High-Performance Inference Engine for LLMs

xLLM is a high-performance inference engine designed for large language models (LLMs), optimized specifically for diverse AI accelerators. This framework enables efficient enterprise-grade deployment, significantly enhancing performance while reducing operational costs.

Key features include:

• Service-Engine Decoupled Architecture - Achieves breakthrough efficiency through elastic scheduling and dynamic PD disaggregation.
• Multi-Stream Parallel Computing - Utilizes graph fusion optimization and speculative inference for improved throughput.
• Global KV Cache Management - Implements intelligent offloading and prefetching strategies.
• Dynamic Load Balancing - Ensures efficient distribution of resources among multiple experts.

xLLM supports the deployment of mainstream models such as DeepSeek-V3.1 and Qwen2/3, facilitating applications in intelligent customer service, risk control, and supply chain optimization.