Introducing AIBrix: Cost-Effective and Scalable Control Plane for vLLM

Open-source large language models (LLMs) like LLaMA, Deepseek, Qwen and Mistral etc have surged in popularity, offering enterprises greater flexibility, cost savings, and control over their AI deployments. These models have empowered organizations to build their own AI-driven applications, from chatbots and agents to content generation and recommendation systems. However, while these models are widely accessible, turning them into cost-efficient, production-grade APIs remains a significant challenge. Achieving low-latency, scalable inference requires more than just an optimized model—it demands a holistic system approach that spans multiple layers, from the model itself to the inference engine and the surrounding infrastructure.