Hyperbolic GPU Marketplace is solving AI compute shortages by making idle GPUs available at a fraction of the cost of traditional cloud providers. It started with real people running into real problems. A Berkeley professor struggling to run confidential AI research because she couldn’t get a machine. A startup abandoning AI training because cloud GPUs would kill their budget. A developer building a Perplexity-like app but being forced to limit users due to API rate limits and costs.
Jasper Zhang and Yuchen Jin saw this problem firsthand. AI innovation wasn’t failing due to lack of talent—it was failing because compute was too expensive and hard to access. But the GPUs were out there, sitting idle. There are over 2 billion personal computers in the world, most of them unused for 19+ hours a day. Ethereum moving to proof-of-stake alone freed up compute equal to 10 million RTX 3090s. The supply was there; it just wasn’t being used.
Hyperbolic built an on-demand GPU marketplace to fix this, making compute affordable for developers while letting suppliers monetize unused hardware. Up to 75% cheaper than AWS, Azure, and GCP, with instance deployment in under a minute.
Who Benefits
Developers:
Save up to 75% on GPU rentals.
No long-term commitments, scale up or down anytime.
Instances launch in under a minute with a simple UI or API.
Pre-configured Docker images for PyTorch, TensorFlow, and CUDA so developers can skip setup.
Secure SSH access, no manual approvals needed.
Smart billing, no charge for failed instances.
Suppliers:
Monetize idle GPUs by setting their own pricing.
5-minute onboarding, low setup requirements.
Future feature: Order book system for real-time pricing insights.
Hyperbolic’s GPU Marketplace addresses a critical challenge in AI: affordable access to compute resources. Hyperbolic aggregates underutilized GPUs from data centers, mining farms, and personal machines into a decentralized, on-demand platform, significantly cutting compute costs for developers and researchers by up to 75%.
Hyperbolic is cheaper than AWS by 9x for H100 SXM and 4.4x for H200, while also undercutting CoreWeave, RunPod, and Vast.ai.
Why It’s Different
Traditional cloud providers like AWS, Azure, and GCP have long wait times, rigid pricing, and vendor lock-in. Decentralized platforms like Vast.ai and RunPod are cheaper but unreliable, with inconsistent performance. Hyperbolic fixes this by offering low-cost, high-performance, automated compute with fault tolerance.
Powered by Hyper-dOS: Ensures automatic load balancing, failure recovery, and clustering for multi-GPU workloads.
Auto-Scaling: Workloads dynamically adjust to demand, so GPUs aren’t sitting idle.
Clustered GPU Allocation: Multi-GPU setups for AI training.
Future Support: Expanding to AMD and Intel GPUs.
What’s Coming Up
Market-driven pricing: Suppliers will soon be able to see demand in real-time and adjust pricing dynamically.
Expanded GPU support: AMD and Intel GPUs coming soon.
Better auto-scaling: Smarter clustering for large-scale AI workloads.
AI compute should be accessible and affordable. Hyperbolic makes that happen, giving developers cost-effective, flexible, and high-performance GPUs without the inefficiencies of traditional cloud.
