IO.NET vs Theta EdgeCloud

Access to 300,000+ verified GPUs from 139 countries with 6,000+ cluster-ready GPUs

Deploy clusters in under 90 seconds with auto-scaling capabilities

Choose from containers, Ray clusters, or bare metal based on workload needs

Uses the same distributed computing framework that OpenAI used to train GPT-3

AI models, smart agents, and API integration for workflow automation

Kernel-level VPN with secure mesh protocols for data protection

Combines traditional cloud GPUs via Google Cloud and AWS with 30,000+ community-operated edge nodes for flexible compute.

Supply-demand driven pricing where node operators set rates and users select GPUs based on availability and cost.

Routes heavy training jobs to cloud/datacenter GPUs and distributes parallelizable inference across edge nodes.

Reroutes jobs to healthy nodes if a community node goes offline mid-task, ensuring workload continuity.

Docker-based job execution with Jupyter Notebook and SSH access for flexible development environments.

On-demand model inference APIs and dedicated AI model serving with support for popular generative AI models.