Alok(@analogalok):Ziphu achieved 3× performance gains and Nvidia level cost parity on domestic Chinese chips for serving GLM 3.5 Flash!. The wildest detail in the GLM-5.3-Flash release: Ziphu used a GLM 5.3 infrastructure agent to write custom GPU kernels, debug bottlenecks, and build an inference engine on top of SGLang, creating a self optimizing feedback loop that achieved 3× performance gains and Nvidia level cost parity on domestic Chinese chips.

Alok

@analogalok

Mechatronics Engineer AI belongs on your device. • Offline inference • No subscriptions. Teaching you to own your AI Intelligence Stack

가입 November 2013

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Alok@analogalok

2026.08.26 14:47

Ziphu achieved 3× performance gains and Nvidia level cost parity on domestic Chinese chips for serving GLM 3.5 Flash!. The wildest detail in the GLM-5.3-Flash release: Ziphu used a GLM 5.3 infrastructure agent to write custom GPU kernels, debug bottlenecks, and build an inference engine on top of SGLang, creating a self optimizing feedback loop that achieved 3× performance gains and Nvidia level cost parity on domestic Chinese chips.