At Hyperbolic, we’re building an open and accessible AI ecosystem—of the people, by the people, for the people. Because we embed ourselves with our users, we know that they are looking for AI inference providers that can offer quick onboarding of the latest open source instruct and base models at low costs with reliable data privacy and verifiability.
Many of the top AI inference providers meet some of these demands, but only Hyperbolic meets them all.
Model Availability and Quality
Hyperbolic serves the most unique open source models that aren’t readily available elsewhere, while providers like Together.ai and Fireworks.ai only focus on onboarding those most popular. Our users gain access to cutting-edge models days or even weeks before they appear on other platforms. What's more significant is our commitment to running models in BF16 precision, compared to the FP8 format used by competitors. This technical choice isn't just a number—it results in notably higher quality outputs from open source models, matching more closely to their original training quality.
Lepton AI and Anyscale have also made strides in model deployment, but Hyperbolic's platform stands out by offering both base and instruction-tuned model variants. This flexibility allows developers to choose the most suitable version for their specific use case as well as raw model capabilities.
Cost Structure and Efficiency
Many AI inference providers, like Together.ai and Fireworks.ai, rely on traditional cloud infrastructure and are forced to feed into the impression of scarcity of compute with overwhelming prices. By leveraging our innovative decentralized network of underutilized GPUs, Hyperbolic delivers inference at a fraction of the cost compared to providers relying on centralized resources. Our distributed approach allows us to pass significant savings to our users without compromising on performance or reliability.
Privacy and Security
Data privacy is a major consideration for organizations deploying AI solutions. Unlike some providers who maintain opaque data-handling practices, Hyperbolic implements rigorous data privacy measures. None of your inputs or outputs are stored or used for model training—a unique commitment we make to our community of builders.
Verified Inference
When leveraging distributed compute resources, verifiability of outputs is a natural concern. Hyperbolic’s Proof of Sampling protocol (PoSP) is a groundbreaking feature that utilizes concepts of game theory to guarantee honesty in our network.
PoSP provides cryptographic verification that model outputs are genuine and unmanipulated, adding a layer of trust and transparency that other platforms lack. In a world where AI outputs have significant implications, this verification capability sets a new standard for responsible AI inference and model deployment.
Hyperbolic’s Open and Accessible AI Ecosystem
While providers like Anyscale and Lepton AI continue to iterate on traditional centralized infrastructure, Hyperbolic is pioneering a new paradigm in AI inference. Our decentralized approach not only democratizes access to AI computing resources but also creates a more sustainable and efficient ecosystem for AI inference.
Hyperbolic is building more than just another inference platform—we're creating the foundation for the next generation of AI applications. Take your ideas hyperbolic at app.hyperbolic.xyz.
About Hyperbolic
Hyperbolic is democratizing AI by delivering a complete open ecosystem of AI infrastructure, services, and models. Through coordinating a decentralized network of global GPUs and leveraging proprietary verification technology, developers and researchers have access to reliable, scalable, and affordable compute as well as the latest open-source models.
Founded by award-winning Math and AI researchers from UC Berkeley and the University of Washington, Hyperbolic is committed to creating a future where AI technology is universally accessible, verified, and collectively governed.
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