Alibaba Cloud cuts Nvidia GPU usage by 82% with new pooling system

Published on January 04, 2026 | Translated from Spanish
Technical diagram showing Alibaba Cloud's GPU pooling system, with multiple interconnected NVIDIA GPUs sharing resources, comparative efficiency charts before and after, and metrics showing an 82% reduction in usage.

Alibaba Cloud Reduces NVIDIA GPU Usage by 82% with New Pooling System

Alibaba Cloud has announced a revolutionary advance in cloud computing with a new pooling system that reduces NVIDIA GPU usage by an astounding 82%. This innovative technology allows 213 GPUs to perform work equivalent to 1,192 units, marking a significant milestone in resource optimization for artificial intelligence. 🚀

A Quantum Leap in Computational Efficiency

The new Alibaba Cloud pooling system represents a paradigm shift in GPU resource management. By enabling a pool of 213 GPUs to perform as if they were 1,192 units, the company has demonstrated an improvement of up to 9 times in effective output, translating into significant cost and energy savings for businesses relying on intensive computing for AI. 💡

Key Metrics of the Technological Advancement:
  • 82% reduction in NVIDIA GPU usage
  • Up to 9 times more output with the same resources
  • 213 real GPUs with the performance of 1,192 virtual ones
The pooling system allows 213 real GPUs to operate with the capacity of 1,192 virtual units

Pooling Technology for Scalable AI

The system developed by Alibaba Cloud works through an intelligent pooling architecture that optimizes GPU resource allocation according to the fluctuating demand of artificial intelligence workloads. This technology enables resource sharing among multiple users and applications without compromising performance, solving one of the biggest challenges in cloud computing for AI. ☁️

Technical Features of the System:
  • Dynamic pooling of shared GPU resources
  • Automatic allocation optimization based on demand
  • Scalable architecture for variable workloads

Impact on the Artificial Intelligence Industry

This technological advancement comes at a crucial time for the AI industry, where the global GPU shortage and high costs have represented significant barriers for many organizations. The ability to multiply the efficiency of existing GPUs could accelerate the adoption of AI at the enterprise level and make the technology more accessible for startups and SMEs. 📈

Benefits for Cloud Users:
  • Drastic reduction in GPU infrastructure costs
  • Greater access to computing resources for AI
  • Optimization of energy consumption and sustainability

The Future of Efficient Cloud Computing

The success of Alibaba Cloud with this system sets a new standard in computational efficiency for the industry. As the demand for AI resources continues to grow exponentially, technologies like this will be essential to maintain the scalability and sustainability of cloud services. This development not only benefits Alibaba's customers but also drives innovation across the entire cloud computing industry. ✨