Integrate SGLang into IBM Spyre within less than a week using AI tools
A team of two, with the help of an AI programming agent, completed the integration of SGLang and IBM Spyre in less than a week, building a plugin with about 1,500 lines of code. SGLang's inference throughput on Spyre is about 3.6 times higher than the reference PyTorch implementation (using torch-spyre) and performs comparably to vLLM on Granite 3.3 8B and Gemma 4 26B A4B workloads.



















