Overview
AIBrix is a cost-efficient and pluggable infrastructure framework for GenAI inference, designed for large-scale LLM deployment. Built under the vLLM project, it provides production-grade components including routing, autoscaling, distributed inference, and KV caching to build scalable LLM services on Kubernetes.
Key Features
- High-density LoRA management and model adapters for lightweight adaptation and deployment
- LLM gateway and intelligent routing for multi-model and multi-replica traffic management
- Autoscaler tailored for inference workloads that dynamically scales resources to optimize costs
- Distributed inference, distributed KV cache, and heterogeneous GPU scheduling support
Use Cases
Enterprise LLM inference platform and service deployment. Mixed-model deployments with cost optimization requirements. Research and engineering scenarios for building and evaluating large-scale inference baselines on Kubernetes.
Technical Details
Implemented with Go and Python, designed for Kubernetes-native deployment. Supports distributed inference, distributed KV cache, and heterogeneous GPU scheduling to maximize throughput and cost efficiency. Open source under Apache-2.0 license with extensive documentation and community support.