supplier rates. On-demand billing is usage-based, and failed instances are not charged. ### Do on-demand GPUs require a contract or minimum term? No. On-demand instances do not require a minimum term or contract. Users can launch capacity for an experiment, benchmark, fine-tuning job, or training run and shut it down when finished. ### Can Hyperbolic run distributed training clusters? Yes. Clustered allocation can scale from a single node to 1000+ GPUs and supports InfiniBand or Ethernet interconnects. Reserved clusters provide dedicated capacity for workloads that need predictable availability. ### How do on-demand and reserved GPUs differ? On-demand GPUs are usage-based and have no fixed commitment. Reserved GPUs provide dedicated capacity at a discounted rate in exchange for a fixed-term commitment paid upfront, making them suited to predictable, sustained workloads. ## クイック情報 - **Category**: GPU cloud and AI infrastructure - **Primary users**: AI-native teams, researchers, developers, and infrastructure providers - **GPU types listed**: NVIDIA H100 SXM, H200, B200, and other high-performance GPUs - **Deployment range**: Single node to 1000+ GPUs - **Interconnect options**: InfiniBand or Ethernet - **API**: OpenAI-compatible API for serving AI workloads