Integrating SGLang into Spyre in Under a Week with AI

A two-person team used AI coding agents to integrate SGLang with IBM Spyre in under a week, producing a plugin of roughly 1,500 lines built on existing PyTorch Spyre support and SGLang's extension points. SGLang delivered about 3.6× the throughput of the reference PyTorch inference implementation using torch-spyre and was on par with vLLM on the measured workloads for Granite 3.3 8B and Gemma 4 26B A4B. Prefix sharing through RadixCache worked without any Spyre-specific changes.