High-Performance GPU Infrastructure
DeployInstantly
GPU Infrastructure for Every Stage
On-Demand GPUs
Launch H100, H200, B200, and other high-performance GPUs in minutes with no commitment. Best for researchers, developers, and teams that need flexible, usage-based GPU access for experimentation, training, fine-tuning, batch jobs, and short-term workloads.
- Fast, flexible GPU access
- None
- Usage-based
Reserved Clusters
Reserve dedicated GPU capacity at discounted rates with commitments under one year. Best for AI-native startups, research labs, and infrastructure teams running steady workloads that need predictable access without depending on on-demand availability.
- Predictable GPU capacity
- Under one year
- Discounted reserved rates
Private Cloud
Access Hyperbolic’s supplier network for dedicated GPU infrastructure at the lowest long-term rates. Best for teams ready to scale with predictable capacity, stronger infrastructure control, and longer-term GPU commitments.
- Long-term GPU infrastructure
- More than one year
- Lowest long-term rates
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Why AI teams choose Hyperbolic
Affordable compute
Rent GPUs starting at $3.19/GPU/hr, cutting compute costs for training and inference.
GPU capacity for every workload
Access H100, H200, and B200 capacity without traditional cloud procurement cycles or unnecessary operational complexity.
Direct GPU access
Run training, fine-tuning, inference, and compute-intensive workloads with direct access to your GPU environment and the control to configure it around your workload.
A clear path to production
Start with flexible On-Demand capacity. As usage becomes more predictable, move into Reserved or Private Cloud infrastructure without starting over with a new compute partner.
Smart billing notifications
Get notified within 3 minutes if an instance fails. No charges for failed instances — only pay for GPUs that come online.
Competitive pricing at every stage
Launch GPUs when you need them, scale usage up or down, or reserve capacity for sustained workloads that require predictable availability.
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More Flexibility,
Less Overhead
Traditional cloud GPU access often means long procurement cycles, rigid commitments, and extra platform complexity. Hyperbolic gives AI-native teams, researchers, and developers a faster way to access GPU compute, from on-demand GPUs to reserved clusters and Private Cloud infrastructure.
AWS
Azure
CoreWeave
Fluidstack
Lambda Labs
RunPod
How it Works
Getting started with Hyperbolic doesn’t require a crash course in cloud engineering. The flow is straightforward, so you can move from idea to execution without losing momentum.
Choose your setup: fast VMs or bare metal performance
Set your GPU count: scale from a single node to 1000+ GPUs
Pick your interconnect: InfiniBand or Ethernet
Launch a cluster in minutes with no provisioning delays
One GPU Cloud, Every Use Case
Hyperbolic gives builders access to GPU compute for:
Foundation-model training
Fine-tuning and LoRA
Research experiments
Batch compute jobs
Evaluation and data processing pipelines
Long-running training workloads
Agent workflows and automation
Production AI workloads that need predictable GPU capacity
Built for Every Workload
Evaluating Open Models at Scale
Generative AI development
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Hyperbolic's computing platform has provided robust and reliable support for our Chatbot Arena. We run our FastChat and SLang applications on this platform to serve state-of-the-art open vision-language models. We are thrilled to leverage their solutions to deliver exceptional user experiences.
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GPU Rental FAQs
GPU rentals on Hyperbolic start at $3.19/hr for an NVIDIA H100 SXM. H200s are $3.99/hr and B200s are $5.99/hr, with pricing refreshed weekly based on the best available rates from suppliers. You pay only for what you use, with no charges for failed instances. Payment works by credit card or Stripe.
No. On-demand GPU instances do not require a minimum term or contract. You can launch capacity for a quick experiment, a benchmark, a fine-tuning job, or a multi-day training run, then shut it down when the work is complete. For teams that need guaranteed capacity for longer-running workloads, reserved clusters provide dedicated GPUs without preemption.
Yes. Clustered allocation scales from a single node to 1000+ GPUs and deploys in minutes, with high-bandwidth interconnects to keep throughput high and latency low for data- and model-parallel training. Renting GPUs in a cluster also unlocks additional savings versus provisioning nodes individually.
Both options are available through the Hyperbolic app and run on the same platform. On-Demand GPUs are billed by usage with no fixed commitment, making them best for flexible, short-term, or unpredictable workloads. Reserved GPUs provide the same capacity at a discounted rate in exchange for a fixed-term commitment paid upfront. They are best for predictable, sustained workloads where you know you will need the capacity for the full reservation period.
