Choose Your Solution
Start with the product that matches your workload. Use On-Demand GPUs for flexible compute, Reserved for predictable capacity at a lower rate, Private Cloud for dedicated infrastructure, or Inference API for serving models through an OpenAI-compatible endpoint.On-Demand GPUs
Best for: Experimentation, model training, fine-tuning, custom deployments, and flexible GPU access. Launch high-performance GPU instances when you need capacity without committing before your workload is proven. On-Demand GPUs give teams flexible access to GPU infrastructure for testing, training, fine-tuning, benchmarking, and early production workloads. Learn more about On-Demand GPUs →Reserved
Best for: Sustained GPU demand, production workloads, predictable usage, and teams that want a lower rate than on-demand. Reserved gives you the same GPU capacity you would use on-demand, reserved for a fixed term at a discounted rate. It runs on the same platform and the same hardware — you simply commit to the capacity up front for a lower price. Reserved is self-serve in the app, and larger commitments can also be arranged with our team. Learn more about Reserved →Private Cloud
Best for: Enterprise AI teams, sensitive workloads, dedicated environments, and teams that need stronger isolation and operational control. Private Cloud gives organizations dedicated GPU infrastructure for production-scale AI workloads. It is designed for teams that need predictable capacity, stronger isolation, custom infrastructure requirements, and a long-term partner for AI compute planning. Learn more about Private Cloud →Quick Comparison
GPU availability noteHyperbolic provides access to high-performance GPU capacity, including H100, H200, and B200 infrastructure. Availability may vary by product, supply, region, and configuration. Check the Hyperbolic console for current On-Demand and Reserved GPU options, or contact our team for Private Cloud requirements.
Who Uses Hyperbolic?
AI-Natives
For teams building AI products where compute access directly affects product velocity. Start on demand, test quickly, and move into reserved infrastructure as usage grows.Research Teams and AI Labs
For teams running experiments, benchmarking models, fine-tuning workloads, and scaling research infrastructure without waiting through long procurement cycles.Infrastructure and Engineering Leaders
For teams responsible for sourcing, validating, and scaling GPU infrastructure across training, fine-tuning, and production workloads.Enterprise AI Teams
For organizations that need predictable capacity, dedicated environments, stronger isolation, and a path from pilot projects to production AI infrastructure.Get Started
Get Started Guide
Set up your account and launch your first workload in minutes
Need Help Choosing? Not sure which service is right for you? Check our detailed comparison guide or contact our team for personalized recommendations.