GLM Built Its Own Inference Infrastructure

The article underscores how GLM chose to build its own inference infrastructure to better control performance, cost, and scalability for AI workloads. For CIOs and technology leaders, the strategic takeaway is that as AI adoption grows, generic platforms may not deliver the latency, efficiency, or operational flexibility needed, making build-vs-buy decisions for inference a core infrastructure issue. IT organizations should expect greater responsibility for GPU economics, capacity planning, and runtime optimization as AI moves from experimentation to production at scale.