Unite Global GPU Resources Deploy Massive Models, Orchestrate Cloud-Edge AI
Next-generation computing network that connects distributed GPU resources across regions, data centers, and security domains. Deploy 100B+ parameter models across clusters, orchestrate cloud-edge-end collaborative inference, and transform idle resources into productive AI infrastructure. Perfect for enterprises with scattered compute resources, massive model requirements, and strict compliance needs.
Built for Scaling teams
Empower your team with cross-domain computing networks that adapt to your needs, enabling true computing power flow across regions.
Cross-Domain
Virtual intelligent computing factory enabling cross-domain AI services and computing power allocation.
Secure
Compute power comes to you, data stays in place. Ensuring data security while enabling cross-domain access.
Scalable
Intelligent computing center management with global resource mapping and monitoring for true scalability.
Edge-Ready
Support for heavy edge computing and cloud-edge collaborative scenarios in embodied intelligence and industrial applications.
Key Features
Enterprise-grade infrastructure for global AI operations
Virtual Intelligent Computing Factory
Computing domain management, computing domain scheduling rule configuration, cross-domain AI service management.
Intelligent Computing Center Management
Computing cluster registration, management, proxy control, global computing resource map, global monitoring and alerting.
Data Security
Compute power comes to you, data stays in place. Ensure data security while enabling cross-domain compute access.
Advanced Capabilities
Breakthrough features for massive models and cloud-edge orchestration
Cross-domain AI Services
Cross-domain training tasks, fine-tuning tasks, collaborative inference, and high-availability AI model services.
Cloud-Edge-End Collaborative Inference
Orchestrate AI inference across cloud, edge, and end devices seamlessly. Route requests intelligently based on latency, data locality, and resource availability. Perfect for real-time applications requiring low-latency edge responses with cloud-scale model capabilities.
Cross-Cluster Model Sharding
Deploy massive models that exceed single-cluster capacity by sharding across multiple clusters. Automatically partition model layers and coordinate inference across distributed resources. Run 100B+ parameter models using idle GPUs scattered across your infrastructure.
Idle Resource Optimization
Transform idle GPU capacity into productive AI infrastructure. Automatically discover and leverage underutilized resources across clusters to deploy ultra-large models or scale inference workloads. Maximize ROI on existing hardware investments.
Edge Computing Support
Support for heavy edge computing and cloud-edge collaborative scenarios in embodied intelligence, transportation, and industrial applications.
Key Benefits
Transform your infrastructure with measurable business impact
Cross-domain Computing Power Allocation
Solve multiple regional computing center usage imbalance and scattered computing power device utilization without intruding on end-users.
Data Security Guarantee
When borrowing computing network resources, computing power comes to you while data stays in place, ensuring data security.
Unified Cloud-Edge Inference
Deploy models once, run everywhere. Seamlessly route inference requests between cloud and edge based on latency requirements and data locality. Reduce edge deployment costs while maintaining sub-100ms response times for real-time applications.
Deploy Models Beyond Single-Cluster Limits
Break through hardware constraints. Deploy 100B+ parameter models by intelligently sharding across clusters. Leverage idle resources scattered across your infrastructure to run models that would otherwise require massive upfront investment.
Turn Idle GPUs into Revenue
Monetize underutilized GPU capacity automatically. Transform idle resources into productive AI inference infrastructure without manual intervention. Increase overall cluster utilization by 40-60% while reducing infrastructure waste.
Improved Resource Utilization
Address low overall computing power utilization and idle computing power due to inability of single-point computing power to support large models.
True Computing Power Flow
Abstract to computing resource layer to achieve true computing power flow, not just server-level matching.
Target Customers
Built for organizations with complex infrastructure and compliance needs
Large Enterprises
Enterprises with high data security requirements (e.g., public security, finance) needing cross-domain compute access.
Large Computing Power Operators
Operators with scattered heterogeneous computing power and edge-side computing power that cannot be coordinated.
Edge Computing Industries
Industries requiring embodied intelligence, transportation, intelligent driving, and industrial edge computing capabilities.
Pricing Model
Custom pricing for large enterprise deployments
Custom Enterprise Pricing
Large orders of at least ¥2 million per year, single price per order. Includes multi-cluster Tensor OS, additional computing network scheduling layer components, and global central control components.
Build Your Computing Network
Contact us to learn how Tensor Net can transform your computing infrastructure