Load Balanced Inference Distribution

via “distributed inference with multi-node deployment and load balancing”

Fast LLM/VLM serving — RadixAttention, prefix caching, structured output, automatic parallelism.

Unique: Implements multi-node inference with automatic load balancing and support for multiple parallelism strategies (tensor, pipeline, data), managing inter-node communication and request distribution transparently.

vs others: Supports distributed inference across multiple nodes with automatic load balancing, unlike vLLM which is primarily single-node focused. Includes fault tolerance and graceful degradation.