- THETA Network is launching the beta version of EdgeCloud’s hybrid edge-cloud computing platform on June 25, 2025.
- EdgeCloud connects community-run edge nodes with traditional cloud GPUs for high-performance computing tasks, including AI workloads.
- Major universities and professional sports teams already use EdgeCloud, with rewards paid in TFuel based on USD value.
- The platform features dynamic GPU pricing, job orchestration, failover support, and lets users contribute idle GPUs for compensation.
- EdgeCloud supports a wide range of advanced computing jobs, from AI model inference to scientific research and video processing.
Theta Network will release the beta version of EdgeCloud’s hybrid edge-cloud computing infrastructure on June 25, 2025. The new system combines community-operated edge nodes—devices run by individuals—with traditional cloud-based Graphics Processing Units (GPUs). This move aims to support the growing demand for distributed and AI-ready computing power in various fields.
According to Theta Labs, EdgeCloud enables users with idle GPUs to share their hardware in exchange for TFuel tokens, which are calculated based on the U.S. dollar market rate. Leading organizations, including academic institutions such as Stanford University, Seoul National University, KAIST, University of Oregon, Michigan State University, and NTU Singapore have adopted EdgeCloud for AI research and development. Top sports brands, such as the NBA’s Houston Rockets, NHL’s Vegas Golden Knights and New Jersey Devils, and MLS’s San Jose Earthquakes and Philadelphia Union also use the platform.
"EdgeCloud’s hybrid architecture balances computing workloads between high-end cloud servers and a global network of edge nodes," states Theta Labs. This structure allows for flexible, scalable, and lower-cost computing solutions for tasks like AI model inference, 3D rendering, financial simulations, and video transcoding.
EdgeCloud participants can set their own hourly rental rates for contributed GPUs using the platform’s decentralized marketplace. Developers and users choose nodes that best fit their requirements and budget. Supported GPUs range from consumer models, such as NVIDIA 3070s, to enterprise-grade A100s and H100s. The system uses containerized jobs, allowing a variety of computational workloads to run reliably across hardware types.
The EdgeCloud beta will feature job orchestration—a system that distributes tasks based on node performance—failover support for improved reliability, and an API for developers to submit and track jobs. According to Theta Labs, future updates will allow users to further customize node preferences and access detailed analytics dashboards.
To join the network, contributors need a compatible Nvidia GPU (8GB vRAM or higher), a recent operating system (like Ubuntu 22.04 or Windows 10/11 for preview testers), a CPU with at least 4 cores, 16GB RAM, 256GB storage, and a stable 100 Mbps or faster internet connection. Monthly rewards for running jobs or offering on-demand model inference are distributed at the beginning of each month.
Detailed setup instructions and frequently asked questions are available on the Theta EdgeCloud website and through the provided FAQs.
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