AI Inference & Serving

Production-Grade Infrastructure for AI Inference and Deployment

Low Latency · High Throughput · Elastic Scaling
Reliable and scalable inference infrastructure for large models and AI applications

Triton Inference Server

Supports mainstream deep learning frameworks such as PyTorch and TensorFlow,

enabling high-concurrency inference, dynamic batching, and multi-model management

for production-grade AI serving.

TensorRT Acceleration

GPU-based performance inference optimization engine

By employing operator fusion and precision optimization, inference latency is significantly reduced and throughput performance is improved.

with support for INT8 and FP16 inference.

vLLM Inference Engine

A high-performance inference framework designed for large language models,

leveraging PagedAttention to improve memory efficiency

and significantly boost concurrency and response performance.

Low-Latency Nodes

Global Infrastructure for AI Inference and Serving

Acceleration Plans

For latency-sensitive and high-throughput workloads, optional acceleration plans are available:

Node and Performance Description

Multi-region global deployment across Asia, North America, and Europe

U.S. inference nodes available in major metropolitan areas, including: Silicon Valley, Los Angeles, Dallas, Chicago, New York, and Virginia

Typical inference latency for 70B-scale LLMs:

Core Asia regions:10–20ms
Major U.S. cities: 15–30ms

Up to 100Gbps network bandwidth per node

Integrated with global CDN and intelligent routing for stable cross-region access

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